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a222d266bd9062726c4662f3ffc10eddf6fbd279
mtp_chrome-extension/build/camera.bundle.js
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franklin a222d266bd commit
2024-07-12 22:00:06 +01:00

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/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
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/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
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/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function ca(...e){Be().getBool("IS_TEST")||Be().getBool("PROD")||console.warn(...e)}function pa(...e){Be().getBool("IS_TEST")||Be().getBool("PROD")||console.log(...e)}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const da=We("kernelRegistry",(()=>new Map)),fa=We("gradRegistry",(()=>new Map));function ha(e,t){const n=ka(e,t);return da.get(n)}function ma(e){return fa.get(e)}function ga(e){const t=da.entries(),n=[];for(;;){const{done:r,value:a}=t.next();if(r)break;const[o,s]=a,[i]=o.split("_");i===e&&n.push(s)}return n}function ya(e){const{kernelName:t,backendName:n}=e,r=ka(t,n);da.has(r)&&ca(`The kernel '${t}' for backend '${n}' is already registered`),da.set(r,e)}function ba(e){const{kernelName:t}=e;fa.has(t)&&Be().getBool("DEBUG")&&ca(`Overriding the gradient for '${t}'`),fa.set(t,e)}function va(e,t){const n=ka(e,t);if(!da.has(n))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);da.delete(n)}function wa(e){if(!fa.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);fa.delete(e)}function xa(e,t){ga(e).forEach((e=>{ya(Object.assign({},e,{backendName:t}))}))}function ka(e,t){return`${t}_${e}`}
/**
* @license
* Copyright 2023 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Sa(e){return e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray}var Ea=n(3720);
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
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/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function La(e,t){return"string"===t?Ua(e):za([e],t)}function za(e,t){if("string"===t)throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=Ha(e)),Be().getBool("DEBUG")&&me(e,t),function(e,t){return e instanceof Float32Array&&"float32"===t||e instanceof Int32Array&&"int32"===t||e instanceof Uint8Array&&"bool"===t}(e,t))return e;if(null==t||"float32"===t||"complex64"===t)return new Float32Array(e);if("int32"===t)return new Int32Array(e);if("bool"===t){const t=new Uint8Array(e.length);for(let n=0;n<t.length;++n)0!==Math.round(e[n])&&(t[n]=1);return t}throw new Error(`Unknown data type ${t}`)}function Ba(){return Be().platform.now()}function Va(e,t){return Be().platform.fetch(e,t)}function Ua(e,t="utf-8"){return t=t||"utf-8",Be().platform.encode(e,t)}function ja(e,t="utf-8"){return t=t||"utf-8",Be().platform.decode(e,t)}function Wa(e){return null!=Be().platform.isTypedArray?Be().platform.isTypedArray(e):Sa(e)}function Ha(e,t=[],n=!1){if(null==t&&(t=[]),"boolean"==typeof e||"number"==typeof e||"string"==typeof e||Fe(e)||null==e||Wa(e)&&n)t.push(e);else if(Array.isArray(e)||Wa(e))for(let r=0;r<e.length;++r)Ha(e[r],t,n);else{let r=-1;for(const t of Object.keys(e))/^([1-9]+[0-9]*|0)$/.test(t)&&(r=Math.max(r,Number(t)));for(let a=0;a<=r;a++)Ha(e[a],t,n)}return t}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class qa{constructor(e,t){this.backendTimer=e,this.logger=t,null==t&&(this.logger=new Ka)}profileKernel(e,t,n){let r;const a=()=>{r=n()};let o;const s=Ba();if(this.backendTimer.timerAvailable())o=this.backendTimer.time(a);else{a();for(const e of r)e.dataSync();o=Promise.resolve({kernelMs:Ba()-s})}if(Be().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let t=0;t<r.length;t++){const n=r[t];n.data().then((t=>{Ga(t,n.dtype,e)}))}return{kernelName:e,outputs:r,inputs:t,timeMs:o.then((e=>e.kernelMs)),extraInfo:o.then((e=>null!=e.getExtraProfileInfo?e.getExtraProfileInfo():""))}}logKernelProfile(e){const{kernelName:t,outputs:n,timeMs:r,inputs:a,extraInfo:o}=e;n.forEach((e=>{Promise.all([e.data(),r,o]).then((n=>{this.logger.logKernelProfile(t,e,n[0],n[1],a,n[2])}))}))}}function Ga(e,t,n){if("float32"!==t)return!1;for(let t=0;t<e.length;t++){const r=e[t];if(isNaN(r)||!isFinite(r))return console.warn(`Found ${r} in the result of '${n}'`),!0}return!1}class Ka{logKernelProfile(e,t,n,r,a,o){const s="number"==typeof r?ue(`${r}ms`,9):r.error,i=ue(e,25),u=t.rank,l=t.size,c=ue(t.shape.toString(),14);let p="";for(const e in a){const n=a[e];if(null!=n){const r=n.shape||t.shape,a=r.length;p+=`${e}: ${a}D ${a>0?r:""} `}}console.log(`%c${i}\t%c${s}\t%c${u}D ${c}\t%c${l}\t%c${p}\t%c${o}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Qa=20,Ya=3,Xa=7;function Za(e,t,n,r){const a=Te(t),o=function(e,t,n,r){const a=ee(t),o=r[r.length-1],s=new Array(o).fill(0),i=t.length,u="complex64"===n?no(e):e;if(i>1)for(let e=0;e<a/o;e++){const t=e*o;for(let e=0;e<o;e++)s[e]=Math.max(s[e],Ja(u[t+e],0,n).length)}return s}(e,t,n,a),s=t.length,i=to(e,t,n,a,o),u=["Tensor"];return r&&(u.push(` dtype: ${n}`),u.push(` rank: ${s}`),u.push(` shape: [${t}]`),u.push(" values:")),u.push(i.map((e=>" "+e)).join("\n")),u.join("\n")}function Ja(e,t,n){let r;return r=Array.isArray(e)?`${parseFloat(e[0].toFixed(Xa))} + ${parseFloat(e[1].toFixed(Xa))}j`:we(e)?`'${e}'`:"bool"===n?eo(e):parseFloat(e.toFixed(Xa)).toString(),ue(r,t)}function eo(e){return 0===e?"false":"true"}function to(e,t,n,r,a,o=!0){const s="complex64"===n?2:1,i=t[0],u=t.length;if(0===u){if("complex64"===n){return[Ja(no(e)[0],0,n)]}return"bool"===n?[eo(e[0])]:[e[0].toString()]}if(1===u){if(i>Qa){const t=Ya*s;let r=Array.from(e.slice(0,t)),o=Array.from(e.slice((i-Ya)*s,i*s));return"complex64"===n&&(r=no(r),o=no(o)),["["+r.map(((e,t)=>Ja(e,a[t],n))).join(", ")+", ..., "+o.map(((e,t)=>Ja(e,a[i-Ya+t],n))).join(", ")+"]"]}return["["+("complex64"===n?no(e):Array.from(e)).map(((e,t)=>Ja(e,a[t],n))).join(", ")+"]"]}const l=t.slice(1),c=r.slice(1),p=r[0]*s,d=[];if(i>Qa){for(let t=0;t<Ya;t++){const r=t*p,o=r+p;d.push(...to(e.slice(r,o),l,n,c,a,!1))}d.push("...");for(let t=i-Ya;t<i;t++){const r=t*p,o=r+p;d.push(...to(e.slice(r,o),l,n,c,a,t===i-1))}}else for(let t=0;t<i;t++){const r=t*p,o=r+p;d.push(...to(e.slice(r,o),l,n,c,a,t===i-1))}const f=2===u?",":"";d[0]="["+(i>0?d[0]+f:"");for(let e=1;e<d.length-1;e++)d[e]=" "+d[e]+f;let h=",\n";for(let e=2;e<u;e++)h+="\n";return d[d.length-1]=" "+d[d.length-1]+"]"+(o?"":h),d}function no(e){const t=[];for(let n=0;n<e.length;n+=2)t.push([e[n],e[n+1]]);return t}
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class ro{constructor(e,t,n){if(this.dtype=t,this.shape=e.slice(),this.size=ee(e),null!=n){const e=n.length;X(e===this.size,(()=>`Length of values '${e}' does not match the size inferred by the shape '${this.size}'.`))}if("complex64"===t)throw new Error("complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).");this.values=n||he(t,this.size),this.strides=Te(e)}set(e,...t){0===t.length&&(t=[0]),X(t.length===this.rank,(()=>`The number of provided coordinates (${t.length}) must match the rank (${this.rank})`));const n=this.locToIndex(t);this.values[n]=e}get(...e){0===e.length&&(e=[0]);let t=0;for(const n of e){if(n<0||n>=this.shape[t]){const t=`Requested out of range element at ${e}. Buffer shape=${this.shape}`;throw new Error(t)}t++}let n=e[e.length-1];for(let t=0;t<e.length-1;++t)n+=this.strides[t]*e[t];return this.values[n]}locToIndex(e){if(0===this.rank)return 0;if(1===this.rank)return e[0];let t=e[e.length-1];for(let n=0;n<e.length-1;++n)t+=this.strides[n]*e[n];return t}indexToLoc(e){if(0===this.rank)return[];if(1===this.rank)return[e];const t=new Array(this.shape.length);for(let n=0;n<t.length-1;++n)t[n]=Math.floor(e/this.strides[n]),e-=t[n]*this.strides[n];return t[t.length-1]=e,t}get rank(){return this.shape.length}toTensor(){return ao().makeTensor(this.values,this.shape,this.dtype)}}let ao=null,oo=null,so=null;class io{constructor(e,t,n,r){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=ee(e),this.strides=Te(e),this.dataId=n,this.id=r,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){const e=await this.data();return oo.buffer(this.shape,this.dtype,e)}bufferSync(){return oo.buffer(this.shape,this.dtype,this.dataSync())}async array(){const e=await this.data();return Ae(this.shape,e,"complex64"===this.dtype)}arraySync(){return Ae(this.shape,this.dataSync(),"complex64"===this.dtype)}async data(){this.throwIfDisposed();const e=ao().read(this.dataId);if("string"===this.dtype){const t=await e;try{return t.map((e=>ja(e)))}catch(e){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return e}dataToGPU(e){return this.throwIfDisposed(),ao().readToGPU(this.dataId,e)}dataSync(){this.throwIfDisposed();const e=ao().readSync(this.dataId);if("string"===this.dtype)try{return e.map((e=>ja(e)))}catch(e){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();const e=await ao().read(this.dataId);return"string"===this.dtype?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(this.kerasMask&&this.kerasMask.dispose(),ao().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return oo.print(this,e)}clone(){return this.throwIfDisposed(),oo.clone(this)}toString(e=!1){return Za(this.dataSync(),this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),oo.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),ao().makeVariable(this,e,t,n)}}function uo(){return We("Tensor",(()=>io))}Object.defineProperty(io,Symbol.hasInstance,{value:e=>!!e&&null!=e.data&&null!=e.dataSync&&null!=e.throwIfDisposed}),uo();class lo extends io{constructor(e,t,n,r){super(e.shape,e.dtype,e.dataId,r),this.trainable=t,this.name=n}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!re(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);ao().disposeTensor(this),this.dataId=e.dataId,ao().incRef(this,null)}dispose(){ao().disposeVariable(this),this.isDisposedInternal=!0}}
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
var co,po,fo,ho,mo;Object.defineProperty(lo,Symbol.hasInstance,{value:e=>e instanceof io&&null!=e.assign&&e.assign instanceof Function}),function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"}(co||(co={})),function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"}(po||(po={})),function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"}(fo||(fo={})),function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"}(ho||(ho={})),function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"}(mo||(mo={}));const go={float32:ho,int32:po,bool:fo,complex64:mo};function yo(e,t){if("string"===e||"string"===t){if("string"===e&&"string"===t)return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return go[e][t]}function bo(e){return yo(e,"int32")}function vo(e){return null!=e&&"object"==typeof e&&"texture"in e&&e.texture instanceof WebGLTexture}function wo(e){return"undefined"!=typeof GPUBuffer&&null!=e&&"object"==typeof e&&"buffer"in e&&e.buffer instanceof GPUBuffer}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function xo(e,t){if(e.dtype===t.dtype)return[e,t];const n=yo(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function ko(e,t){X(e.dtype===t.dtype,(()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`))}function So(e,t){return t.some((t=>t.id===e.id))}function Eo(e){const t=[];return No(e,t,new Set),t}function No(e,t,n){if(null==e)return;if(e instanceof io)return void t.push(e);if(r=e,!Array.isArray(r)&&"object"!=typeof r)return;var r;const a=e;for(const e in a){const r=a[e];n.has(r)||(n.add(r),No(r,t,n))}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function To(e){return null!=e.kernelName}class _o{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(const e in this.registeredVariables)this.registeredVariables[e].dispose()}}class Ao{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new _o}async ready(){if(null!=this.pendingBackendInit)return this.pendingBackendInit.then((()=>{}));if(null!=this.backendInstance)return;const e=this.getSortedBackends();for(let t=0;t<e.length;t++){const n=e[t];if(await this.initializeBackend(n).success)return void await this.setBackend(n)}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(null!=this.pendingBackendInit)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(null==this.backendInstance){const{name:e,asyncInit:t}=this.initializeBackendsAndReturnBest();if(t)throw new Error(`The highest priority backend '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry)){if(!(e in this.registryFactory))return null;{const{asyncInit:t}=this.initializeBackend(e);if(t)return null}}return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,n=1){return e in this.registryFactory?(ca(`${e} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:n},!0)}async setBackend(e){if(null==this.registryFactory[e])throw new Error(`Backend name '${e}' not found in registry`);if(this.backendName=e,null==this.registry[e]){this.backendInstance=null;const{success:t,asyncInit:n}=this.initializeBackend(e);if(!(n?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new qa(this.backendInstance),!0}setupRegisteredKernels(){ga(this.backendName).forEach((e=>{null!=e.setupFunc&&e.setupFunc(this.backendInstance)}))}disposeRegisteredKernels(e){ga(e).forEach((t=>{null!=t.disposeFunc&&t.disposeFunc(this.registry[e])}))}initializeBackend(e){const t=this.registryFactory[e];if(null==t)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{const n=t.factory();if(!n||n instanceof V||"function"!=typeof n.then)return this.registry[e]=n,{success:!0,asyncInit:!1};{const t=++this.pendingBackendInitId,r=n.then((n=>!(t<this.pendingBackendInitId)&&(this.registry[e]=n,this.pendingBackendInit=null,!0))).catch((n=>(t<this.pendingBackendInitId||(this.pendingBackendInit=null,ca(`Initialization of backend ${e} failed`),ca(n.stack||n.message)),!1)));return this.pendingBackendInit=r,{success:r,asyncInit:!0}}}catch(t){return ca(`Initialization of backend ${e} failed`),ca(t.stack||t.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&null!=this.pendingBackendInit&&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(0===Object.keys(this.registryFactory).length)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(){const e=this.getSortedBackends();for(let t=0;t<e.length;t++){const 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){const n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),o=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,o),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n,r=null;if(null==t){if("function"!=typeof e)throw new Error("Please provide a function to tidy()");t=e}else{if("string"!=typeof e&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof t)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");r=e}return this.scopedRun((()=>this.startScope(r)),(()=>this.endScope(n)),(()=>(n=t(),n instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n)))}scopedRun(e,t,n){e();try{const e=n();return t(),e}catch(e){throw t(),e}}nextTensorId(){return Ao.nextTensorId++}nextVariableId(){return Ao.nextVariableId++}clone(e){const t=Mo.runKernel(un,{x:e}),n={x:e};return this.addTapeNode(this.state.activeScope.name,n,[t],(e=>({x:()=>{const t={x:e},n={dtype:"float32"};return Mo.runKernel(mt,t,n)}})),[],{}),t}runKernel(e,t,n){null==this.backendName&&this.backend;if(!(null!=ha(e,this.backendName)))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){const r=this.backend.numDataIds();let a=0;n.forEach((e=>{a+="complex64"===e.dtype?3:1}));const o=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],s=r-t-a-o;if(s>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${s} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[];const r=this.isTapeOn(),a=this.state.numBytes,o=this.state.numTensors;let s,i;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0),null==this.backendName&&this.backend;const u=To(e)?e.kernelName:null!=this.state.activeScope?this.state.activeScope.name:"";if(To(e)){const{kernelName:t,inputs:a,attrs:o}=e;null==this.backendName&&this.backend;const u=ha(t,this.backendName);X(null!=u,(()=>`Cannot find registered kernel '${t}' for backend '${this.backendName}'`)),s=()=>{const e=this.backend.numDataIds();i=u.kernelFunc({inputs:a,attrs:o,backend:this.backend});const s=Array.isArray(i)?i:[i];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(t,e,s);const l=s.map((e=>null!=e.rank?e:this.makeTensorFromTensorInfo(e)));if(r){const e=this.getTensorsForGradient(t,a,l);n=this.saveTensorsForBackwardMode(e)}return l}}else{const{forwardFunc:t}=e,a=e=>{r&&(n=e.map((e=>this.keep(this.clone(e)))))};s=()=>{const e=this.backend.numDataIds();i=this.tidy((()=>t(this.backend,a)));const n=Array.isArray(i)?i:[i];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(u,e,n),n}}const{inputs:l,attrs:c}=e,p=To(e)?null:e.backwardsFunc;let d;return this.scopedRun((()=>this.state.kernelDepth++),(()=>this.state.kernelDepth--),(()=>{this.ENV.getBool("DEBUG")||this.state.profiling?(d=this.profiler.profileKernel(u,l,(()=>s())),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs):t=s()})),r&&this.addTapeNode(u,l,t,p,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-o,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(l).map((e=>null!=l[e]?l[e].shape:null)),outputShapes:t.map((e=>e.shape)),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(i)?t:t[0]}saveTensorsForBackwardMode(e){const t=e.map((e=>this.keep(this.clone(e))));return t}getTensorsForGradient(e,t,n){const r=ma(e);if(null!=r){const e=r.inputsToSave||[],a=r.outputsToSave||[];let o;r.saveAllInputs?(X(Array.isArray(t),(()=>"saveAllInputs is true, expected inputs to be an array.")),o=Object.keys(t).map((e=>t[e]))):o=e.map((e=>t[e]));const s=n.filter(((e,t)=>a[t]));return o.concat(s)}return[]}makeTensor(e,t,n,r){if(null==e)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let a=e;"string"===n&&we(e[0])&&(a=e.map((e=>Ua(e))));const o=r.write(a,t,n),s=new io(t,n,o,this.nextTensorId());if(this.trackTensor(s,r),"string"===n){const e=this.state.tensorInfo.get(o),t=ve(a);this.state.numBytes+=t-e.bytes,e.bytes=t}return s}makeTensorFromDataId(e,t,n,r){const a={dataId:e,shape:t,dtype:n=n||"float32"};return this.makeTensorFromTensorInfo(a,r)}makeTensorFromTensorInfo(e,t){const{dataId:n,shape:r,dtype:a}=e,o=new io(r,a,n,this.nextTensorId());return this.trackTensor(o,t),o}makeVariable(e,t=!0,n,r){n=n||this.nextVariableId().toString(),null!=r&&r!==e.dtype&&(e=e.cast(r));const a=new lo(e,t,n,this.nextTensorId());if(null!=this.state.registeredVariables[a.name])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++,"string"===e.dtype&&this.state.numStringTensors++;let n=0;"complex64"!==e.dtype&&"string"!==e.dtype&&(n=e.size*be(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 lo||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;const t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,"string"===e.dtype&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),"complex64"!==e.dtype&&"string"!==e.dtype){const t=e.size*be(e.dtype);this.state.numBytes-=t}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(const e in this.state.registeredVariables){const t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),null!=this.state.registeredVariables[e.name]&&delete this.state.registeredVariables[e.name]}memory(){const 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,null==e.reasons&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;const 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((e=>e.totalBytesSnapshot))),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(const e of this.state.activeProfile.kernels)e.kernelTimeMs=await e.kernelTimeMs,e.extraInfo=await e.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&0===this.state.kernelDepth}addTapeNode(e,t,n,r,a,o){const s={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},i=ma(e);null!=i&&(r=i.gradFunc),null!=r&&(s.gradient=e=>(e=e.map(((e,t)=>{if(null==e){const e=n[t],r=Oe(e.size,e.dtype);return this.makeTensor(r,e.shape,e.dtype)}return e})),r(e.length>1?e:e[0],a,o))),this.state.activeTape.push(s)}keep(e){return e.kept=!0,e}startTape(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){const t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){const t=Eo(e),n=new Set(t.map((e=>e.id)));for(let e=0;e<this.state.activeScope.track.length;e++){const t=this.state.activeScope.track[e];t.kept||n.has(t.id)||t.dispose()}const r=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach((e=>{e.kept||e.scopeId!==r.id||this.track(e)}))}gradients(e,t,n,r=!1){if(X(t.length>0,(()=>"gradients() received an empty list of xs.")),null!=n&&"float32"!==n.dtype)throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);const a=this.scopedRun((()=>this.startTape()),(()=>this.endTape()),(()=>this.tidy("forward",e)));X(a instanceof io,(()=>"The result y returned by f() must be a tensor."));const o=
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r={},a={};for(let e=0;e<t.length;e++)r[t[e].id]=!0;for(let n=0;n<e.length;n++){const o=e[n],s=o.inputs;for(const e in s){const n=s[e];let i=!1;for(let e=0;e<t.length;e++)if(r[n.id]){o.outputs.forEach((e=>r[e.id]=!0)),i=!0,a[o.id]=!0;break}if(i)break}}const o={};o[n.id]=!0;const s={};for(let t=e.length-1;t>=0;t--){const n=e[t],r=n.inputs;for(let e=0;e<n.outputs.length;e++)if(o[n.outputs[e].id]){for(const e in r)o[r[e].id]=!0,s[n.id]=!0;break}}const i=[];for(let t=0;t<e.length;t++){const n=e[t];if(a[n.id]&&s[n.id]){const e={};for(const t in n.inputs){const a=n.inputs[t];r[a.id]&&(e[t]=a)}const t=Object.assign({},n);t.inputs=e,t.outputs=n.outputs,i.push(t)}}return i}(this.state.activeTape,t,a);if(!r&&0===o.length&&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",(()=>{const e={};e[a.id]=null==n?function(e){const t=Me(ee(e),"float32");return Mo.makeTensor(t,e,"float32")}(a.shape):n,function(e,t,n,r){for(let a=t.length-1;a>=0;a--){const o=t[a],s=[];if(o.outputs.forEach((t=>{const n=e[t.id];null!=n?s.push(n):s.push(null)})),null==o.gradient)throw new Error(`Cannot compute gradient: gradient function not found for ${o.kernelName}.`);const i=o.gradient(s);for(const t in o.inputs){if(!(t in i))throw new Error(`Cannot backprop through input ${t}. Available gradients found: ${Object.keys(i)}.`);const a=n((()=>i[t]()));if("float32"!==a.dtype)throw new Error(`Error in gradient for op ${o.kernelName}. The gradient of input ${t} must have 'float32' dtype, but has '${a.dtype}'`);const s=o.inputs[t];if(!re(a.shape,s.shape))throw new Error(`Error in gradient for op ${o.kernelName}. The gradient of input '${t}' has shape '${a.shape}', which does not match the shape of the input '${s.shape}'`);if(null==e[s.id])e[s.id]=a;else{const t=e[s.id];e[s.id]=r(t,a),t.dispose()}}}}(e,o,(e=>this.tidy(e)),Oo);const r=t.map((t=>e[t.id]));return 0===this.state.gradientDepth&&(this.state.activeTape.forEach((e=>{for(const t of e.saved)t.dispose()})),this.state.activeTape=null),{value:a,grads:r}}))}customGrad(e){return X(Ee(e),(()=>"The f passed in customGrad(f) must be a function.")),(...t)=>{let n;X(t.every((e=>e instanceof io)),(()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors"));const r={};t.forEach(((e,t)=>{r[t]=e}));return this.runKernelFunc({forwardFunc:(r,a)=>(n=e(...t,a),X(n.value instanceof io,(()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor")),X(Ee(n.gradFunc),(()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function.")),n.value),backwardsFunc:(e,r)=>{const a=n.gradFunc(e,r),o=Array.isArray(a)?a:[a];X(o.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(...).")),X(o.every((e=>e instanceof io)),(()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."));const s={};return o.forEach(((e,t)=>{s[t]=()=>e})),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)}readToGPU(e,t){return this.state.tensorInfo.get(e).backend.readToGPU(e,t)}async time(e){const t=Ba(),n=await this.backend.time(e);return n.wallMs=Ba()-t,n}track(e){return null!=this.state.activeScope&&(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 _o;for(const e in this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}}function Io(){const e=je();if(null==e._tfengine){const t=new Le(e);e._tfengine=new Ao(t)}var t;return t=e._tfengine.ENV,Ue=t,ao=()=>e._tfengine,e._tfengine}Ao.nextTensorId=0,Ao.nextVariableId=0;const Mo=Io();function Oo(e,t){const n={a:e,b:t};return Mo.runKernel(Ke,n)}let Do;function Co(e){Do=e}function $o(e){if(void 0!==Do)return Do;if(e||"undefined"!=typeof navigator&&null!=navigator){if(e||(e=navigator),"ReactNative"===e.product)return!0;const t=e.userAgent||e.vendor||("undefined"!=typeof window?window.opera:"");if(!t){const t=e;return t.userAgentData&&t.userAgentData.mobile}return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(t)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(t.substr(0,4))}return!1}function Ro(){return"undefined"!=typeof window&&null!=window.document||"undefined"!=typeof WorkerGlobalScope}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Fo=Be();
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Po(e,t){let n=e;if(Wa(e))return"string"===t?[]:[e.length];if(vo(e)){const t=e.channels||"RGBA";return[e.height,e.width*t.length]}if(wo(e))return[e.buffer.size/(null==t?4:be(t))];if(!Array.isArray(e))return[];const r=[];for(;Array.isArray(n)||Wa(n)&&"string"!==t;)r.push(n.length),n=n[0];return Array.isArray(e)&&Be().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&Lo(e,r,[]),r}function Lo(e,t,n){if(n=n||[],!Array.isArray(e)&&!Wa(e))return void X(0===t.length,(()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`));X(t.length>0,(()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`)),X(e.length===t[0],(()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`));const r=t.slice(1);for(let t=0;t<e.length;++t)Lo(e[t],r,n.concat(t))}function zo(e,t,n,r){if("string_or_numeric"!==e){if(null==e)throw new Error("Expected dtype cannot be null.");if("numeric"!==e&&e!==t||"numeric"===e&&"string"===t)throw new Error(`Argument '${n}' passed to '${r}' must be ${e} tensor, but got ${t} tensor`)}}function Bo(e,t,n,r="numeric"){if(e instanceof uo())return zo(r,e.dtype,t,n),e;let a=Se(e);if("string"!==a&&["bool","int32","float32"].indexOf(r)>=0&&(a=r),zo(r,a,t,n),null==e||!Wa(e)&&!Array.isArray(e)&&"number"!=typeof e&&"boolean"!=typeof e&&"string"!=typeof e){const r=null==e?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${r}'`)}const o=Po(e,a);Wa(e)||Array.isArray(e)||(e=[e]);const s="string"!==a?za(e,a):Ha(e,[],!0);return Mo.makeTensor(s,o,a)}function Vo(e,t,n,r="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map(((e,a)=>Bo(e,`${t}[${a}]`,n,r)))}Fo.registerFlag("DEBUG",(()=>!1),(e=>{e&&console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.")})),Fo.registerFlag("IS_BROWSER",(()=>Ro())),Fo.registerFlag("IS_NODE",(()=>"undefined"!=typeof process&&void 0!==process.versions&&void 0!==process.versions.node)),Fo.registerFlag("IS_CHROME",(()=>"undefined"!=typeof navigator&&null!=navigator&&null!=navigator.userAgent&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor))),Fo.registerFlag("IS_SAFARI",(()=>"undefined"!=typeof navigator&&null!=navigator&&null!=navigator.userAgent&&/Safari/.test(navigator.userAgent)&&/Apple/.test(navigator.vendor))),Fo.registerFlag("PROD",(()=>!1)),Fo.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",(()=>Fo.getBool("DEBUG"))),Fo.registerFlag("DEPRECATION_WARNINGS_ENABLED",(()=>!0)),Fo.registerFlag("IS_TEST",(()=>!1)),Fo.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",(()=>Fo.getBool("DEBUG"))),Fo.registerFlag("WRAP_TO_IMAGEBITMAP",(()=>!1)),Fo.registerFlag("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU",(()=>!1)),Fo.registerFlag("USE_SETTIMEOUTCUSTOM",(()=>!1));
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Uo="__op";function jo(e){const t=Object.keys(e);if(1!==t.length)throw new Error(`Please provide an object with a single key (operation name) mapping to a function. Got an object with ${t.length} keys.`);let n=t[0];const r=e[n];n.endsWith("_")&&(n=n.substring(0,n.length-1)),n+=Uo;const a=(...e)=>{Mo.startScope(n);try{const t=r(...e);return Fe(t)&&console.error("Cannot return a Promise inside of tidy."),Mo.endScope(t),t}catch(e){throw Mo.endScope(null),e}};return Object.defineProperty(a,"name",{value:n,configurable:!0}),a}const Wo=jo({complex_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"real","complex"),r=Bo(t,"imag","complex");Z(n.shape,r.shape,`real and imag shapes, ${n.shape} and ${r.shape}, must match in call to tf.complex().`);const a={real:n,imag:r};return Mo.runKernel(bt,a)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Ho(e,t,n,r){if(null==r)r=Se(e);else if("complex64"===r)throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(wo(e)||vo(e)){if("float32"!==r&&"int32"!==r)throw new Error(`Creating tensor from GPU data only supports 'float32'|'int32' dtype, while the dtype is ${r}.`);return Mo.backend.createTensorFromGPUData(e,t||n,r)}if(!Wa(e)&&!Array.isArray(e)&&"number"!=typeof e&&"boolean"!=typeof e&&"string"!=typeof e)throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(null!=t){Ce(t);const e=ee(t),r=ee(n);X(e===r,(()=>`Based on the provided shape, [${t}], the tensor should have ${e} values but has ${r}`));for(let e=0;e<n.length;++e){const r=n[e],a=e!==n.length-1||r!==ee(t.slice(e));X(n[e]===t[e]||!a,(()=>`Error creating a new Tensor. Inferred shape (${n}) does not match the provided shape (${t}). `))}}return Wa(e)||Array.isArray(e)||(e=[e]),t=t||n,e="string"!==r?za(e,r):Ha(e,[],!0),Mo.makeTensor(e,t,r)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function qo(e,t,n){return Ho(e,t,Po(e,n),n)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Go={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8};class Ko{static join(e){return new Ko(e).slice()}constructor(e){if(this.shards=[],this.previousShardIndex=0,null==e)return;if(e instanceof Array||(e=[e]),0===(e=e.map((e=>Wa(e)?e.buffer:e))).length)return;this.bufferUniformSize=e[0].byteLength;let t=0;for(let n=0;n<e.length;n++){const r=e[n];n!==e.length-1&&r.byteLength!==this.bufferUniformSize&&(this.bufferUniformSize=void 0);const a=t+r.byteLength;this.shards.push({buffer:r,start:t,end:a}),t=a}0===this.shards.length&&(this.byteLength=0),this.byteLength=this.shards[this.shards.length-1].end}slice(e=0,t=this.byteLength){if(0===this.shards.length)return new ArrayBuffer(0);if(e=isNaN(Number(e))?0:e,t=isNaN(Number(t))?0:t,e=Math.max(0,e),(t=Math.min(this.byteLength,t))<=e)return new ArrayBuffer(0);const n=this.findShardForByte(e);if(-1===n)throw new Error(`Could not find start shard for byte ${e}`);const r=new ArrayBuffer(t-e),a=new Uint8Array(r);let o=0;for(let r=n;r<this.shards.length;r++){const n=this.shards[r],s=e+o-n.start,i=o,u=Math.min(t,n.end)-n.start,l=new Uint8Array(n.buffer,s,u-s);if(a.set(l,i),o+=l.length,t<n.end)break}return r}findShardForByte(e){if(0===this.shards.length||e<0||e>=this.byteLength)return-1;if(null!=this.bufferUniformSize)return this.previousShardIndex=Math.floor(e/this.bufferUniformSize),this.previousShardIndex;function t(t){return e<t.start?-1:e>=t.end?1:0}if(0===t(this.shards[this.previousShardIndex]))return this.previousShardIndex;const n=function(e,t){let n=0,r=e.length;for(;n<=r;){const a=Math.floor((r-n)/2)+n,o=t(e[a]);if(0===o)return a;o<0?r=a:n=a+1}return-1}(this.shards,t);return-1===n?-1:(this.previousShardIndex=n,this.previousShardIndex)}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Qo=4;async function Yo(e,t){const n=[],r=[],a=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);for(let o=0;o<a.length;++o){const s=a[o],i=Array.isArray(e)?e[o].tensor:e[s];if("float32"!==i.dtype&&"int32"!==i.dtype&&"bool"!==i.dtype&&"string"!==i.dtype&&"complex64"!==i.dtype)throw new Error(`Unsupported dtype in weight '${s}': ${i.dtype}`);const u={name:s,shape:i.shape,dtype:i.dtype};if("string"===i.dtype){const e=new Promise((async e=>{const t=await i.bytes(),n=t.reduce(((e,t)=>e+t.length),0)+Qo*t.length,r=new Uint8Array(n);let a=0;for(let e=0;e<t.length;e++){const n=t[e],o=new Uint8Array(new Uint32Array([n.length]).buffer);r.set(o,a),a+=Qo,r.set(n,a),a+=n.length}e(r)}));r.push(e)}else r.push(i.data());null!=t&&(u.group=t),n.push(u)}return{data:Zo(await Promise.all(r)),specs:n}}function Xo(e,t){const n=new Ko(e),r={};let a,o=0;for(const e of t){const t=e.name,s=e.dtype,i=e.shape,u=ee(i);let l;if("quantization"in e){const r=e.quantization;if("uint8"===r.dtype||"uint16"===r.dtype){if(!("min"in r)||!("scale"in r))throw new Error(`Weight ${e.name} with quantization ${r.dtype} doesn't have corresponding metadata min and scale.`)}else{if("float16"!==r.dtype)throw new Error(`Weight ${e.name} has unknown quantization dtype ${r.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);if("float32"!==s)throw new Error(`Weight ${e.name} is quantized with ${r.dtype} which only supports weights of type float32 not ${s}.`)}const i=Go[r.dtype],c=n.slice(o,o+u*i),p="uint8"===r.dtype?new Uint8Array(c):new Uint16Array(c);if("float32"===s)if("uint8"===r.dtype||"uint16"===r.dtype){l=new Float32Array(p.length);for(let e=0;e<p.length;e++){const t=p[e];l[e]=t*r.scale+r.min}}else{if("float16"!==r.dtype)throw new Error(`Unsupported quantization type ${r.dtype} for weight type float32.`);void 0===a&&(a=us()),l=a(p)}else{if("int32"!==s)throw new Error(`Unsupported dtype in weight '${t}': ${s}`);if("uint8"!==r.dtype&&"uint16"!==r.dtype)throw new Error(`Unsupported quantization type ${r.dtype} for weight type int32.`);l=new Int32Array(p.length);for(let e=0;e<p.length;e++){const t=p[e];l[e]=Math.round(t*r.scale+r.min)}}o+=u*i}else if("string"===s){const t=ee(e.shape);l=[];for(let e=0;e<t;e++){const e=new Uint32Array(n.slice(o,o+Qo))[0];o+=Qo;const t=new Uint8Array(n.slice(o,o+e));l.push(t),o+=e}}else{const e=Go[s],a=n.slice(o,o+u*e);if("float32"===s)l=new Float32Array(a);else if("int32"===s)l=new Int32Array(a);else if("bool"===s)l=new Uint8Array(a);else{if("complex64"!==s)throw new Error(`Unsupported dtype in weight '${t}': ${s}`);{l=new Float32Array(a);const e=new Float32Array(l.length/2),n=new Float32Array(l.length/2);for(let t=0;t<e.length;t++)e[t]=l[2*t],n[t]=l[2*t+1];const o=qo(e,i,"float32"),s=qo(n,i,"float32");r[t]=Wo(o,s),o.dispose(),s.dispose()}}o+=u*e}"complex64"!==s&&(r[t]=qo(l,i,s))}return r}function Zo(e){if(null===e)throw new Error(`Invalid input value: ${JSON.stringify(e)}`);let t=0;const n=[];e.forEach((e=>{if(t+=e.byteLength,n.push(e.byteLength===e.buffer.byteLength?e:new e.constructor(e)),!(e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array))throw new Error(`Unsupported TypedArray subtype: ${e.constructor.name}`)}));const r=new Uint8Array(t);let a=0;return n.forEach((e=>{r.set(new Uint8Array(e.buffer),a),a+=e.byteLength})),r.buffer}const Jo="undefined"!=typeof Buffer&&("undefined"==typeof Blob||"undefined"==typeof atob||"undefined"==typeof btoa);function es(e){return Jo?Buffer.byteLength(e,"utf8"):new Blob([e]).size}function ts(e){return Ko.join(e)}function ns(e){for(e=e.trim();e.endsWith("/");)e=e.slice(0,e.length-1);const t=e.split("/");return t[t.length-1]}function rs(e,t){const n={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,weightsManifest:t};return null!=e.signature&&(n.signature=e.signature),null!=e.userDefinedMetadata&&(n.userDefinedMetadata=e.userDefinedMetadata),null!=e.modelInitializer&&(n.modelInitializer=e.modelInitializer),null!=e.initializerSignature&&(n.initializerSignature=e.initializerSignature),null!=e.trainingConfig&&(n.trainingConfig=e.trainingConfig),n}function as(e,t,n){const r={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy};if(null!=e.trainingConfig&&(r.trainingConfig=e.trainingConfig),null!=e.weightsManifest){if(!t)throw new Error("modelJSON has weightsManifest but weightSpecs is null");if(!n)throw new Error("modelJSON has weightsManifest but weightData is null");r.weightSpecs=t,r.weightData=n}return null!=e.signature&&(r.signature=e.signature),null!=e.userDefinedMetadata&&(r.userDefinedMetadata=e.userDefinedMetadata),null!=e.modelInitializer&&(r.modelInitializer=e.modelInitializer),null!=e.initializerSignature&&(r.initializerSignature=e.initializerSignature),r}async function os(e,t){let n,r;return null!=e.weightsManifest&&([n,r]=await t(e.weightsManifest)),as(e,n,r)}function ss(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("Expected JSON model topology, received ArrayBuffer.");return{dateSaved:new Date,modelTopologyType:"JSON",modelTopologyBytes:null==e.modelTopology?0:es(JSON.stringify(e.modelTopology)),weightSpecsBytes:null==e.weightSpecs?0:es(JSON.stringify(e.weightSpecs)),weightDataBytes:null==e.weightData?0:new Ko(e.weightData).byteLength}}function is(e){const t=[];for(const n of e)t.push(...n.weights);return t}function us(){const e=function(){const e=e=>{let t=e<<13,n=0;for(;0==(8388608&t);)n-=8388608,t<<=1;return t&=-8388609,n+=947912704,t|n},t=new Uint32Array(2048);t[0]=0;for(let n=1;n<1024;n++)t[n]=e(n);for(let e=1024;e<2048;e++)t[e]=939524096+(e-1024<<13);return t}(),t=function(){const e=new Uint32Array(64);e[0]=0,e[31]=1199570944,e[32]=2147483648,e[63]=3347054592;for(let t=1;t<31;t++)e[t]=t<<23;for(let t=33;t<63;t++)e[t]=2147483648+(t-32<<23);return e}(),n=function(){const e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}();return r=>{const a=new ArrayBuffer(4*r.length),o=new Uint32Array(a);for(let a=0;a<r.length;a++){const s=r[a],i=e[n[s>>10]+(1023&s)]+t[s>>10];o[a]=i}return new Float32Array(a)}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class ls{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return null==ls.instance&&(ls.instance=new ls),ls.instance}static registerSaveRouter(e){ls.getInstance().saveRouters.push(e)}static registerLoadRouter(e){ls.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return ls.getHandlers(e,"save")}static getLoadHandlers(e,t){return ls.getHandlers(e,"load",t)}static getHandlers(e,t,n){const r=[];return("load"===t?ls.getInstance().loadRouters:ls.getInstance().saveRouters).forEach((t=>{const a=t(e,n);null!==a&&r.push(a)})),r}}const cs=e=>ls.registerSaveRouter(e),ps=e=>ls.registerLoadRouter(e),ds=e=>ls.getSaveHandlers(e),fs=(e,t)=>ls.getLoadHandlers(e,t),hs="tensorflowjs",ms="models_store",gs="model_info_store";function ys(){if(!Be().getBool("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");const e="undefined"==typeof window?self:window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(null==t)throw new Error("The current browser does not appear to support IndexedDB.");return t}function bs(e){const t=e.result;t.createObjectStore(ms,{keyPath:"modelPath"}),t.createObjectStore(gs,{keyPath:"modelPath"})}class vs{constructor(e){if(this.indexedDB=ys(),null==e||!e)throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");this.modelPath=e}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");return this.databaseAction(this.modelPath,e)}async load(){return this.databaseAction(this.modelPath)}databaseAction(e,t){return new Promise(((e,n)=>{const r=this.indexedDB.open(hs,1);r.onupgradeneeded=()=>bs(r),r.onsuccess=()=>{const a=r.result;if(null==t){const t=a.transaction(ms,"readonly"),r=t.objectStore(ms).get(this.modelPath);r.onsuccess=()=>{if(null==r.result)return a.close(),n(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));e(r.result.modelArtifacts)},r.onerror=e=>(a.close(),n(r.error)),t.oncomplete=()=>a.close()}else{t.weightData=Ko.join(t.weightData);const r=ss(t),o=a.transaction(gs,"readwrite");let s,i,u=o.objectStore(gs);try{s=u.put({modelPath:this.modelPath,modelArtifactsInfo:r})}catch(e){return n(e)}s.onsuccess=()=>{i=a.transaction(ms,"readwrite");const s=i.objectStore(ms);let l;try{l=s.put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:r})}catch(e){return n(e)}l.onsuccess=()=>e({modelArtifactsInfo:r}),l.onerror=e=>{u=o.objectStore(gs);const t=u.delete(this.modelPath);t.onsuccess=()=>(a.close(),n(l.error)),t.onerror=e=>(a.close(),n(l.error))}},s.onerror=e=>(a.close(),n(s.error)),o.oncomplete=()=>{null==i?a.close():i.oncomplete=()=>a.close()}}},r.onerror=e=>n(r.error)}))}}vs.URL_SCHEME="indexeddb://";const ws=e=>{return Be().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(vs.URL_SCHEME)?(t=e.slice(vs.URL_SCHEME.length),new vs(t)):null;var t};ls.registerSaveRouter(ws),ls.registerLoadRouter(ws);class xs{constructor(){this.indexedDB=ys()}async listModels(){return new Promise(((e,t)=>{const n=this.indexedDB.open(hs,1);n.onupgradeneeded=()=>bs(n),n.onsuccess=()=>{const r=n.result,a=r.transaction(gs,"readonly"),o=a.objectStore(gs).getAll();o.onsuccess=()=>{const t={};for(const e of o.result)t[e.modelPath]=e.modelArtifactsInfo;e(t)},o.onerror=e=>(r.close(),t(o.error)),a.oncomplete=()=>r.close()},n.onerror=e=>t(n.error)}))}async removeModel(e){var t;return e=(t=e).startsWith(vs.URL_SCHEME)?t.slice(vs.URL_SCHEME.length):t,new Promise(((t,n)=>{const r=this.indexedDB.open(hs,1);r.onupgradeneeded=()=>bs(r),r.onsuccess=()=>{const a=r.result,o=a.transaction(gs,"readwrite"),s=o.objectStore(gs),i=s.get(e);let u;i.onsuccess=()=>{if(null==i.result)return a.close(),n(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{const r=s.delete(e),o=()=>{u=a.transaction(ms,"readwrite");const r=u.objectStore(ms).delete(e);r.onsuccess=()=>t(i.result.modelArtifactsInfo),r.onerror=e=>n(i.error)};r.onsuccess=o,r.onerror=e=>(o(),a.close(),n(i.error))}},i.onerror=e=>(a.close(),n(i.error)),o.oncomplete=()=>{null==u?a.close():u.oncomplete=()=>a.close()}},r.onerror=e=>n(r.error)}))}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const ks="/",Ss="tensorflowjs_models",Es="info",Ns="model_topology",Ts="weight_specs",_s="weight_data",As="model_metadata";function Is(e){return{info:[Ss,e,Es].join(ks),topology:[Ss,e,Ns].join(ks),weightSpecs:[Ss,e,Ts].join(ks),weightData:[Ss,e,_s].join(ks),modelMetadata:[Ss,e,As].join(ks)}}function Ms(e){for(const t of Object.values(e))window.localStorage.removeItem(t)}function Os(e){const t=e.split(ks);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(ks)}class Ds{constructor(e){if(!Be().getBool("IS_BROWSER")||"undefined"==typeof window||void 0===window.localStorage)throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,null==e||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=Is(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{const t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),r=ss(e),a=Ko.join(e.weightData);try{this.LS.setItem(this.keys.info,JSON.stringify(r)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,function(e){if(Jo)return Buffer.from(e).toString("base64");const t=new Uint8Array(e);let n="";for(let e=0,r=t.length;e<r;e++)n+=String.fromCharCode(t[e]);return btoa(n)}(a));const o={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,signature:null!=e.signature?e.signature:void 0,userDefinedMetadata:null!=e.userDefinedMetadata?e.userDefinedMetadata:void 0,modelInitializer:null!=e.modelInitializer?e.modelInitializer:void 0,initializerSignature:null!=e.initializerSignature?e.initializerSignature:void 0,trainingConfig:null!=e.trainingConfig?e.trainingConfig:void 0};return this.LS.setItem(this.keys.modelMetadata,JSON.stringify(o)),{modelArtifactsInfo:r}}catch(e){throw Ms(this.keys),new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${r.modelTopologyBytes}, weightSpecsBytes=${r.weightSpecsBytes}, weightDataBytes=${r.weightDataBytes}.`)}}}async load(){const e=JSON.parse(this.LS.getItem(this.keys.info));if(null==e)throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);if("JSON"!==e.modelTopologyType)throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");const t={},n=JSON.parse(this.LS.getItem(this.keys.topology));if(null==n)throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);t.modelTopology=n;const r=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(null==r)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=r;const a=this.LS.getItem(this.keys.modelMetadata);if(null!=a){const e=JSON.parse(a);t.format=e.format,t.generatedBy=e.generatedBy,t.convertedBy=e.convertedBy,null!=e.signature&&(t.signature=e.signature),null!=e.userDefinedMetadata&&(t.userDefinedMetadata=e.userDefinedMetadata),null!=e.modelInitializer&&(t.modelInitializer=e.modelInitializer),null!=e.initializerSignature&&(t.initializerSignature=e.initializerSignature),null!=e.trainingConfig&&(t.trainingConfig=e.trainingConfig)}const o=this.LS.getItem(this.keys.weightData);if(null==o)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=function(e){if(Jo){const t=Buffer.from(e,"base64");return t.buffer.slice(t.byteOffset,t.byteOffset+t.byteLength)}const t=atob(e),n=new Uint8Array(t.length);for(let e=0;e<t.length;++e)n.set([t.charCodeAt(e)],e);return n.buffer}(o),t}}Ds.URL_SCHEME="localstorage://";const Cs=e=>{return Be().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Ds.URL_SCHEME)?(t=e.slice(Ds.URL_SCHEME.length),new Ds(t)):null;var t};ls.registerSaveRouter(Cs),ls.registerLoadRouter(Cs);class $s{constructor(){X(Be().getBool("IS_BROWSER"),(()=>"Current environment is not a web browser")),X("undefined"==typeof window||void 0!==window.localStorage,(()=>"Current browser does not appear to support localStorage")),this.LS=window.localStorage}async listModels(){const e={},t=Ss+ks,n=ks+Es;for(let r=0;r<this.LS.length;++r){const a=this.LS.key(r);if(a.startsWith(t)&&a.endsWith(n)){e[Os(a)]=JSON.parse(this.LS.getItem(a))}}return e}async removeModel(e){var t;const n=Is(e=(t=e).startsWith(Ds.URL_SCHEME)?t.slice(Ds.URL_SCHEME.length):t);if(null==this.LS.getItem(n.info))throw new Error(`Cannot find model at path '${e}'`);const r=JSON.parse(this.LS.getItem(n.info));return Ms(n),r}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Rs="://";class Fs{constructor(){this.managers={}}static getInstance(){return null==Fs.instance&&(Fs.instance=new Fs),Fs.instance}static registerManager(e,t){X(null!=e,(()=>"scheme must not be undefined or null.")),e.endsWith(Rs)&&(e=e.slice(0,e.indexOf(Rs))),X(e.length>0,(()=>"scheme must not be an empty string."));const n=Fs.getInstance();X(null==n.managers[e],(()=>`A model store manager is already registered for scheme '${e}'.`)),n.managers[e]=t}static getManager(e){const t=Fs.getInstance().managers[e];if(null==t)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return Object.keys(Fs.getInstance().managers)}}function Ps(e){if(-1===e.indexOf(Rs))throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${Fs.getSchemes().join(",")}`);return{scheme:e.split(Rs)[0],path:e.split(Rs)[1]}}async function Ls(e,t,n=!1){X(e!==t,(()=>`Old path and new path are the same: '${e}'`));const r=ls.getLoadHandlers(e);X(r.length>0,(()=>`Copying failed because no load handler is found for source URL ${e}.`)),X(r.length<2,(()=>`Copying failed because more than one (${r.length}) load handlers for source URL ${e}.`));const a=r[0],o=ls.getSaveHandlers(t);X(o.length>0,(()=>`Copying failed because no save handler is found for destination URL ${t}.`)),X(o.length<2,(()=>`Copying failed because more than one (${r.length}) save handlers for destination URL ${t}.`));const s=o[0],i=Ps(e).scheme,u=Ps(e).path,l=i===Ps(e).scheme,c=await a.load();n&&l&&await Fs.getManager(i).removeModel(u);const p=await s.save(c);return n&&!l&&await Fs.getManager(i).removeModel(u),p.modelArtifactsInfo}async function zs(){const e=Fs.getSchemes(),t={};for(const n of e){const e=await Fs.getManager(n).listModels();for(const r in e){t[n+Rs+r]=e[r]}}return t}async function Bs(e){const t=Ps(e);return Fs.getManager(t.scheme).removeModel(t.path)}async function Vs(e,t){return Ls(e,t,!1)}async function Us(e,t){return Ls(e,t,!0)}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class js{constructor(){this.messageName="setTimeoutCustom",this.functionRefs=[],this.handledMessageCount=0,this.hasEventListener=!1}fetch(e,t){return fetch(e,t)}now(){return performance.now()}encode(e,t){if("utf-8"!==t&&"utf8"!==t)throw new Error(`Browser's encoder only supports utf-8, but got ${t}`);return null==this.textEncoder&&(this.textEncoder=new TextEncoder),this.textEncoder.encode(e)}decode(e,t){return new TextDecoder(t).decode(e)}setTimeoutCustom(e,t){"undefined"!=typeof window&&Be().getBool("USE_SETTIMEOUTCUSTOM")?(this.functionRefs.push(e),setTimeout((()=>{window.postMessage({name:this.messageName,index:this.functionRefs.length-1},"*")}),t),this.hasEventListener||(this.hasEventListener=!0,window.addEventListener("message",(e=>{if(e.source===window&&e.data.name===this.messageName){e.stopPropagation();(0,this.functionRefs[e.data.index])(),this.handledMessageCount++,this.handledMessageCount===this.functionRefs.length&&(this.functionRefs=[],this.handledMessageCount=0)}}),!0))):setTimeout(e,t)}isTypedArray(e){return Sa(e)}}if(Be().get("IS_BROWSER")){Be().setPlatform("browser",new js);try{Fs.registerManager(Ds.URL_SCHEME,new $s)}catch(e){}try{Fs.registerManager(vs.URL_SCHEME,new xs)}catch(e){}}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Ws=()=>n(5410);let Hs;class qs{constructor(){this.util=n(8628),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return null!=Be().global.fetch?Be().global.fetch(e,t):(null==Hs&&(Hs=Ws()),Hs(e,t))}now(){const e=process.hrtime();return 1e3*e[0]+e[1]/1e6}encode(e,t){if("utf-8"!==t&&"utf8"!==t)throw new Error(`Node built-in encoder only supports utf-8, but got ${t}`);return this.textEncoder.encode(e)}decode(e,t){return 0===e.length?"":new this.util.TextDecoder(t).decode(e)}isTypedArray(e){return this.util.types.isFloat32Array(e)||this.util.types.isInt32Array(e)||this.util.types.isUint8Array(e)||this.util.types.isUint8ClampedArray(e)}}
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Gs(e,t="float32",n){return t=t||"float32",Ce(e),new ro(e,t,n)}Be().get("IS_NODE")&&!Be().get("IS_BROWSER")&&Be().setPlatform("node",new qs);const Ks=jo({cast_:
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","cast");if(!ge(t))throw new Error(`Failed to cast to unknown dtype ${t}`);if("string"===t&&"string"!==n.dtype||"string"!==t&&"string"===n.dtype)throw new Error("Only strings can be casted to strings");const r={x:n},a={dtype:t};return Mo.runKernel(mt,r,a)}});const Qs=jo({clone_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","clone","string_or_numeric")};return Mo.runKernel(un,t)}});
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Ys(e,t=!1){console.log(e.toString(t))}
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
Io();
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Xs(){Be().set("PROD",!0)}function Zs(){Be().set("DEBUG",!0)}function Js(){Be().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function ei(e){Be().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}function ti(){Mo.disposeVariables()}function ni(){return Mo}function ri(){return Mo.memory()}function ai(e){return Mo.profile(e)}function oi(e,t){return Mo.tidy(e,t)}function si(e){Eo(e).forEach((e=>e.dispose()))}function ii(e){return Mo.keep(e)}function ui(e){return Mo.time(e)}function li(e){return Mo.setBackend(e)}function ci(){return Mo.ready()}function pi(){return Mo.backendName}function di(e){Mo.removeBackend(e)}function fi(e){return Mo.findBackend(e)}function hi(e){return Mo.findBackendFactory(e)}function mi(e,t,n=1){return Mo.registerBackend(e,t,n)}function gi(){return Mo.backend}function yi(e,t){Be().setPlatform(e,t)}oo={buffer:Gs,cast:Ks,clone:Qs,print:Ys},so=ei;const bi=jo({add_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","add"),r=Bo(t,"b","add");[n,r]=xo(n,r);const a={a:n,b:r};return Mo.runKernel(Ke,a)}});const vi=jo({floorDiv_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","floorDiv"),r=Bo(t,"b","floorDiv");[n,r]=xo(n,r);const a={a:n,b:r};return Mo.runKernel(tn,a)}});const wi=jo({div_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","div"),r=Bo(t,"b","div");if([n,r]=xo(n,r),"int32"===n.dtype&&"int32"===r.dtype)return vi(n,r);const a={a:n,b:r};return Mo.runKernel(Ut,a,{})}});const xi=jo({mul_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","mul"),r=Bo(t,"b","mul");[n,r]=xo(n,r);const a={a:n,b:r};return Mo.runKernel(Un,a)}});const ki=jo({sqrt_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","sqrt","float32")};return Mo.runKernel(Ir,t)}});const Si=jo({square_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=Bo(e,"x","square");return Mo.runKernel("Square",{x:t},{})}});const Ei=jo({zerosLike_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","zerosLike")};return Mo.runKernel(ra,t)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Ni(e){return X(Ee(e),(()=>"The f passed in grad(f) must be a function")),(t,n)=>{const r=Bo(t,"x","tf.grad","string_or_numeric"),a=null!=n?Bo(n,"dy","tf.grad"):null;return Mo.tidy((()=>{const{value:t,grads:n}=Mo.gradients((()=>e(r)),[r],a);return null!=a&&Z(t.shape,a.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),Oi(n),n[0]}))}}function Ti(e){return X(Ee(e),(()=>"The f passed in grads(f) must be a function")),(t,n)=>{X(Array.isArray(t),(()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s"));const r=Vo(t,"args","tf.grads","string_or_numeric"),a=null!=n?Bo(n,"dy","tf.grads"):null;return Mo.tidy((()=>{const{value:t,grads:n}=Mo.gradients((()=>e(...r)),r,a);return null!=a&&Z(t.shape,a.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Oi(n),n}))}}function _i(e){return X(Ee(e),(()=>"The f passed in valueAndGrad(f) must be a function")),(t,n)=>{X(t instanceof io,(()=>"The x passed in valueAndGrad(f)(x) must be a tensor")),X(null==n||n instanceof io,(()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor"));const{grads:r,value:a}=Mo.gradients((()=>e(t)),[t],n);return Oi(r),{grad:r[0],value:a}}}function Ai(e){return X(Ee(e),(()=>"The f passed in valueAndGrads(f) must be a function")),(t,n)=>{X(Array.isArray(t)&&t.every((e=>e instanceof io)),(()=>"The args passed in valueAndGrads(f)(args) must be array of tensors")),X(null==n||n instanceof io,(()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor"));const r=Mo.gradients((()=>e(...t)),t,n);return null!=n&&Z(r.value.shape,n.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),Oi(r.grads),r}}function Ii(e,t){X(Ee(e),(()=>"The f passed in variableGrads(f) must be a function")),X(null==t||Array.isArray(t)&&t.every((e=>e instanceof lo)),(()=>"The varList passed in variableGrads(f, varList) must be an array of variables"));const n=null!=t;if(!n){t=[];for(const e in Mo.registeredVariables)t.push(Mo.registeredVariables[e])}const r=n?t.filter((e=>!e.trainable)):null,a=t.length;t=t.filter((e=>e.trainable)),X(t.length>0,(()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${a} variables is trainable.`));const{value:o,grads:s}=Mo.gradients(e,t,null,!0);X(s.some((e=>null!=e)),(()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize().")),X(0===o.rank,(()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${o.rank} tensor`));const i={};return t.forEach(((e,t)=>{null!=s[t]&&(i[e.name]=s[t])})),null!=r&&r.forEach((e=>i[e.name]=null)),{value:o,grads:i}}function Mi(e){return Mo.customGrad(e)}function Oi(e){if(e.filter((e=>null==e)).length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that\n the f you passed encloses all operations that lead from x to y.")}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Di(e,t){if((Wa(e)&&"string"!==t||Array.isArray(e))&&"complex64"!==t)throw new Error("Error creating a new Scalar: value must be a primitive (number|boolean|string)");if("string"===t&&Wa(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return Ho(e,[],[],t)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Ci=new Map,$i=new Map;class Ri{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}}class Fi{constructor(){this.classNameMap={}}static getMap(){return null==Fi.instance&&(Fi.instance=new Fi),Fi.instance}static register(e){Fi.getMap().classNameMap[e.className]=[e,e.fromConfig]}}function Pi(e,t,n){X(null!=e.className,(()=>"Class being registered does not have the static className property defined.")),X("string"==typeof e.className,(()=>"className is required to be a string, but got type "+typeof e.className)),X(e.className.length>0,(()=>"Class being registered has an empty-string as its className, which is disallowed.")),void 0===t&&(t="Custom"),void 0===n&&(n=e.className);const r=t+">"+n;return Fi.register(e),Ci.set(r,e),$i.set(e,r),e}function Li(e){return $i.has(e)?$i.get(e):e.className}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class zi extends Ri{minimize(e,t=!1,n){const{value:r,grads:a}=this.computeGradients(e,n);if(null!=n){const e=n.map((e=>({name:e.name,tensor:a[e.name]})));this.applyGradients(e)}else this.applyGradients(a);return si(a),t?r:(r.dispose(),null)}get iterations(){return null==this.iterations_&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return Ii(e,t)}dispose(){null!=this.iterations_&&si(this.iterations_)}async saveIterations(){return null==this.iterations_&&(this.iterations_=0),{name:"iter",tensor:Di(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}}Object.defineProperty(zi,Symbol.hasInstance,{value:e=>null!=e.minimize&&null!=e.computeGradients&&null!=e.applyGradients});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Bi extends zi{static get className(){return"Adadelta"}constructor(e,t,n=null){super(),this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],null==n&&(this.epsilon=Mo.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=Mo.registeredVariables[t];null==this.accumulatedGrads[n]&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:oi((()=>Ei(r).variable(false)))}),null==this.accumulatedUpdates[n]&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:oi((()=>Ei(r).variable(false)))});const a=Array.isArray(e)?e[n].tensor:e[t];if(null==a)return;const o=this.accumulatedGrads[n].variable,s=this.accumulatedUpdates[n].variable;oi((()=>{const e=bi(xi(o,this.rho),xi(Si(a),1-this.rho)),t=xi(wi(ki(bi(s,this.epsilon)),ki(bi(o,this.epsilon))),a),n=bi(xi(s,this.rho),xi(Si(t),1-this.rho));o.assign(e),s.assign(n);const i=bi(xi(t,-this.learningRate),r);r.assign(i)}))})),this.incrementIterations()}dispose(){null!=this.accumulatedUpdates&&(si(this.accumulatedGrads.map((e=>e.variable))),si(this.accumulatedUpdates.map((e=>e.variable))))}async getWeights(){const e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){const t=(e=await this.extractIterations(e)).length/2;this.accumulatedGrads=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(false)}))),this.accumulatedUpdates=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(false)})))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}}
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Vi(e,t,n){Ce(e);const r={shape:e,value:t,dtype:n=n||Se(t)};return Mo.runKernel(Zt,{},r)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Ui extends zi{static get className(){return"Adagrad"}constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=Mo.registeredVariables[t];if(null==this.accumulatedGrads[n]){const e=!1;this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:oi((()=>Vi(r.shape,this.initialAccumulatorValue).variable(e)))}}const a=Array.isArray(e)?e[n].tensor:e[t];if(null==a)return;const o=this.accumulatedGrads[n].variable;oi((()=>{const e=bi(o,Si(a));o.assign(e);const t=bi(xi(wi(a,ki(bi(e,Mo.backend.epsilon()))),-this.learningRate),r);r.assign(t)}))})),this.incrementIterations()}dispose(){null!=this.accumulatedGrads&&si(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);this.accumulatedGrads=e.map((e=>({originalName:e.name,variable:e.tensor.variable(false)})))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}}const ji=jo({pow_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"base","pow"),r=Bo(t,"exp","pow");[n,r]=xo(n,r);const a={a:n,b:r};return Mo.runKernel(Jn,a)}});const Wi=jo({sub_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","sub"),r=Bo(t,"b","sub");[n,r]=xo(n,r);const a={a:n,b:r};return Mo.runKernel(qr,a)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Hi extends zi{static get className(){return"Adam"}constructor(e,t,n,r=null){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],oi((()=>{this.accBeta1=Di(t).variable(),this.accBeta2=Di(n).variable()})),null==r&&(this.epsilon=Mo.backend.epsilon())}applyGradients(e){const t=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);oi((()=>{const n=Wi(1,this.accBeta1),r=Wi(1,this.accBeta2);t.forEach(((t,a)=>{const o=Mo.registeredVariables[t];null==this.accumulatedFirstMoment[a]&&(this.accumulatedFirstMoment[a]={originalName:`${t}/m`,variable:oi((()=>Ei(o).variable(false)))}),null==this.accumulatedSecondMoment[a]&&(this.accumulatedSecondMoment[a]={originalName:`${t}/v`,variable:oi((()=>Ei(o).variable(false)))});const s=Array.isArray(e)?e[a].tensor:e[t];if(null==s)return;const i=this.accumulatedFirstMoment[a].variable,u=this.accumulatedSecondMoment[a].variable,l=bi(xi(i,this.beta1),xi(s,1-this.beta1)),c=bi(xi(u,this.beta2),xi(Si(s),1-this.beta2)),p=wi(l,n),d=wi(c,r);i.assign(l),u.assign(c);const f=bi(xi(wi(p,bi(ki(d),this.epsilon)),-this.learningRate),o);o.assign(f)})),this.accBeta1.assign(xi(this.accBeta1,this.beta1)),this.accBeta2.assign(xi(this.accBeta2,this.beta2))})),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&si(this.accumulatedFirstMoment.map((e=>e.variable))),null!=this.accumulatedSecondMoment&&si(this.accumulatedSecondMoment.map((e=>e.variable)))}async getWeights(){const e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){e=await this.extractIterations(e),oi((()=>{this.accBeta1.assign(ji(this.beta1,this.iterations_+1)),this.accBeta2.assign(ji(this.beta2,this.iterations_+1))}));const t=e.length/2;this.accumulatedFirstMoment=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(false)}))),this.accumulatedSecondMoment=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(false)})))}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)}}const qi=jo({abs_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=Bo(e,"x","abs");if("complex64"===t.dtype){const e={x:t};return Mo.runKernel(vt,e)}{const e={x:t};return Mo.runKernel(He,e)}}});
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Gi(e,t){const n=e.length,r=[];for(let a=0;a<n;a++){const o=n-1-a,s=e[o]||1;(t[t.length-1-a]||1)>1&&1===s&&r.unshift(o)}return r}function Ki(e,t){const n=[];for(let r=0;r<t.length;r++){const a=e[e.length-r-1],o=t.length-r-1,s=t[o];(null==a||1===a&&s>1)&&n.unshift(o)}return n}function Qi(e,t){const n=Math.max(e.length,t.length),r=new Array(n);for(let a=0;a<n;a++){let o=e[e.length-a-1];null==o&&(o=1);let s=t[t.length-a-1];if(null==s&&(s=1),1===o)r[n-a-1]=s;else if(1===s)r[n-a-1]=o;else{if(o!==s){throw Error(`Operands could not be broadcast together with shapes ${e} and ${t}.`)}r[n-a-1]=o}}return r}const Yi=jo({maximum_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","maximum"),r=Bo(t,"b","maximum");[n,r]=xo(n,r),"bool"===n.dtype&&(n=Ks(n,"int32"),r=Ks(r,"int32")),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(Mn,a)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Xi extends zi{static get className(){return"Adamax"}constructor(e,t,n,r=null,a=0){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.decay=a,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],oi((()=>{this.iteration=Di(0).variable(),this.accBeta1=Di(t).variable()})),null==r&&(this.epsilon=Mo.backend.epsilon())}applyGradients(e){const t=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);oi((()=>{const n=Wi(1,this.accBeta1),r=wi(-this.learningRate,bi(xi(this.iteration,this.decay),1));t.forEach(((t,a)=>{const o=Mo.registeredVariables[t];null==this.accumulatedFirstMoment[a]&&(this.accumulatedFirstMoment[a]={originalName:`${t}/m`,variable:Ei(o).variable(false)}),null==this.accumulatedWeightedInfNorm[a]&&(this.accumulatedWeightedInfNorm[a]={originalName:`${t}/v`,variable:Ei(o).variable(false)});const s=Array.isArray(e)?e[a].tensor:e[t];if(null==s)return;const i=this.accumulatedFirstMoment[a].variable,u=this.accumulatedWeightedInfNorm[a].variable,l=bi(xi(i,this.beta1),xi(s,1-this.beta1)),c=xi(u,this.beta2),p=qi(s),d=Yi(c,p);i.assign(l),u.assign(d);const f=bi(xi(wi(r,n),wi(l,bi(d,this.epsilon))),o);o.assign(f)})),this.iteration.assign(bi(this.iteration,1)),this.accBeta1.assign(xi(this.accBeta1,this.beta1))})),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&si(this.accumulatedFirstMoment.map((e=>e.variable))),null!=this.accumulatedWeightedInfNorm&&si(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)}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Zi extends zi{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=Array.isArray(e)?e[n].tensor:e[t];if(null==r)return;const a=Mo.registeredVariables[t];oi((()=>{const e=bi(xi(this.c,r),a);a.assign(e)}))})),this.incrementIterations()}setLearningRate(e){this.learningRate=e,null!=this.c&&this.c.dispose(),this.c=ii(Di(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(0!==(e=await this.extractIterations(e)).length)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Ji extends Zi{static get className(){return"Momentum"}constructor(e,t,n=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=Di(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=Mo.registeredVariables[t];if(null==this.accumulations[n]){const e=!1;this.accumulations[n]={originalName:`${t}/momentum`,variable:oi((()=>Ei(r).variable(e)))}}const a=this.accumulations[n].variable,o=Array.isArray(e)?e[n].tensor:e[t];null!=o&&oi((()=>{let e;const t=bi(xi(this.m,a),o);e=this.useNesterov?bi(xi(this.c,bi(o,xi(t,this.m))),r):bi(xi(this.c,t),r),a.assign(t),r.assign(e)}))})),this.incrementIterations()}dispose(){this.m.dispose(),null!=this.accumulations&&si(this.accumulations.map((e=>e.variable)))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){e=await this.extractIterations(e);this.accumulations=e.map((e=>({originalName:e.name,variable:e.tensor.variable(false)})))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class eu extends zi{static get className(){return"RMSProp"}constructor(e,t=.9,n=0,r=null,a=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=r,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=a,null==r&&(this.epsilon=Mo.backend.epsilon()),null==e)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=Mo.registeredVariables[t],a=!1;null==this.accumulatedMeanSquares[n]&&(this.accumulatedMeanSquares[n]={originalName:`${t}/rms`,variable:oi((()=>Ei(r).variable(a)))}),null==this.accumulatedMoments[n]&&(this.accumulatedMoments[n]={originalName:`${t}/momentum`,variable:oi((()=>Ei(r).variable(a)))}),null==this.accumulatedMeanGrads[n]&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${t}/mg`,variable:oi((()=>Ei(r).variable(a)))});const o=Array.isArray(e)?e[n].tensor:e[t];if(null==o)return;const s=this.accumulatedMeanSquares[n].variable,i=this.accumulatedMoments[n].variable;oi((()=>{const e=bi(xi(s,this.decay),xi(Si(o),1-this.decay));if(this.centered){const t=this.accumulatedMeanGrads[n].variable,a=bi(xi(t,this.decay),xi(o,1-this.decay)),u=wi(xi(o,this.learningRate),ki(Wi(e,bi(Si(a),this.epsilon)))),l=bi(xi(i,this.momentum),u);s.assign(e),t.assign(a),i.assign(l);const c=Wi(r,l);r.assign(c)}else{const e=bi(xi(s,this.decay),xi(Si(o),1-this.decay)),t=bi(xi(i,this.momentum),wi(xi(o,this.learningRate),ki(bi(e,this.epsilon))));s.assign(e),i.assign(t);const n=Wi(r,t);r.assign(n)}}))})),this.incrementIterations()}dispose(){null!=this.accumulatedMeanSquares&&si(this.accumulatedMeanSquares.map((e=>e.variable))),null!=this.accumulatedMeanGrads&&this.centered&&si(this.accumulatedMeanGrads.map((e=>e.variable))),null!=this.accumulatedMoments&&si(this.accumulatedMoments.map((e=>e.variable)))}async getWeights(){const e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){e=await this.extractIterations(e);const t=this.centered?e.length/3:e.length/2,n=!1;this.accumulatedMeanSquares=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)}))),this.accumulatedMoments=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)}))),this.centered&&(this.accumulatedMeanGrads=e.slice(2*t,3*t).map((e=>({originalName:e.name,variable:e.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)}}
/**
* @license
* Copyright 2022 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const tu=[Bi,Ui,Hi,Xi,Ji,eu,Zi];function nu(e){return new Promise((e=>setTimeout(e))).then(e)}class ru{constructor(e){if(!Be().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(ru.URL_SCHEME)&&(e=e.slice(ru.URL_SCHEME.length)),null!=e&&0!==e.length||(e="model"),this.modelJsonFileName=e+".json",this.weightDataFileName=e+".weights.bin"}async save(e){if("undefined"==typeof document)throw new Error("Browser downloads are not supported in this environment since `document` is not present");const t=Ko.join(e.weightData),n=window.URL.createObjectURL(new Blob([t],{type:"application/octet-stream"}));if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");{const t=rs(e,[{paths:["./"+this.weightDataFileName],weights:e.weightSpecs}]),r=window.URL.createObjectURL(new Blob([JSON.stringify(t)],{type:"application/json"})),a=null==this.modelJsonAnchor?document.createElement("a"):this.modelJsonAnchor;if(a.download=this.modelJsonFileName,a.href=r,await nu((()=>a.dispatchEvent(new MouseEvent("click")))),null!=e.weightData){const e=null==this.weightDataAnchor?document.createElement("a"):this.weightDataAnchor;e.download=this.weightDataFileName,e.href=n,await nu((()=>e.dispatchEvent(new MouseEvent("click"))))}return{modelArtifactsInfo:ss(e)}}}}ru.URL_SCHEME="downloads://";class au{constructor(e){if(null==e||e.length<1)throw new Error(`When calling browserFiles, at least 1 file is required, but received ${e}`);this.jsonFile=e[0],this.weightsFiles=e.slice(1)}async load(){return new Promise(((e,t)=>{const n=new FileReader;n.onload=n=>{const r=JSON.parse(n.target.result),a=r.modelTopology;if(null==a)return void t(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));if(null==r.weightsManifest)return void t(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));if(0===this.weightsFiles.length)return void e({modelTopology:a});const o=os(r,(e=>this.loadWeights(e)));e(o)},n.onerror=e=>t(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),n.readAsText(this.jsonFile)}))}loadWeights(e){const t=[],n=[];for(const r of e)t.push(...r.weights),n.push(...r.paths);const r=this.checkManifestAndWeightFiles(e),a=n.map((e=>this.loadWeightsFile(e,r[e])));return Promise.all(a).then((e=>[t,e]))}loadWeightsFile(e,t){return new Promise(((n,r)=>{const a=new FileReader;a.onload=e=>{const t=e.target.result;n(t)},a.onerror=t=>r(`Failed to weights data from file of path '${e}'.`),a.readAsArrayBuffer(t)}))}checkManifestAndWeightFiles(e){const t=[],n=this.weightsFiles.map((e=>ns(e.name))),r={};for(const a of e)a.paths.forEach((e=>{const a=ns(e);if(-1!==t.indexOf(a))throw new Error(`Duplicate file basename found in weights manifest: '${a}'`);if(t.push(a),-1===n.indexOf(a))throw new Error(`Weight file with basename '${a}' is not provided.`);r[e]=this.weightsFiles[n.indexOf(a)]}));if(t.length!==this.weightsFiles.length)throw new Error(`Mismatch in the number of files in weights manifest (${t.length}) and the number of weight files provided (${this.weightsFiles.length}).`);return r}}function ou(e){return new au(e)}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function su(e,t,n,r){!function(e){X(null!=e&&Array.isArray(e)&&e.length>0,(()=>"promises must be a none empty array"))}(e),function(e,t){X(e>=0&&e<=1,(()=>`Progress fraction must be in range [0, 1], but got startFraction ${e}`)),X(t>=0&&t<=1,(()=>`Progress fraction must be in range [0, 1], but got endFraction ${t}`)),X(t>=e,(()=>`startFraction must be no more than endFraction, but got startFraction ${e} and endFraction ${t}`))}(n=null==n?0:n,r=null==r?1:r);let a=0;return Promise.all(e.map((o=>(o.then((o=>{const s=n+ ++a/e.length*(r-n);return t(s),o})),o))))}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function iu(e,t){null==t&&(t={});const n=null==t.fetchFunc?Be().platform.fetch:t.fetchFunc,r=e.map((e=>n(e,t.requestInit,{isBinary:!0}))),a=(null==t.onProgress?await Promise.all(r):await su(r,t.onProgress,0,.5)).map((e=>e.arrayBuffer()));return null==t.onProgress?await Promise.all(a):await su(a,t.onProgress,.5,1)}async function uu(e,t="",n,r){return lu((e=>iu(e,{requestInit:r})))(e,t,n)}function lu(e){return async(t,n="",r)=>{const a=t.map((()=>!1)),o={},s=null!=r?r.map((()=>!1)):[],i=[];if(t.forEach(((e,t)=>{let n=0;e.weights.forEach((e=>{const u="quantization"in e?e.quantization.dtype:e.dtype,l=Go[u]*ee(e.shape),c=()=>{a[t]=!0,null==o[t]&&(o[t]=[]),o[t].push({manifestEntry:e,groupOffset:n,sizeBytes:l})};null!=r?r.forEach(((t,n)=>{t===e.name&&(c(),s[n]=!0)})):c(),i.push(e.name),n+=l}))})),!s.every((e=>e))){const e=r.filter(((e,t)=>!s[t]));throw new Error(`Could not find weights in manifest with names: ${e.join(", ")}. \nManifest JSON has weights with names: ${i.join(", ")}.`)}const u=a.reduce(((e,t,n)=>(t&&e.push(n),e)),[]),l=[];u.forEach((e=>{t[e].paths.forEach((e=>{const t=n+(n.endsWith("/")?"":"/")+e;l.push(t)}))}));const c=await e(l),p={};let d=0;return u.forEach((e=>{const n=t[e].paths.length,r=new Ko(c.slice(d,d+n));o[e].forEach((e=>{const t=Xo(r.slice(e.groupOffset,e.groupOffset+e.sizeBytes),[e.manifestEntry]);for(const e in t)p[e]=t[e]})),d+=n})),p}}ls.registerSaveRouter((e=>Be().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(ru.URL_SCHEME)?function(e="model"){return new ru(e)}(e.slice(ru.URL_SCHEME.length)):null));class cu{constructor(e,t){if(this.DEFAULT_METHOD="POST",null==t&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.onProgress=t.onProgress,this.weightUrlConverter=t.weightUrlConverter,null!=t.fetchFunc?(X("function"==typeof t.fetchFunc,(()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)")),this.fetch=t.fetchFunc):this.fetch=Be().platform.fetch,X(null!=e&&e.length>0,(()=>"URL path for http must not be null, undefined or empty.")),Array.isArray(e)&&X(2===e.length,(()=>`URL paths for http must have a length of 2, (actual length is ${e.length}).`)),this.path=e,null!=t.requestInit&&null!=t.requestInit.body)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{}}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");const t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;const n=rs(e,[{paths:["./model.weights.bin"],weights:e.weightSpecs}]);if(t.body.append("model.json",new Blob([JSON.stringify(n)],{type:"application/json"}),"model.json"),null!=e.weightData){const n=Ko.join(e.weightData);t.body.append("model.weights.bin",new Blob([n],{type:"application/octet-stream"}),"model.weights.bin")}const r=await this.fetch(this.path,t);if(r.ok)return{modelArtifactsInfo:ss(e),responses:[r]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${r.status}.`)}async load(){const e=await this.fetch(this.path,this.requestInit);if(!e.ok)throw new Error(`Request to ${this.path} failed with status code ${e.status}. Please verify this URL points to the model JSON of the model to load.`);let t;try{t=await e.json()}catch(e){let t=`Failed to parse model JSON of response from ${this.path}.`;throw this.path.endsWith(".pb")?t+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":t+=" Please make sure the server is serving valid JSON for this request.",new Error(t)}const n=t.modelTopology,r=t.weightsManifest;if(null==n&&null==r)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);return os(t,(e=>this.loadWeights(e)))}async loadWeights(e){const t=Array.isArray(this.path)?this.path[1]:this.path,[n,r]=function(e){const t=e.lastIndexOf("/"),n=e.lastIndexOf("?"),r=e.substring(0,t),a=n>t?e.substring(n):"";return[r+"/",a]}(t),a=this.weightPathPrefix||n,o=is(e),s=[],i=[];for(const t of e)for(const e of t.paths)null!=this.weightUrlConverter?i.push(this.weightUrlConverter(e)):s.push(a+e+r);this.weightUrlConverter&&s.push(...await Promise.all(i));return[o,await iu(s,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress})]}}function pu(e){return null!=e.match(cu.URL_SCHEME_REGEX)}cu.URL_SCHEME_REGEX=/^https?:\/\//;const du=(e,t)=>{if("undefined"==typeof fetch&&(null==t||null==t.fetchFunc))return null;{let n=!0;if(n=Array.isArray(e)?e.every((e=>pu(e))):pu(e),n)return fu(e,t)}return null};function fu(e,t){return new cu(e,t)}function hu(e,t){return fu(e,t)}ls.registerSaveRouter(du),ls.registerLoadRouter(du);
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class mu{constructor(e){this.modelArtifacts=e}load(){return this.modelArtifacts}}class gu{constructor(e){this.saveHandler=e}save(e){return this.saveHandler(e)}}class yu{constructor(e){e.load&&(this.load=()=>Promise.resolve(e.load())),e.save&&(this.save=t=>Promise.resolve(e.save(t)))}}function bu(e,t,n,r){return new yu(vu(...arguments))}function vu(e,t,n,r){if(1===arguments.length){return null!=e.modelTopology||null!=e.weightSpecs?new mu(e):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new mu({modelTopology:e}))}return console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new mu({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:r})}function wu(e){return new gu(e)}function xu(e){return new gu(e)}const ku=jo({matMul_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=!1,r=!1){let a=Bo(e,"a","matMul"),o=Bo(t,"b","matMul");[a,o]=xo(a,o);const s={a,b:o},i={transposeA:n,transposeB:r};return Mo.runKernel(lt,s,i)}});const Su=jo({oneHot_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=1,r=0,a="int32"){if(t<2)throw new Error(`Error in oneHot: depth must be >=2, but it is ${t}`);const o={indices:Bo(e,"indices","oneHot","int32")},s={dtype:a,depth:t,onValue:n,offValue:r};return Mo.runKernel(Qn,o,s)}});const Eu=jo({imag_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={input:Bo(e,"input","imag")};return Mo.runKernel(cn,t)}});const Nu=jo({neg_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","neg")};return Mo.runKernel(jn,t)}});const Tu=jo({real_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={input:Bo(e,"input","real")};return Mo.runKernel(sr,t)}});const _u=jo({transpose_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","transpose");if(null==t&&(t=r.shape.map(((e,t)=>t)).reverse()),X(r.rank===t.length,(()=>`Error in transpose: rank of input ${r.rank} must match length of perm ${t}.`)),t.forEach((e=>{X(e>=0&&e<r.rank,(()=>"All entries in 'perm' must be between 0 and "+(r.rank-1)+` but got ${t}`))})),r.rank<=1)return r.clone();const a={x:r},o={perm:t};return"complex64"===r.dtype?oi((()=>{let e=Tu(r),t=Eu(r);return e=Mo.runKernel(Zr,{x:e},o),t=Mo.runKernel(Zr,{x:t},o),n&&(t=Nu(t)),Wo(e,t)})):Mo.runKernel(Zr,a,o)}});const Au=jo({confusionMatrix_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"labels","confusionMatrix"),a=Bo(t,"predictions","confusionMatrix");X(null==n||n>0&&Number.isInteger(n),(()=>`If provided, numClasses must be a positive integer, but got ${n}`)),X(1===r.rank,(()=>`Expected the rank of labels to be 1, but got ${r.rank}`)),X(1===a.rank,(()=>`Expected the rank of predictions to be 1, but got ${a.rank}`)),X(r.shape[0]===a.shape[0],(()=>`Mismatch in the number of examples: ${r.shape[0]} vs. ${a.shape[0]}. Labels and predictions should have the same number of elements.`)),X(n>0&&Number.isInteger(n),(()=>`numClasses is required to be a positive integer, but got ${n}`));const o=Su(Ks(r,"int32"),n),s=Su(Ks(a,"int32"),n),i=_u(o),u=ku(i,s);return Ks(u,"int32")}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Iu(e,t,n){if(J(e),null!=t&&3!==t.length)throw new Error("tensor3d() requires shape to have three numbers");const r=Po(e,n);if(3!==r.length&&1!==r.length)throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");if(1===r.length&&null==t)throw new Error("tensor3d() requires shape to be provided when `values` are a flat array");return Ho(e,t,r,n)}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let Mu,Ou=!1;function Du(e,t=3){if(t>4)throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");if(null==e)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let n=!1,r=!1,a=!1,o=!1,s=!1,i=!1;if(e.data instanceof Uint8Array)n=!0;else if("undefined"!=typeof ImageData&&e instanceof ImageData)r=!0;else if("undefined"!=typeof HTMLVideoElement&&e instanceof HTMLVideoElement)a=!0;else if("undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement)o=!0;else if(null!=e.getContext)s=!0;else{if(!("undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap))throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${e.constructor.name}`);i=!0}if(null!=ha(oa,Mo.backendName)){const n={pixels:e},r={numChannels:t};return Mo.runKernel(oa,n,r)}const[u,l]=a?[e.videoWidth,e.videoHeight]:[e.width,e.height];let c,p;if(s)c=e.getContext("2d").getImageData(0,0,u,l).data;else if(r||n)c=e.data;else if(o||a||i){if(null==Mu)if("undefined"==typeof document){if("undefined"==typeof OffscreenCanvas||"undefined"==typeof OffscreenCanvasRenderingContext2D)throw new Error("Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.");Mu=new OffscreenCanvas(1,1).getContext("2d")}else Mu=document.createElement("canvas").getContext("2d",{willReadFrequently:!0});Mu.canvas.width=u,Mu.canvas.height=l,Mu.drawImage(e,0,0,u,l),c=Mu.getImageData(0,0,u,l).data}if(4===t)p=new Int32Array(c);else{const e=u*l;p=new Int32Array(e*t);for(let n=0;n<e;n++)for(let e=0;e<t;++e)p[n*t+e]=c[4*n+e]}return Iu(p,[l,u,t],"int32")}function Cu(e){return"undefined"!=typeof window&&"undefined"!=typeof ImageBitmap&&window.hasOwnProperty("createImageBitmap")&&!(e instanceof ImageBitmap)&&function(e){return null!=e&&0!==e.width&&0!==e.height}(e)&&!function(e){return null!=e&&e.data instanceof Uint8Array}(e)}async function $u(e,t=3){let n=null;if(Be().getBool("WRAP_TO_IMAGEBITMAP")&&Cu(e)){let t;try{t=await createImageBitmap(e,{premultiplyAlpha:"none"})}catch(e){t=null}n=null!=t&&t.width===e.width&&t.height===e.height?t:e}else n=e;return Du(n,t)}function Ru(e){if(2!==e.rank&&3!==e.rank)throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${e.rank}.`);const t=2===e.rank?1:e.shape[2];if(t>4||2===t)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${t}`);if("float32"!==e.dtype&&"int32"!==e.dtype)throw new Error(`Unsupported type for toPixels: ${e.dtype}. Please use float32 or int32 tensors.`)}async function Fu(e,t){let n=Bo(e,"img","toPixels");if(!(e instanceof io)){const e=n;n=Ks(e,"int32"),e.dispose()}Ru(n);const[r,a]=n.shape.slice(0,2),o=2===n.rank?1:n.shape[2],s=await n.data(),i="float32"===n.dtype?255:1,u=new Uint8ClampedArray(a*r*4);for(let e=0;e<r*a;++e){const t=[0,0,0,255];for(let r=0;r<o;r++){const a=s[e*o+r];if("float32"===n.dtype){if(a<0||a>1)throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${a}.`)}else if("int32"===n.dtype&&(a<0||a>255))throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${a}.`);1===o?(t[0]=a*i,t[1]=a*i,t[2]=a*i):t[r]=a*i}const r=4*e;u[r+0]=Math.round(t[0]),u[r+1]=Math.round(t[1]),u[r+2]=Math.round(t[2]),u[r+3]=Math.round(t[3])}if(null!=t){if(!Ou){null!=ha(Vt,Mo.backendName)&&(console.warn("tf.browser.toPixels is not efficient to draw tensor on canvas. Please try tf.browser.draw instead."),Ou=!0)}t.width=a,t.height=r;const e=t.getContext("2d"),n=new ImageData(u,a,r);e.putImageData(n,0,0)}return n!==e&&n.dispose(),u}function Pu(e,t,n){let r=Bo(e,"img","draw");if(!(e instanceof io)){const e=r;r=Ks(e,"int32"),e.dispose()}Ru(r),function(e){const t=(null==e?void 0:e.alpha)||1;if(t>1||t<0)throw new Error(`Alpha value ${t} is suppoed to be in range [0 - 1].`)}(null==n?void 0:n.imageOptions);const a={image:r},o={canvas:t,options:n};Mo.runKernel(Vt,a,o)}const Lu=jo({fromPixels_:Du});function zu(e,t){const n=e.shape.length,r=t.shape.length;if(n<1)throw new Error(`tf.gatherND() expects the input to be rank 1 or higher, but the rank was ${n}.`);if(r<1)throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${r}.`);if("int32"!==t.dtype)throw new Error(`tf.gatherND() expects the indices to be int32 type, but the dtype was ${t.dtype}.`);if(t.shape[r-1]>n)throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${t.shape[r-1]} vs. ${n}`);if(0===ee(e.shape))throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);const a=t.shape,o=a[a.length-1];let s=1;for(let e=0;e<a.length-1;++e)s*=a[e];const i=e.shape,u=a.slice();u.pop();let l=1;for(let e=o;e<n;++e)l*=i[e],u.push(i[e]);const c=[...Te(e.shape).map((e=>e/l)),1].slice(0,o);return[u,s,l,c]}function Bu(e,t,n){const r=t.rank>1?t.shape[t.rank-1]:1,a=t.rank>1?t.rank-1:1,o=`Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${n.shape}, indices.shape: ${t.shape}, shape: ${e}, sliceDim: ${r}, and batchDim: ${a}.`;if(n.rank<a)throw new Error(o+` update.rank < ${a}. `);if(e.length<r+(n.rank-a))throw new Error(o+` Output shape length < ${r+(n.rank-a)}`);if(n.rank!==a+e.length-r)throw new Error(o+" update.rank != "+(a+e.length-r));for(let e=0;e<a;++e)if(n.shape[e]!==t.shape[e])throw new Error(o+` updates.shape[${e}] (${n.shape[e]}) != indices.shape[${e}] (${t.shape[e]}).`);for(let t=0;t<n.rank-a;++t)if(n.shape[t+a]!==e[t+r])throw new Error(o+` updates.shape[${t+a}] (${n.shape[t+a]}) != shape[${t+a}] (${e[t+a]})`)}function Vu(e,t,n){if(t.rank<1)throw new Error(`tf.scatterND() expects the indices to be rank 1 or higher, but the rank was ${t.rank}.`);if(e.rank<1)throw new Error(`tf.scatterND() expects the updates to be rank 1 or higher, but the rank was ${e.rank}.`);if("int32"!==t.dtype)throw new Error(`The dtype of 'indices' should be int32, but got dtype: ${t.dtype}`);if(n.length<1)throw new Error(`Output rank must be greater or equal to 1, but got shape: ${n}`);if(0===n.length){if(0===t.size)throw new Error(`Indices specified for empty output. indices shape: ${t.shape}`);if(0===e.size)throw new Error(`Updates specified for empty output. updates shape: ${e.shape}`)}Bu(n,t,e)}function Uu(e,t,n){const r=t.shape.length,a=r>1?t.shape[r-1]:1,o=n.length;let s=1;for(let e=a;e<o;++e)s*=n[e];const i=a<1?1:a;return{sliceRank:a,numUpdates:ee(t.shape)/i,sliceSize:s,strides:[...Te(n.slice(0,a)),1],outputSize:ee(n)}}
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const ju=-2,Wu=-1;function Hu(e,t,n){const r=e.shape.length;X(r===t.length,(()=>`Error in slice${r}D: Length of begin ${t} must match the rank of the array (${r}).`)),X(r===n.length,(()=>`Error in slice${r}D: Length of size ${n} must match the rank of the array (${r}).`));for(let a=0;a<r;++a)X(t[a]+n[a]<=e.shape[a],(()=>`Error in slice${r}D: begin[${a}] + size[${a}] (${t[a]+n[a]}) would overflow input.shape[${a}] (${e.shape[a]})`))}function qu(e){const t=[];let n=0;for(;e>0;)1&e&&t.push(n),e/=2,n++;return t}function Gu(e,t,n){const r=[];for(let a=0;a<e.length;a++)r[a]=Math.ceil((t[a]-e[a])/n[a]);return r}function Ku(e,t,n,r){const a=[...e];for(let e=a.length;e<r.length;e++)a.push(1);for(let e=0;e<n;e++)0===e?a[t]=1:(a.splice(t,0,1),a.pop());return a}function Qu(e,t,n){return n<=e?n:n-(t-1)}function Yu(e,t){const n=[];for(let r=0;r<e;r++)n.push(t+r);return n}function Xu(e,t,n,r,a,o,s,i,u){const l=e.length;let c=new Array(l),p=new Array(l),d=new Array(l);if(t.length&&n>0){const u=t[0],l=n+1;c=Zu(s,u,l,r,e),p=Ju(i,u,l,a,e),d=Ku(o,u,l,e)}else for(let t=0;t<l;t++)c[t]=tl(s,r,o,e,t,u),p[t]=nl(i,a,o,e,t,u),d[t]=el(o,t,u);return{begin:c,end:p,strides:d}}function Zu(e,t,n,r,a){const o=[...a],s=Yu(n,t);for(let a=0;a<o.length;a++)if(s.indexOf(a)>-1)o[a]=0;else{const s=Qu(t,n,a);let i=r[s];e&1<<s&&(i=0),o[a]=i}return o}function Ju(e,t,n,r,a){const o=[...a],s=Yu(n,t);for(let a=0;a<o.length;a++)if(s.indexOf(a)>-1)o[a]=Number.MAX_SAFE_INTEGER;else{const s=Qu(t,n,a);let i=r[s];e&1<<s&&(i=Number.MAX_SAFE_INTEGER),o[a]=i}for(let e=0;e<o.length;e++){const t=a[e];o[e]<0&&(o[e]+=t),o[e]=H(0,o[e],a[e])}return o}function el(e,t,n){let r=e[t];return(n&1<<t||null==r)&&(r=1),r}function tl(e,t,n,r,a,o){let s=t[a];const i=n[a]||1;(e&1<<a||o&1<<a||null==s)&&(s=i>0?Number.MIN_SAFE_INTEGER:Number.MAX_SAFE_INTEGER);const u=r[a];return s<0&&(s+=u),s=H(0,s,u-1),s}function nl(e,t,n,r,a,o){let s=t[a];const i=n[a]||1;(e&1<<a||o&1<<a||null==s)&&(s=i>0?Number.MAX_SAFE_INTEGER:Number.MIN_SAFE_INTEGER);const u=r[a];return s<0&&(s+=u),s=i>0?H(0,s,u):H(-1,s,u-1),s}function rl(e,t,n){let r=n.length;for(let e=0;e<n.length;e++)if(n[e]>1){r=e;break}for(let a=r+1;a<n.length;a++)if(t[a]>0||n[a]!==e[a])return!1;return!0}function al(e,t){let n=e.length>0?e[e.length-1]:1;for(let r=0;r<e.length-1;r++)n+=e[r]*t[r];return n}function ol(e,t,n){let r;const a=e.shape.length;let o;return r="number"==typeof t?[t,...new Array(a-1).fill(0)]:t.length<a?t.concat(new Array(a-t.length).fill(0)):t.slice(),r.forEach((e=>{X(-1!==e,(()=>"slice() does not support negative begin indexing."))})),o=null==n?new Array(a).fill(-1):"number"==typeof n?[n,...new Array(a-1).fill(-1)]:n.length<a?n.concat(new Array(a-n.length).fill(-1)):n,o=o.map(((t,n)=>t>=0?t:(X(-1===t,(()=>`Negative size values should be exactly -1 but got ${t} for the slice() size at index ${n}.`)),e.shape[n]-r[n]))),[r,o]}function sl(e,t,n,r,a,o,s,i,u){let l;if(null==r?(l=new Array(t.length),l.fill(1)):l=r,null!=s&&0!=(s&s-1))throw new Error("Multiple ellipses in slice is not allowed.");let c=!1;const p={dims:l.length,numAddAxisAfterEllipsis:0,begin:t.slice(),end:n.slice(),strides:l.slice(),beginMask:a,endMask:o,ellipsisMask:s,newAxisMask:i,shrinkAxisMask:u};for(let e=0;e<p.dims;e++)c&&0!=(1<<e&i)&&p.numAddAxisAfterEllipsis++,1<<e&s&&(c=!0);c||(p.ellipsisMask|=1<<p.dims,p.dims++);const d={dims:e.length,beginMask:0,endMask:0,beginValid:!1,endValid:!1};!function(e,t){t.beginMask=0,t.endMask=0,t.shrinkAxisMask=0;let n=0;t.beginValid=null!=e.begin,t.endValid=null!=e.end,t.begin=new Array(t.dims),t.end=new Array(t.dims),t.strides=new Array(t.dims),t.finalShapeGatherIndices=[],t.finalShapeGatherIndicesSparse=[],t.inputShapeGatherIndicesSparse=new Array(t.dims);for(let r=0;r<e.dims;r++)if(1<<r&e.ellipsisMask){const a=Math.min(t.dims-(e.dims-r)+1+e.numAddAxisAfterEllipsis,t.dims);for(;n<a;n++)t.begin[n]=0,t.end[n]=0,t.strides[n]=1,t.beginMask|=1<<n,t.endMask|=1<<n,t.finalShapeGatherIndices.push(n),t.finalShapeGatherIndicesSparse.push(-1),t.inputShapeGatherIndicesSparse[n]=r}else if(1<<r&e.newAxisMask)t.finalShapeGatherIndices.push(ju),t.finalShapeGatherIndicesSparse.push(-1);else{if(n===t.begin.length)throw Error(`Index out of range using input dim ${n}; input has only ${t.dims} dims, ${t.begin.length}.`);null!=e.begin&&(t.begin[n]=e.begin[r]),null!=e.end&&(t.end[n]=e.end[r]),t.strides[n]=e.strides[r],e.beginMask&1<<r&&(t.beginMask|=1<<n),e.endMask&1<<r&&(t.endMask|=1<<n),e.shrinkAxisMask&1<<r?(t.finalShapeGatherIndices.push(Wu),t.finalShapeGatherIndicesSparse.push(-1),t.shrinkAxisMask|=1<<n):(t.finalShapeGatherIndices.push(n),t.finalShapeGatherIndicesSparse.push(r)),t.inputShapeGatherIndicesSparse[n]=r,n++}}(p,d);let f=!0,h=!0,m=!0;const g=[],y=[];for(let t=0;t<e.length;++t){if(0===d.strides[t])throw Error(`strides[${t}] must be non-zero`);const n=!!(d.shrinkAxisMask&1<<t),r=e[t];if(-1===r){g.push(n?1:-1);continue}const a=[d.beginMask&1<<t,d.endMask&1<<t],o=[d.strides[t]>0?0:-1,d.strides[t]>0?r:r-1];if(n&&d.strides[t]<=0)throw Error("only stride 1 allowed on non-range indexing.");m=m&&1===d.strides[t];const s=!!(d.beginMask&1<<t&&d.endMask&1<<t);if(d.beginValid&&d.endValid){if(n){const e=d.begin[t]<0?r+d.begin[t]:d.begin[t];if(d.begin[t]=e,d.end[t]=d.begin[t]+1,e<0||e>=r)throw Error(`slice index ${d.begin[t]} of dimension ${t} out of bounds.`)}else d.begin[t]=il(d.begin[t],0,d.strides[t],r,a,o),d.end[t]=il(d.end[t],1,d.strides[t],r,a,o);const e=1===d.strides[t]&&0===d.begin[t]&&d.end[t]===r;f=f&&e,h=h&&(0===t&&1===d.strides[t]||e)}else f=f&&1===d.strides[t]&&s,h=h&&(0===t&&1===d.strides[t]||s);let i,u=!1;if(d.beginValid&&d.endValid?(i=d.end[t]-d.begin[t],u=!0):n?(i=1,u=!0):s&&r>=0&&(i=d.strides[t]<0?-r:r,u=!0),u){let e;e=0===i||i<0!=d.strides[t]<0?0:Math.trunc(i/d.strides[t])+(i%d.strides[t]!=0?1:0),g.push(e)}else g.push(-1)}for(let e=0;e<d.finalShapeGatherIndices.length;++e){const t=d.finalShapeGatherIndices[e];t>=0?y.push(g[t]):t===ju&&y.push(1)}return{finalShapeSparse:y.filter(((e,t)=>d.finalShapeGatherIndices[t]!==ju)),finalShape:y,isIdentity:f,sliceDim0:h,isSimpleSlice:m,begin:d.begin,end:d.end,strides:d.strides}}function il(e,t,n,r,a,o){if(a[t])return n>0?o[t]:o[t+1&1];{const t=e<0?r+e:e;return t<o[0]?o[0]:t>o[1]?o[1]:t}}
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const ul=.001,ll=.1;function cl(e,t,n){return null==n&&(n=pl()),dl(e,t,((e,t)=>gl(e,t,n)))}function pl(){return 32===Mo.backend.floatPrecision()?ul:ll}function dl(e,t,n){let r=!0;if((Wa(e)||Wa(t))&&(r=!1),Wa(e)&&Wa(t)&&(r=!0),r){const n=e.constructor.name,r=t.constructor.name;if(n!==r)throw new Error(`Arrays are of different type. Actual: ${n}. Expected: ${r}`)}if(Array.isArray(e)&&Array.isArray(t)){const n=Po(e),r=Po(t);if(!re(n,r))throw new Error(`Arrays have different shapes. Actual: [${n}]. Expected: [${r}]`)}const a=Wa(e)?e:Ha(e),o=Wa(t)?t:Ha(t);if(a.length!==o.length)throw new Error(`Arrays have different lengths actual: ${a.length} vs expected: ${o.length}.\nActual: ${a}.\nExpected: ${o}.`);for(let e=0;e<o.length;++e){const t=a[e],r=o[e];if(!n(t,r))throw new Error(`Arrays differ: actual[${e}] = ${t}, expected[${e}] = ${r}.\nActual: ${a}.\nExpected: ${o}.`)}"undefined"!=typeof expect&&expect().nothing()}function fl(e,t){e().then((()=>t.fail()),(()=>t())),"undefined"!=typeof expect&&expect().nothing()}function hl(e,t){const n="string"==typeof t||"number"==typeof t||"boolean"==typeof t?[t]:t;return we(e)||we(e[0])||we(t)||we(t[0])?dl(e,n,((e,t)=>e==t)):dl(e,t,((e,t)=>gl(e,t,0)))}function ml(e,t,n){if(null==n&&(n=pl()),!gl(e,t,n))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`);"undefined"!=typeof expect&&expect().nothing()}function gl(e,t,n){return!isFinite(e)&&!isFinite(t)||!(isNaN(e)||isNaN(t)||Math.abs(e-t)>n)}function yl(e,t,n){for(let r=0;r<e.length;r++)if(e[r]<t||e[r]>n)throw new Error(`Value out of range:${e[r]} low: ${t}, high: ${n}`)}function bl(e,t){const n=new Float32Array(e),r=new Float32Array(t);if(n.length!==r.length)throw new Error(`Expected ArrayBuffer to be of length ${r.length}, but it was ${n.length}`);for(let e=0;e<r.length;e++)if(n[e]!==r[e])throw new Error(`Expected ArrayBuffer value at ${e} to be ${r[e]} but got ${n[e]} instead`)}function vl(e){for(let t=0;t<e.length;t++){const n=e[t];Array.isArray(n)?vl(n):e[t]=Ua(n)}return e}function wl(e){const t=document.createElement("video");return"playsInline"in t&&(t.playsInline=!0),t.muted=!0,t.loop=!0,t.style.position="fixed",t.style.left="0px",t.style.top="0px",t.preload="auto",t.appendChild(e),new Promise((e=>{t.addEventListener("loadeddata",(n=>e(t))),t.load()}))}async function xl(e){await e.play(),"requestVideoFrameCallback"in e&&await new Promise((t=>{e.requestVideoFrameCallback(t)}))}
/** @license See the LICENSE file. */
const kl="4.13.0";
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Sl{static sgd(e){return new Zi(e)}static momentum(e,t,n=!1){return new Ji(e,t,n)}static rmsprop(e,t=.9,n=0,r=null,a=!1){return new eu(e,t,n,r,a)}static adam(e=.001,t=.9,n=.999,r=null){return new Hi(e,t,n,r)}static adadelta(e=.001,t=.95,n=null){return new Bi(e,t,n)}static adamax(e=.002,t=.9,n=.999,r=null,a=0){return new Xi(e,t,n,r,a)}static adagrad(e,t=.1){return new Ui(e,t)}}const El=jo({acos_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","acos")};return Mo.runKernel(qe,t)}});const Nl=jo({acosh_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","acosh")};return Mo.runKernel(Ge,t)}});const Tl=jo({addN_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){X(Array.isArray(e),(()=>"The argument passed to tf.addN() must be a list of tensors")),X(e.length>=1,(()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`));const t=e.map(((e,t)=>Bo(e,`tensors${t}`,"addN"))),n=t[0];t.forEach((e=>{if(e.dtype!==n.dtype)throw new Error("All tensors passed to tf.addN() must have the same dtype")})),t.forEach((e=>{if(!re(e.shape,n.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")}));const r=t;return Mo.runKernel(Qe,r)}});const _l=jo({all_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){const r={x:Bo(e,"x","all","bool")},a={axis:t,keepDims:n};return Mo.runKernel(Ye,r,a)}});const Al=jo({any_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){const r={x:Bo(e,"x","any","bool")},a={axis:t,keepDims:n};return Mo.runKernel(Xe,r,a)}});const Il=jo({argMax_:
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){const n={x:Bo(e,"x","argMax")},r={axis:t};return Mo.runKernel(Ze,n,r)}});const Ml=jo({argMin_:
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){const n={x:Bo(e,"x","argMin")},r={axis:t};return Mo.runKernel(Je,n,r)}});const Ol=jo({asin_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","asin")};return Mo.runKernel(et,t)}});const Dl=jo({asinh_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","asinh")};return Mo.runKernel(tt,t)}});const Cl=jo({atan_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","atan")};return Mo.runKernel(nt,t)}});const $l=jo({atan2_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","atan2"),r=Bo(t,"b","atan2");[n,r]=xo(n,r);const a={a:n,b:r};return Mo.runKernel(at,a)}});const Rl=jo({atanh_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","atanh")};return Mo.runKernel(rt,t)}});
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Fl(e,t,n,r,a="NHWC",o){return zl(e,[...t,e[3]],n,o,r,null,null,Ql(a))}function Pl(e,t,n,r,a,o,s="channelsLast"){const[i,u]=Ul(t);let l;if("channelsLast"===s)l=[i,u,e[3],e[3]];else{if("channelsFirst"!==s)throw new Error(`Unknown dataFormat ${s}`);l=[i,u,e[1],e[1]]}return zl(e,l,n,r,a,o,!1,s)}function Ll(e,t,n,r,a,o,s="NDHWC"){const[i,u,l]=jl(t);let c,p;if("NDHWC"===s)p="channelsLast",c=[i,u,l,e[4],e[4]];else{if("NCDHW"!==s)throw new Error(`Unknown dataFormat ${s}`);p="channelsFirst",c=[i,u,l,e[1],e[1]]}return Bl(e,c,n,r,a,!1,p,o)}function zl(e,t,n,r,a,o,s=!1,i="channelsLast"){let[u,l,c,p]=[-1,-1,-1,-1];if("channelsLast"===i)[u,l,c,p]=e;else{if("channelsFirst"!==i)throw new Error(`Unknown dataFormat ${i}`);[u,p,l,c]=e}const[d,f,,h]=t,[m,g]=Ul(n),[y,b]=Ul(r),v=Wl(d,y),w=Wl(f,b),{padInfo:x,outHeight:k,outWidth:S}=function(e,t,n,r,a,o,s,i,u){let l,c,p;if("number"==typeof e){l={top:e,bottom:e,left:e,right:e,type:0===e?"VALID":"NUMBER"};const a=function(e,t,n,r,a){null==r&&(r=Vl(e,t,n));const o=e[0],s=e[1],i=Hl((o-t+2*r)/n+1,a),u=Hl((s-t+2*r)/n+1,a);return[i,u]}([t,n],o,r,e,i);c=a[0],p=a[1]}else if("same"===e){c=Math.ceil(t/r),p=Math.ceil(n/a);const e=Math.max(0,(c-1)*r+o-t),i=Math.max(0,(p-1)*a+s-n),u=Math.floor(e/2),d=e-u,f=Math.floor(i/2);l={top:u,bottom:d,left:f,right:i-f,type:"SAME"}}else if("valid"===e)l={top:0,bottom:0,left:0,right:0,type:"VALID"},c=Math.ceil((t-o+1)/r),p=Math.ceil((n-s+1)/a);else{if("object"!=typeof e)throw Error(`Unknown padding parameter: ${e}`);{const d="channelsLast"===u?e[1][0]:e[2][0],f="channelsLast"===u?e[1][1]:e[2][1],h="channelsLast"===u?e[2][0]:e[3][0],m="channelsLast"===u?e[2][1]:e[3][1];l={top:d,bottom:f,left:h,right:m,type:0===d&&0===f&&0===h&&0===m?"VALID":"EXPLICIT"},c=Hl((t-o+d+f)/r+1,i),p=Hl((n-s+h+m)/a+1,i)}}return{padInfo:l,outHeight:c,outWidth:p}}(a,l,c,m,g,v,w,o,i),E=s?h*p:h;let N;return"channelsFirst"===i?N=[u,E,k,S]:"channelsLast"===i&&(N=[u,k,S,E]),{batchSize:u,dataFormat:i,inHeight:l,inWidth:c,inChannels:p,outHeight:k,outWidth:S,outChannels:E,padInfo:x,strideHeight:m,strideWidth:g,filterHeight:d,filterWidth:f,effectiveFilterHeight:v,effectiveFilterWidth:w,dilationHeight:y,dilationWidth:b,inShape:e,outShape:N,filterShape:t}}function Bl(e,t,n,r,a,o=!1,s="channelsLast",i){let[u,l,c,p,d]=[-1,-1,-1,-1,-1];if("channelsLast"===s)[u,l,c,p,d]=e;else{if("channelsFirst"!==s)throw new Error(`Unknown dataFormat ${s}`);[u,d,l,c,p]=e}const[f,h,m,,g]=t,[y,b,v]=jl(n),[w,x,k]=jl(r),S=Wl(f,w),E=Wl(h,x),N=Wl(m,k),{padInfo:T,outDepth:_,outHeight:A,outWidth:I}=function(e,t,n,r,a,o,s,i,u,l,c){let p,d,f,h;"valid"===e&&(e=0);if("number"==typeof e){p={top:e,bottom:e,left:e,right:e,front:e,back:e,type:0===e?"VALID":"NUMBER"};const m=function(e,t,n,r,a,o){null==a&&(a=Vl(e,t[0],r[0]));const s=[0,0,0,n];for(let n=0;n<3;n++)e[n]+2*a>=t[n]&&(s[n]=Hl((e[n]-t[n]+2*a)/r[n]+1,o));return s}([t,n,r,1],[i,u,l],1,[a,o,s],e,c);d=m[0],f=m[1],h=m[2]}else{if("same"!==e)throw Error(`Unknown padding parameter: ${e}`);{d=Math.ceil(t/a),f=Math.ceil(n/o),h=Math.ceil(r/s);const e=(d-1)*a+i-t,c=(f-1)*o+u-n,m=(h-1)*s+l-r,g=Math.floor(e/2),y=e-g,b=Math.floor(c/2),v=c-b,w=Math.floor(m/2);p={top:b,bottom:v,left:w,right:m-w,front:g,back:y,type:"SAME"}}}return{padInfo:p,outDepth:d,outHeight:f,outWidth:h}}(a,l,c,p,y,b,v,S,E,N,i),M=o?g*d:g;let O;return"channelsFirst"===s?O=[u,M,_,A,I]:"channelsLast"===s&&(O=[u,_,A,I,M]),{batchSize:u,dataFormat:s,inDepth:l,inHeight:c,inWidth:p,inChannels:d,outDepth:_,outHeight:A,outWidth:I,outChannels:M,padInfo:T,strideDepth:y,strideHeight:b,strideWidth:v,filterDepth:f,filterHeight:h,filterWidth:m,effectiveFilterDepth:S,effectiveFilterHeight:E,effectiveFilterWidth:N,dilationDepth:w,dilationHeight:x,dilationWidth:k,inShape:e,outShape:O,filterShape:t}}function Vl(e,t,n,r=1){const a=Wl(t,r);return Math.floor((e[0]*(n-1)-n+a)/2)}function Ul(e){return"number"==typeof e?[e,e,e]:2===e.length?[e[0],e[1],1]:e}function jl(e){return"number"==typeof e?[e,e,e]:e}function Wl(e,t){return t<=1?e:e+(e-1)*(t-1)}function Hl(e,t){if(!t)return Math.trunc(e);switch(t){case"round":return Math.round(e);case"ceil":return Math.ceil(e);case"floor":return Math.floor(e);default:throw new Error(`Unknown roundingMode ${t}`)}}function ql(e){const[t,n,r]=Ul(e);return 1===t&&1===n&&1===r}function Gl(e,t){return ql(e)||ql(t)}function Kl(e){return Ul(e).every((e=>e>0))}function Ql(e){if("NHWC"===e)return"channelsLast";if("NCHW"===e)return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function Yl(e,t,n){if(null!=n){if("string"==typeof t)throw Error(`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`);if("number"==typeof t)X(ae(t),(()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`));else{if("object"!=typeof t)throw Error(`Error in ${e}: Unknown padding parameter: ${t}`);t.forEach((t=>{t.forEach((t=>{X(ae(t),(()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`))}))}))}}}const Xl=jo({reshape_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n={x:Bo(e,"x","reshape","string_or_numeric")},r={shape:t};return Mo.runKernel(lr,n,r)}});const Zl=jo({avgPool_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a){const o=Bo(e,"x","avgPool","float32");X(Gl(n,1),(()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${n} and dilations '1'`));let s=o,i=!1;3===o.rank&&(i=!0,s=Xl(o,[1,o.shape[0],o.shape[1],o.shape[2]])),X(4===s.rank,(()=>`Error in avgPool: x must be rank 4 but got rank ${s.rank}.`)),Yl("avgPool",r,a);const u={x:s},l={filterSize:t,strides:n,pad:r,dimRoundingMode:a};let c=Mo.runKernel(ot,u,l);return c=Ks(c,o.dtype),i?Xl(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});const Jl=jo({avgPool3d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o="NDHWC"){const s=Bo(e,"x","avgPool3d","float32");let i=s,u=!1;4===s.rank&&(u=!0,i=Xl(s,[1,s.shape[0],s.shape[1],s.shape[2],s.shape[3]])),X(5===i.rank,(()=>`Error in avgPool3d: x must be rank 5 but got rank ${i.rank}.`)),X("NDHWC"===o,(()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${o}`)),X("number"==typeof n&&n>0||Array.isArray(n)&&n[0]>0&&n[1]>0&&n[2]>0,(()=>`Error in avgPool3d: Stride must be > 0, but got '${n}'`)),Yl("avgPool3d",r,a);const l={x:i},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:o};let p=Mo.runKernel(it,l,c);return p=Ks(p,i.dtype),u?Xl(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}});const ec=jo({concat_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){X(e.length>=1,(()=>"Pass at least one tensor to concat"));const n=Vo(e,"tensors","concat","string_or_numeric");if("complex64"===n[0].dtype&&n.forEach((e=>{if("complex64"!==e.dtype)throw new Error(`Cannot concatenate complex64 tensors with a tensor\n with dtype ${e.dtype}. `)})),1===n.length)return Qs(n[0]);const r=n,a={axis:t};return Mo.runKernel(wt,r,a)}});const tc=jo({sigmoid_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","sigmoid","float32")};return Mo.runKernel(_r,t)}});const nc=jo({slice_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","slice","string_or_numeric");if(0===r.rank)throw new Error("Slicing scalar is not possible");const a={x:r},o={begin:t,size:n};return Mo.runKernel(Sr,a,o)}});const rc=jo({tanh_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","tanh","float32")};return Mo.runKernel(Kr,t)}});const ac=jo({basicLSTMCell_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o){const s=Bo(e,"forgetBias","basicLSTMCell"),i=Bo(t,"lstmKernel","basicLSTMCell"),u=Bo(n,"lstmBias","basicLSTMCell"),l=Bo(r,"data","basicLSTMCell"),c=Bo(a,"c","basicLSTMCell"),p=Bo(o,"h","basicLSTMCell"),d=ec([l,p],1),f=ku(d,i),h=bi(f,u),m=h.shape[0],g=h.shape[1]/4,y=[m,g],b=nc(h,[0,0],y),v=nc(h,[0,g],y),w=nc(h,[0,2*g],y),x=nc(h,[0,3*g],y),k=bi(xi(tc(b),rc(v)),xi(c,tc(bi(s,w))));return[k,xi(rc(k),tc(x))]}});const oc=jo({batchToSpaceND_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","batchToSpaceND"),a=t.reduce(((e,t)=>e*t));X(r.rank>=1+t.length,(()=>`input rank is ${r.rank} but should be > than blockShape.length ${t.length}`)),X(n.length===t.length,(()=>`crops.length is ${n.length} but should be equal to blockShape.length ${t.length}`)),X(r.shape[0]%a==0,(()=>`input tensor batch is ${r.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${a}`));const o={x:r},s={blockShape:t,crops:n};return Mo.runKernel(ct,o,s)}});const sc=jo({batchNorm_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o){null==o&&(o=.001);const s=Bo(e,"x","batchNorm"),i=Bo(t,"mean","batchNorm"),u=Bo(n,"variance","batchNorm");let l,c;null!=a&&(l=Bo(a,"scale","batchNorm")),null!=r&&(c=Bo(r,"offset","batchNorm")),X(i.rank===u.rank,(()=>"Batch normalization gradient requires mean and variance to have equal ranks.")),X(null==c||i.rank===c.rank,(()=>"Batch normalization gradient requires mean and offset to have equal ranks.")),X(null==l||i.rank===l.rank,(()=>"Batch normalization gradient requires mean and scale to have equal ranks."));const p={x:function(e){let t;return t=0===e.rank||1===e.rank?Xl(e,[1,1,1,e.size]):2===e.rank?Xl(e,[1,1,e.shape[0],e.shape[1]]):3===e.rank?Xl(e,[1,e.shape[0],e.shape[1],e.shape[2]]):e,t}(s),scale:l,offset:c,mean:i,variance:u},d={varianceEpsilon:o},f=Mo.runKernel(nn,p,d);return Xl(f,s.shape)}});const ic=jo({batchNorm2d_:function(e,t,n,r,a,o){const s=Bo(e,"x","batchNorm"),i=Bo(t,"mean","batchNorm"),u=Bo(n,"variance","batchNorm");let l,c;return null!=a&&(l=Bo(a,"scale","batchNorm")),null!=r&&(c=Bo(r,"offset","batchNorm")),X(2===s.rank,(()=>`Error in batchNorm2D: x must be rank 2 but got rank ${s.rank}.`)),X(2===i.rank||1===i.rank,(()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${i.rank}.`)),X(2===u.rank||1===u.rank,(()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${u.rank}.`)),null!=l&&X(2===l.rank||1===l.rank,(()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${l.rank}.`)),null!=c&&X(2===c.rank||1===c.rank,(()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`)),sc(s,i,u,c,l,o)}});const uc=jo({batchNorm3d_:function(e,t,n,r,a,o){const s=Bo(e,"x","batchNorm"),i=Bo(t,"mean","batchNorm"),u=Bo(n,"variance","batchNorm");let l,c;return null!=a&&(l=Bo(a,"scale","batchNorm")),null!=r&&(c=Bo(r,"offset","batchNorm")),X(3===s.rank,(()=>`Error in batchNorm3D: x must be rank 3 but got rank ${s.rank}.`)),X(3===i.rank||1===i.rank,(()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`)),X(3===u.rank||1===u.rank,(()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${u.rank}.`)),null!=l&&X(3===l.rank||1===l.rank,(()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${l.rank}.`)),null!=c&&X(3===c.rank||1===c.rank,(()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`)),sc(s,i,u,c,l,o)}});const lc=jo({batchNorm4d_:function(e,t,n,r,a,o){const s=Bo(e,"x","batchNorm"),i=Bo(t,"mean","batchNorm"),u=Bo(n,"variance","batchNorm");let l,c;return null!=a&&(l=Bo(a,"scale","batchNorm")),null!=r&&(c=Bo(r,"offset","batchNorm")),X(4===s.rank,(()=>`Error in batchNorm4D: x must be rank 4 but got rank ${s.rank}.`)),X(4===i.rank||1===i.rank,(()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`)),X(4===u.rank||1===u.rank,(()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${u.rank}.`)),null!=l&&X(4===l.rank||1===l.rank,(()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${l.rank}.`)),null!=c&&X(4===c.rank||1===c.rank,(()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`)),sc(s,i,u,c,l,o)}});const cc=jo({bincount_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","bincount"),a=Bo(t,"weights","bincount");X("int32"===r.dtype,(()=>`Error in bincount: input dtype must be int32, but got ${r.dtype}`)),X(n>=0,(()=>`size must be non-negative, but got ${n}.`)),X(a.size===r.size||0===a.size,(()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${r.shape}, weights shape: ${a.shape}.`));const o={x:r,weights:a},s={size:n};return Mo.runKernel(pt,o,s)}});const pc=jo({bitwiseAnd_:
/**
* @license
* Copyright 2023 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","bitwiseAnd"),r=Bo(t,"y","bitwiseAnd");if(!re(n.shape,r.shape))throw new Error(`BitwiseAnd: Tensors must have the same shape. x: ${n.shape}, y: ${r.shape}`);if("int32"!==n.dtype||"int32"!==r.dtype)throw new Error(`BitwiseAnd: Only supports 'int32' values in tensor, found type of x: ${n.dtype} and type of y: ${r.dtype}`);const a={a:n,b:r};return Mo.runKernel(dt,a)}});const dc=jo({broadcastArgs_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"s0","broadcastArgs","int32"),r=Bo(t,"s1","broadcastArgs","int32");if(1!==n.rank)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${n.rank}`);if(1!==r.rank)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${r.rank}`);const a={s0:n,s1:r};return Mo.runKernel(ht,a)}});const fc=jo({broadcastTo_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"broadcastTo","x");const r=n.shape;if(Ce(t),t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){const e=n.shape.slice();for(;e.length<t.length;)e.unshift(1);n=Xl(n,e)}const a=n.shape,o=Array.from(t);for(let e=t.length-1;e>=0;e--)if(a[e]===t[e])o[e]=1;else if(1!==n.shape[e])throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${t}].`);if(0===o.map(((e,t)=>e>1?t:-1)).filter((e=>e>=0)).length)return Qs(n);const s={x:n},i={reps:o};return Mo.runKernel(Qr,s,i)}});const hc=jo({ceil_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","ceil","float32")};return Mo.runKernel(gt,t)}});const mc=jo({clipByValue_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","clipByValue");if(X(t<=n,(()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`)),t===n)return Vi(r.shape,t,r.dtype);const a={x:r},o={clipValueMin:t,clipValueMax:n};return Mo.runKernel(yt,a,o)}});const gc=jo({concat1d_:function(e){return ec(e,0)}});const yc=jo({concat2d_:function(e,t){return ec(e,t)}});const bc=jo({concat3d_:function(e,t){return ec(e,t)}});const vc=jo({concat4d_:function(e,t){return ec(e,t)}});const wc=jo({conv2d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a="NHWC",o=[1,1],s){const i=Bo(e,"x","conv2d","float32"),u=Bo(t,"filter","conv2d","float32");let l=i,c=!1;3===i.rank&&(c=!0,l=Xl(i,[1,i.shape[0],i.shape[1],i.shape[2]])),X(4===l.rank,(()=>`Error in conv2d: input must be rank 4, but got rank ${l.rank}.`)),X(4===u.rank,(()=>`Error in conv2d: filter must be rank 4, but got rank ${u.rank}.`)),Yl("conv2d",r,s);const p="NHWC"===a?l.shape[3]:l.shape[1];X(p===u.shape[2],(()=>`Error in conv2d: depth of input (${p}) must match input depth for filter ${u.shape[2]}.`)),X(Gl(n,o),(()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`)),X(Kl(o),(()=>"Error in conv2D: Dilated rates should be larger than 0.")),X(Kl(n),(()=>"Error in conv2D: Strides should be larger than 0."));const d={x:l,filter:u},f={strides:n,pad:r,dataFormat:a,dilations:o,dimRoundingMode:s},h=Mo.runKernel(xt,d,f);return c?Xl(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});const xc=jo({conv1d_:function(e,t,n,r,a="NWC",o=1,s){const i=Bo(e,"x","conv1d"),u=Bo(t,"filter","conv1d");let l=i,c=!1;2===i.rank&&(c=!0,l=Xl(i,[1,i.shape[0],i.shape[1]])),X(3===l.rank,(()=>`Error in conv1d: input must be rank 3, but got rank ${l.rank}.`)),X(3===u.rank,(()=>`Error in conv1d: filter must be rank 3, but got rank ${u.rank}.`)),Yl("conv1d",r,s),X(l.shape[2]===u.shape[1],(()=>`Error in conv1d: depth of input (${l.shape[2]}) must match input depth for filter ${u.shape[1]}.`)),X(Gl(n,o),(()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${o}'`)),X(Kl(o),(()=>"Error in conv1D: Dilated rates should be larger than 0.")),X(Kl(n),(()=>"Error in conv1D: Stride should be larger than 0.")),X("NWC"===a,(()=>`Error in conv1d: got dataFormat of ${a} but only NWC is currently supported.`));const p=Xl(u,[1,u.shape[0],u.shape[1],u.shape[2]]),d=Xl(l,[l.shape[0],1,l.shape[1],l.shape[2]]),f=wc(d,p,[1,n],r,"NHWC",[1,o],s);return Xl(f,c?[f.shape[2],f.shape[3]]:[f.shape[0],f.shape[2],f.shape[3]])}});const kc=jo({conv2DBackpropInput_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o="NHWC",s){X(e.length===t.rank,(()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`));let i=e,u=t,l=!1;3===t.rank&&(l=!0,u=Xl(t,[1,t.shape[0],t.shape[1],t.shape[2]]),i=[1,e[0],e[1],e[2]]),X(4===i.length,(()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`)),X(4===u.rank,(()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${u.rank}`)),X(4===n.rank,(()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`));const c="NHWC"===o?i[3]:i[1],p="NHWC"===o?u.shape[3]:u.shape[1];X(c===n.shape[2],(()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`)),X(p===n.shape[3],(()=>`Error in conv2dDerInput: depth of output (${p}) must match output depth for filter ${n.shape[3]}.`)),Yl("conv2dDerInput",a,s);const d={dy:u,filter:n},f={strides:r,pad:a,dataFormat:o,dimRoundingMode:s,inputShape:i},h=Mo.runKernel(St,d,f);return l?Xl(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});const Sc=jo({conv2dTranspose_:function(e,t,n,r,a,o){const s=Bo(e,"x","conv2dTranspose"),i=Bo(t,"filter","conv2dTranspose");return kc(n,s,i,r,a,"NHWC",o)}});const Ec=jo({conv3d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a="NDHWC",o=[1,1,1]){const s=Bo(e,"x","conv3d"),i=Bo(t,"filter","conv3d");let u=s,l=!1;4===s.rank&&(l=!0,u=Xl(s,[1,s.shape[0],s.shape[1],s.shape[2],s.shape[3]])),X(5===u.rank,(()=>`Error in conv3d: input must be rank 5, but got rank ${u.rank}.`)),X(5===i.rank,(()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`)),X(u.shape[4]===i.shape[3],(()=>`Error in conv3d: depth of input (${u.shape[4]}) must match input depth for filter ${i.shape[3]}.`)),X(Gl(n,o),(()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`)),X("NDHWC"===a,(()=>`Error in conv3d: got dataFormat of ${a} but only NDHWC is currently supported.`)),X(Kl(o),(()=>"Error in conv3D: Dilated rates should be larger than 0.")),X(Kl(n),(()=>"Error in conv3D: Strides should be larger than 0."));const c={x:u,filter:i},p={strides:n,pad:r,dataFormat:a,dilations:o},d=Mo.runKernel(Et,c,p);return l?Xl(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}});const Nc=jo({conv3DBackpropInput_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a){X(e.length===t.rank,(()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`));let o=e,s=t,i=!1;4===t.rank&&(i=!0,s=Xl(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),o=[1,e[0],e[1],e[2],e[3]]);const u=o[4],l=s.shape[4];X(5===o.length,(()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${o.length}.`)),X(5===s.rank,(()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${s.rank}`)),X(5===n.rank,(()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`)),X(u===n.shape[3],(()=>`Error in conv3dDerInput: depth of input (${u}) must match input depth for filter ${n.shape[3]}.`)),X(l===n.shape[4],(()=>`Error in conv3dDerInput: depth of output (${l}) must match output depth for filter ${n.shape[4]}.`));const c={dy:s,filter:n},p={pad:a,strides:r,inputShape:o},d=Mo.runKernel(Tt,c,p);return i?Xl(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}});const Tc=jo({conv3dTranspose_:function(e,t,n,r,a){const o=Bo(e,"x","conv3dTranspose"),s=Bo(t,"filter","conv3dTranspose");return Nc(n,o,s,r,a)}});const _c=jo({cos_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","cos","float32")};return Mo.runKernel(_t,t)}});const Ac=jo({cosh_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","cosh","float32")};return Mo.runKernel(At,t)}});const Ic=jo({cumprod_:
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the 'License');
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an 'AS IS' BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0,n=!1,r=!1){const a={x:Bo(e,"x","cumprod")},o={axis:t,exclusive:n,reverse:r};return Mo.runKernel(It,a,o)}});const Mc=jo({cumsum_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0,n=!1,r=!1){const a={x:Bo(e,"x","cumsum")},o={axis:t,exclusive:n,reverse:r};return Mo.runKernel(Mt,a,o)}});const Oc=jo({denseBincount_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=!1){const a=Bo(e,"x","denseBincount"),o=Bo(t,"weights","denseBincount");X("int32"===a.dtype,(()=>`Error in denseBincount: input dtype must be int32, but got ${a.dtype}`)),X(a.rank<=2,(()=>`Error in denseBincount: input must be at most rank 2, but got rank ${a.rank}.`)),X(n>=0,(()=>`size must be non-negative, but got ${n}.`)),X(o.size===a.size||0===o.size,(()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${a.shape}, weights shape: ${o.shape}.`));const s={x:a,weights:o},i={size:n,binaryOutput:r};return Mo.runKernel(Dt,s,i)}});const Dc=jo({depthToSpace_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n="NHWC"){const r=Bo(e,"x","depthToSpace","float32"),a="NHWC"===n?r.shape[1]:r.shape[2],o="NHWC"===n?r.shape[2]:r.shape[3],s="NHWC"===n?r.shape[3]:r.shape[1];X(t>1,(()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`)),X(a*t>=0,(()=>`Negative dimension size caused by overflow when multiplying\n ${a} and ${t} for depthToSpace with input shape\n ${r.shape}`)),X(o*t>=0,(()=>`Negative dimension size caused by overflow when multiplying\n ${o} and ${t} for depthToSpace with input shape\n ${r.shape}`)),X(s%(t*t)==0,(()=>`Dimension size must be evenly divisible by ${t*t} but is ${s} for depthToSpace with input shape ${r.shape}`));const i={x:r},u={blockSize:t,dataFormat:n};return Mo.runKernel(Ct,i,u)}});const Cc=jo({depthwiseConv2d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a="NHWC",o=[1,1],s){const i=Bo(e,"x","depthwiseConv2d","float32"),u=Bo(t,"filter","depthwiseConv2d","float32");let l=i,c=!1;3===i.rank&&(c=!0,l=Xl(i,[1,i.shape[0],i.shape[1],i.shape[2]])),X(4===l.rank,(()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${l.rank}.`)),X(4===u.rank,(()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${u.rank}.`));const p="NHWC"===a?l.shape[3]:l.shape[1];X(p===u.shape[2],(()=>`Error in depthwiseConv2d: number of input channels (${p}) must match the inChannels dimension in filter ${u.shape[2]}.`)),Yl("depthwiseConv2d",r,s);const d={x:l,filter:u},f={strides:n,pad:r,dataFormat:a,dilations:o,dimRoundingMode:s},h=Mo.runKernel($t,d,f);return c?Xl(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});const $c=jo({diag_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","diag")};return Mo.runKernel(Pt,t)}});const Rc=jo({dilation2d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a=[1,1],o="NHWC"){const s=Bo(e,"x","dilation2d"),i=Bo(t,"filter","dilation2d");X(3===s.rank||4===s.rank,(()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${s.rank}.`)),X(3===i.rank,(()=>`Error in dilation2d: filter must be rank 3, but got rank ${i.rank}.`)),X("NHWC"===o,(()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${o}`));let u=s,l=!1;3===s.rank&&(u=Xl(s,[1,s.shape[0],s.shape[1],s.shape[2]]),l=!0),X(u.shape[3]===i.shape[2],(()=>`Error in dilation2d: input and filter must have the same depth: ${u.shape[3]} vs ${i.shape[2]}`));const c={x:u,filter:i},p={strides:n,pad:r,dilations:a},d=Mo.runKernel(Lt,c,p);return l?Xl(d,[d.shape[1],d.shape[2],d.shape[3]]):d}});const Fc=jo({equal_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","equal","string_or_numeric"),r=Bo(t,"b","equal","string_or_numeric");[n,r]=xo(n,r),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(Gt,a)}});const Pc=jo({where_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(t,"a","where"),a=Bo(n,"b","where"),o=Bo(e,"condition","where","bool"),s=Qi(Qi(o.shape,r.shape),a.shape),i={condition:fc(o,s),t:fc(r,s),e:fc(a,s)};return Mo.runKernel(xr,i)}});const Lc=jo({divNoNan_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","div"),r=Bo(t,"b","div");[n,r]=xo(n,r);const a=wi(n,r),o=Ei(a),s=Fc(r,o);return Pc(s,o,a)}});const zc=jo({dot_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"t1","dot"),r=Bo(t,"t2","dot");X(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),(()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${n.rank} and ${r.rank}.`));const a=1===n.rank?n.size:n.shape[1],o=1===r.rank?r.size:r.shape[0];if(X(a===o,(()=>`Error in dot: inner dimensions of inputs must match, but got ${a} and ${o}.`)),1===n.rank&&1===r.rank){const e=Xl(n,[1,-1]),t=Xl(r,[-1,1]),a=ku(e,t);return Xl(a,[])}if(1===n.rank&&2===r.rank){const e=Xl(n,[1,-1]),t=Xl(r,[r.shape[0],r.shape[1]]),a=ku(e,t);return Xl(a,[a.size])}if(2===n.rank&&1===r.rank){const e=Xl(r,[-1,1]),t=ku(n,e);return Xl(t,[t.size])}{const e=Xl(r,[r.shape[0],r.shape[1]]);return ku(n,e)}}});const Bc=jo({einsum_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,...t){const n=t.map(((e,t)=>Bo(e,`tensors${t}`,"einsum"))),r={equation:e};return Mo.runKernel(jt,n,r)}});const Vc=jo({elu_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","elu","float32")};return Mo.runKernel(Wt,t)}});const Uc=jo({ensureShape_:
/**
* @license
* Copyright 2023 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","ensureShape","string_or_numeric");if(!ne(n.shape,t))throw new Error(`EnsureShape: Shape of tensor ${n.shape} is not compatible with expected shape ${t}`);return e}});const jc=jo({erf_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){let t=Bo(e,"x","erf");X("int32"===t.dtype||"float32"===t.dtype,(()=>"Input dtype must be `int32` or `float32`.")),"int32"===t.dtype&&(t=Ks(t,"float32"));const n={x:t};return Mo.runKernel(qt,n)}});
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Wc(e,t){for(let n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0}function Hc(e,t,n){const r=e.length+t.length,a=[];let o=0,s=0;for(let i=0;i<r;i++)-1===n.indexOf(i)?a.push(e[o++]):a.push(t[s++]);return a}function qc(e,t){const n=[],r=e.length;for(let a=0;a<r;a++)-1===t.indexOf(a)&&n.push(e[a]);return[n,t.map((t=>e[t]))]}function Gc(e,t){return Hc(e,t.map((e=>1)),t)}function Kc(e,t,n){X(Wc(t,n),(()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${n} input.`))}function Qc(e,t){if(Wc(e,t))return null;const n=[];for(let r=0;r<t;++r)-1===e.indexOf(r)&&n.push(r);return e.forEach((e=>n.push(e))),n}function Yc(e){return e.map(((e,t)=>[t,e])).sort(((e,t)=>e[1]-t[1])).map((e=>e[0]))}function Xc(e,t){const n=[];for(let r=t-e;r<t;++r)n.push(r);return n}const Zc=jo({max_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){const r={x:Bo(e,"x","max")},a={reductionIndices:t,keepDims:n};return Mo.runKernel(In,r,a)}});const Jc=jo({min_:
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){const r={x:Bo(e,"x","min")},a={axis:t,keepDims:n};return Mo.runKernel(Pn,r,a)}});const ep=jo({sum_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){let r=Bo(e,"x","sum");"bool"===r.dtype&&(r=Ks(r,"int32"));const a={x:r},o={axis:t,keepDims:n};return Mo.runKernel(Mr,a,o)}});function tp(e,t,n=null){if(0===e.rank)return qi(e);if(1!==e.rank&&null===n)return tp(Xl(e,[-1]),t,n);if(1===e.rank||"number"==typeof n||Array.isArray(n)&&1===n.length){if(1===t)return ep(qi(e),n);if(t===1/0)return Zc(qi(e),n);if(t===-1/0)return Jc(qi(e),n);if("euclidean"===t||2===t)return ki(ep(ji(qi(e),Di(2,"int32")),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}if(Array.isArray(n)&&2===n.length){if(1===t)return Zc(ep(qi(e),n[0]),n[1]-1);if(t===1/0)return Zc(ep(qi(e),n[1]),n[0]);if(t===-1/0)return Jc(ep(qi(e),n[1]),n[0]);if("fro"===t||"euclidean"===t)return ki(ep(Si(e),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${n}`)}const np=jo({norm_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t="euclidean",n=null,r=!1){const a=tp(e=Bo(e,"x","norm"),t,n);let o=a.shape;if(r){const t=pe(n,e.shape);o=Gc(a.shape,t)}return Xl(a,o)}});const rp=jo({euclideanNorm_:
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){return np(e,"euclidean",t,n)}});const ap=jo({exp_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","exp")};return Mo.runKernel(Kt,t)}});const op=jo({expandDims_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){const n=Bo(e,"x","expandDims","string_or_numeric");X(t<=n.rank,(()=>"Axis must be <= rank of the tensor"));const r={input:n},a={dim:t};return Mo.runKernel(Qt,r,a)}});const sp=jo({expm1_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","expm1")};return Mo.runKernel(Yt,t)}});const ip=jo({tile_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","tile","string_or_numeric");X(n.rank===t.length,(()=>`Error in transpose: rank of input ${n.rank} must match length of reps ${t}.`));const r={x:n},a={reps:t};return Mo.runKernel(Qr,r,a)}});const up=jo({eye_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r="float32"){null==t&&(t=e);const a=Gs([e,t],r),o=e<=t?e:t;for(let e=0;e<o;++e)a.set(1,e,e);const s=Xl(a.toTensor(),[e,t]);if(null==n)return s;if(1===n.length)return ip(op(s,0),[n[0],1,1]);if(2===n.length)return ip(op(op(s,0),0),[n[0],n[1],1,1]);if(3===n.length)return ip(op(op(op(s,0),0),0),[n[0],n[1],n[2],1,1]);throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${n.length}D.`)}});const lp=jo({floor_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","floor","float32")};return Mo.runKernel(en,t)}});const cp=jo({gather_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=0,r=0){const a={x:Bo(e,"x","gather"),indices:Bo(t,"indices","gather","int32")},o={axis:n,batchDims:r};return Mo.runKernel(rn,a,o)}});const pp=jo({greater_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","greater","string_or_numeric"),r=Bo(t,"b","greater","string_or_numeric");[n,r]=xo(n,r),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(on,a)}});const dp=jo({greaterEqual_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","greaterEqual","string_or_numeric"),r=Bo(t,"b","greaterEqual","string_or_numeric");[n,r]=xo(n,r),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(sn,a)}});const fp=jo({isFinite_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","isFinite")};return Mo.runKernel(pn,t)}});const hp=jo({isInf_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","isInf")};return Mo.runKernel(dn,t)}});const mp=jo({isNaN_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","isNaN")};return Mo.runKernel(fn,t)}});const gp=jo({leakyRelu_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=.2){const n={x:Bo(e,"x","leakyRelu")},r={alpha:t};return Mo.runKernel(hn,n,r)}});const yp=jo({less_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","less","string_or_numeric"),r=Bo(t,"b","less","string_or_numeric");[n,r]=xo(n,r),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(mn,a)}});const bp=jo({lessEqual_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","lessEqual","string_or_numeric"),r=Bo(t,"b","lessEqual","string_or_numeric");[n,r]=xo(n,r),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(gn,a)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function vp(e,t,n){if(n<=0)throw new Error("The number of values should be positive.");const r={start:e,stop:t,num:n};return Mo.runKernel(yn,{},r)}const wp=jo({localResponseNormalization_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=5,n=1,r=1,a=.5){const o=Bo(e,"x","localResponseNormalization");X(4===o.rank||3===o.rank,(()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got\n rank ${o.rank}.`)),X(ae(t),(()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`));let s=o,i=!1;3===o.rank&&(i=!0,s=Xl(o,[1,o.shape[0],o.shape[1],o.shape[2]]));const u={x:s},l={depthRadius:t,bias:n,alpha:r,beta:a},c=Mo.runKernel(Tn,u,l);return i?Xl(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});const xp=jo({log_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","log","float32")};return Mo.runKernel(bn,t)}});const kp=jo({log1p_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","log1p")};return Mo.runKernel(vn,t)}});const Sp=jo({softplus_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","softplus")};return Mo.runKernel(Ar,t)}});const Ep=jo({logSigmoid_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=Bo(e,"x","logSigmoid");return Mi((e=>({value:Nu(Sp(Nu(e))),gradFunc:t=>xi(t,tc(Nu(e)))})))(t)}});const Np=jo({logSoftmax_:
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=-1){const n=Bo(e,"logits","logSoftmax");if(-1===t&&(t=n.rank-1),t!==n.rank-1)throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and axis was ${t}`);const r=Mi(((e,n)=>{const r=Zc(e,t,!0),a=Wi(e,r),o=Wi(Ks(a,"float32"),xp(ep(ap(a),t,!0)));n([o]);return{value:o,gradFunc:(e,n)=>{const[r]=n,a=ap(r);return Wi(e,xi(ep(e,t,!0),a))}}}));return r(n)}});const Tp=jo({logSumExp_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){const r=Bo(e,"x","logSumExp"),a=pe(t,r.shape),o=Zc(r,a,!0),s=Wi(r,o),i=ap(s),u=ep(i,a),l=xp(u),c=bi(Xl(o,l.shape),l);if(n){const e=Gc(c.shape,a);return Xl(c,e)}return c}});const _p=jo({logicalAnd_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"a","logicalAnd","bool"),r=Bo(t,"b","logicalAnd","bool");Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(wn,a)}});const Ap=jo({logicalNot_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","logicalNot","bool")};return Mo.runKernel(xn,t)}});const Ip=jo({logicalOr_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"a","logicalOr","bool"),r=Bo(t,"b","logicalOr","bool");Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(kn,a)}});const Mp=jo({logicalXor_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"a","logicalXor","bool"),r=Bo(t,"b","logicalXor","bool");return Qi(n.shape,r.shape),_p(Ip(e,t),Ap(_p(e,t)))}}),Op=2147483648;const Dp=jo({searchSorted_:function(e,t,n="left"){const r=Bo(e,"sortedSequence","searchSorted"),a=Bo(t,"values","searchSorted"),o=r.shape[r.shape.length-1],s=a.shape[a.shape.length-1],i=Xl(r,[-1,o]),u=Xl(a,[-1,s]);if(i.rank<2)throw new Error("Sorted input argument must be at least 2-dimensional");if(i.shape[0]!==u.shape[0])throw new Error("Leading dimension of 'sortedSequence' and 'values' must match.");if(ee(u.shape)>=Op)throw new Error("values tensor size must less than 2147483648");if(i.shape[1]>=Op)throw new Error(`trailing dim_size must less than 2147483648 for int32 output type, was ${i.shape[1]}`);const l={sortedSequence:i,values:u},c={side:n};return Mo.runKernel(wr,l,c)}});
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Cp(e,t){return Dp(e,t,"left")}const $p=jo({maxPool_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a){const o=Bo(e,"x","maxPool");let s=o,i=!1;3===o.rank&&(i=!0,s=Xl(o,[1,o.shape[0],o.shape[1],o.shape[2]])),X(4===s.rank,(()=>`Error in maxPool: input must be rank 4 but got rank ${s.rank}.`)),X(Gl(n,1),(()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${n} and dilations '1'`)),Yl("maxPool",r,a);const u={x:s},l={filterSize:t,strides:n,pad:r,dimRoundingMode:a},c=Mo.runKernel(On,u,l);return i?Xl(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});const Rp=jo({maxPool3d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=[1,1,1],n,r,a,o="NDHWC"){const s=Bo(e,"x","maxPool3d");let i=s,u=!1;4===s.rank&&(u=!0,i=Xl(s,[1,s.shape[0],s.shape[1],s.shape[2],s.shape[3]])),X(5===i.rank,(()=>`Error in maxPool3d: x must be rank 5 but got rank ${i.rank}.`)),X("NDHWC"===o,(()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${o}`)),Yl("maxPool3d",r,a);const l={x:i},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:o},p=Mo.runKernel(Cn,l,c);return u?Xl(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}});const Fp=jo({maxPoolWithArgmax_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a=!1){const o={x:Bo(e,"x","maxPoolWithArgmax")},s={filterSize:t,strides:n,pad:r,includeBatchInIndex:a},i=Mo.runKernel(Rn,o,s);return{result:i[0],indexes:i[1]}}});const Pp=jo({mean_:
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){const r={x:Bo(e,"x","mean")},a={axis:t,keepDims:n};return Mo.runKernel(Fn,r,a)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Lp(e,t="float32"){if(Ce(e),"complex64"===t){const t=Lp(e,"float32"),n=Lp(e,"float32");return Wo(t,n)}const n=Oe(ee(e),t);return Mo.makeTensor(n,e,t)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function zp(e,t="float32"){if(Ce(e),"complex64"===t){const t=zp(e,"float32"),n=Lp(e,"float32");return Wo(t,n)}const n=Me(ee(e),t);return Mo.makeTensor(n,e,t)}
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Bp(e,t,{indexing:n="xy"}={}){if("xy"!==n&&"ij"!==n)throw new TypeError(`${n} is not a valid third argument to meshgrid`);if(void 0===e)return[];let r=Bo(e,"x","meshgrid",e instanceof io?e.dtype:"float32");if(void 0===t)return[r];let a=Bo(t,"y","meshgrid",t instanceof io?t.dtype:"float32");const o=ee(r.shape),s=ee(a.shape);return"xy"===n?(r=Xl(r,[1,-1]),a=Xl(a,[-1,1]),[ku(zp([s,1],r.dtype),r),ku(a,zp([1,o],a.dtype))]):(r=Xl(r,[-1,1]),a=Xl(a,[1,-1]),[ku(r,zp([1,s],r.dtype)),ku(zp([o,1],a.dtype),a)])}const Vp=jo({minimum_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","minimum"),r=Bo(t,"b","minimum");[n,r]=xo(n,r),"bool"===n.dtype&&(n=Ks(n,"int32"),r=Ks(r,"int32")),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(Ln,a)}});const Up=jo({mirrorPad_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){X("reflect"===n||"symmetric"===n,(()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${n}.`));const r=Bo(e,"x","mirrorPad");if(0===r.rank)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");X(t.length===r.rank,(()=>`Padding doesn't match input. Must be ${r.rank}. Got ${t.length}.`));const a="reflect"===n?1:0;for(let e=0;e<r.rank;e++)X(2===t[e].length,(()=>"Invalid number of paddings. Must be length of 2 each.")),X(t[e][0]>=0&&t[e][0]<=r.shape[e]-a&&t[e][1]>=0&&t[e][1]<=r.shape[e]-a,(()=>`Padding in dimension ${e} cannot be greater than or equal to ${r.shape[e]-a} or less than 0 for input of shape ${r.shape}`));const o={paddings:t,mode:n},s={x:r};return Mo.runKernel(zn,s,o)}});const jp=jo({mod_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","mod"),r=Bo(t,"b","mod");[n,r]=xo(n,r);const a={a:n,b:r};return Mo.runKernel(Bn,a)}});const Wp=jo({moments_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){const r=pe(t,(e=Bo(e,"x","moments")).shape),a=Pp(e,r,n);let o=a.shape;n||(o=Gc(a.shape,r));const s=Si(Wi(Ks(e,"float32"),Xl(a,o)));return{mean:a,variance:Pp(s,r,n)}}});const Hp=jo({multiRNNCell_:function(e,t,n,r){const a=Bo(t,"data","multiRNNCell"),o=Vo(n,"c","multiRNNCell"),s=Vo(r,"h","multiRNNCell");let i=a;const u=[];for(let t=0;t<e.length;t++){const n=e[t](i,o[t],s[t]);u.push(n[0]),u.push(n[1]),i=n[1]}const l=[],c=[];for(let e=0;e<u.length;e+=2)l.push(u[e]),c.push(u[e+1]);return[l,c]}});const qp=jo({multinomial_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=!1){const a=Bo(e,"logits","multinomial"),o=a.size,s=a.rank;if(o<2)throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${o}.`);if(s>2)throw new Error(`Rank of probabilities must be 1 or 2, but is ${s}`);n=n||Math.random();const i={logits:1===s?Xl(a,[1,-1]):a},u={numSamples:t,seed:n,normalized:r},l=Mo.runKernel(Vn,i,u);return 1===s?Xl(l,[l.size]):l}});const Gp=jo({notEqual_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","notEqual","string_or_numeric"),r=Bo(t,"b","notEqual","string_or_numeric");[n,r]=xo(n,r),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(Wn,a)}});const Kp=jo({onesLike_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","onesLike")};return Mo.runKernel(Kn,t)}});const Qp=jo({outerProduct_:function(e,t){const n=Bo(e,"v1","outerProduct"),r=Bo(t,"v2","outerProduct");X(1===n.rank&&1===r.rank,(()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${n.rank} and ${r.rank}.`));const a=Xl(n,[-1,1]),o=Xl(r,[1,-1]);return ku(a,o)}});const Yp=jo({pad_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=0){const r=Bo(e,"x","pad");if(0===r.rank)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");const a={paddings:t,constantValue:n},o={x:r};return Mo.runKernel(Xn,o,a)}});const Xp=jo({pad1d_:function(e,t,n=0){return X(2===t.length,(()=>"Invalid number of paddings. Must be length of 2.")),Yp(e,[t],n)}});const Zp=jo({pad2d_:function(e,t,n=0){return X(2===t.length&&2===t[0].length&&2===t[1].length,(()=>"Invalid number of paddings. Must be length of 2 each.")),Yp(e,t,n)}});const Jp=jo({pad3d_:function(e,t,n=0){return X(3===t.length&&2===t[0].length&&2===t[1].length&&2===t[2].length,(()=>"Invalid number of paddings. Must be length of 2 each.")),Yp(e,t,n)}});const ed=jo({pad4d_:function(e,t,n=0){return X(4===t.length&&2===t[0].length&&2===t[1].length&&2===t[2].length&&2===t[3].length,(()=>"Invalid number of paddings. Must be length of 2 each.")),Yp(e,t,n)}});const td=jo({spaceToBatchND_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","spaceToBatchND");X(r.rank>=1+t.length,(()=>`input rank ${r.rank} should be > than [blockShape] ${t.length}`)),X(n.length===t.length,(()=>`paddings.shape[0] ${n.length} must be equal to [blockShape] ${t.length}`)),X(r.shape.reduce(((e,r,a)=>a>0&&a<=t.length?e&&(r+n[a-1][0]+n[a-1][1])%t[a-1]==0:e),!0),(()=>`input spatial dimensions ${r.shape.slice(1)} with paddings ${n.toString()} must be divisible by blockShapes ${t.toString()}`));const a={x:r},o={blockShape:t,paddings:n};return Mo.runKernel(Or,a,o)}});const nd=jo({pool_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o,s){null==a&&(a=[1,1]),null==o&&(o=1),0===r&&(r="valid");const i=Bo(e,"x","maxPool");let u=i,l=!1;3===i.rank&&(l=!0,u=Xl(i,[1,i.shape[0],i.shape[1],i.shape[2]])),X(Gl(o,a),(()=>`Error in pool: Either strides or dilations must be 1. Got strides ${o} and dilations '${a}'`));const c=Pl(u.shape,t,o,a,r),p=[c.dilationHeight,c.dilationWidth];let d;d="same"===r?function(e,t){const n=e.map(((e,n)=>e+(e-1)*(t[n]-1))),r=n.map((e=>e-1)),a=r.map((e=>Math.floor(e/2))),o=r.map(((e,t)=>e-a[t]));return r.map(((e,t)=>[a[t],o[t]]))}([c.filterHeight,c.filterWidth],p):[[0,0],[0,0]];const f=1===p[0]&&1===p[1],[h,m]=function(e,t,n){const r=n.map((e=>e[0])),a=n.map((e=>e[1])),o=e.concat(r,a),s=t.map(((e,t)=>(e-o[t]%e)%e)),i=a.map(((e,t)=>e+s[t])),u=t.map(((e,t)=>[r[t],i[t]])),l=t.map(((e,t)=>[0,s[t]]));return[u,l]}([c.inHeight,c.inWidth],p,d),g=f?r:"valid",y=f?u:td(u,p,h),b=("avg"===n?()=>Zl(y,t,o,g,s):()=>$p(y,t,o,g,s))(),v=f?b:oc(b,p,m);return l?Xl(v,[v.shape[1],v.shape[2],v.shape[3]]):v}});const rd=jo({prelu_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n={x:Bo(e,"x","prelu"),alpha:Bo(t,"alpha","prelu")};return Mo.runKernel(er,n)}});const ad=jo({prod_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=null,n=!1){let r=Bo(e,"x","prod");"bool"===r.dtype&&(r=Ks(r,"int32"));const a={x:r},o={axis:t,keepDims:n};return Mo.runKernel(tr,a,o)}});const od=jo({raggedGather_:
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r){const a={paramsNestedSplits:e.map(((e,t)=>Bo(e,`tensors${t}`,"raggedGather","int32"))),paramsDenseValues:Bo(t,"paramsDenseValues","raggedGather"),indices:Bo(n,"indices","raggedGather","int32")},o={outputRaggedRank:r},s=Mo.runKernel(nr,a,o);return{outputNestedSplits:s.slice(0,s.length-1),outputDenseValues:s[s.length-1]}}});const sd=jo({raggedRange_:
/**
* @license
* Copyright 2022 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"starts","raggedRange"),a={starts:r,limits:Bo(t,"limits","raggedRange",r.dtype),deltas:Bo(n,"deltas","raggedRange",r.dtype)},o=Mo.runKernel(rr,a);return{rtNestedSplits:o[0],rtDenseValues:o[1]}}});const id=jo({raggedTensorToTensor_:
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a){const o=Bo(e,"shape","raggedTensorToTensor","int32"),s=Bo(t,"values","raggedTensorToTensor"),i={shape:o,values:s,defaultValue:Bo(n,"defaultValue","raggedTensorToTensor",s.dtype),rowPartitionTensors:r.map(((e,t)=>Bo(e,`tensors${t}`,"raggedTensorToTensor","int32")))},u={rowPartitionTypes:a};return Mo.runKernel(ar,i,u)}});const ud=jo({rand_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){Ce(e);const r=ee(e);let a=null;if(null==n||"float32"===n)a=new Float32Array(r);else if("int32"===n)a=new Int32Array(r);else{if("bool"!==n)throw new Error(`Unknown data type ${n}`);a=new Uint8Array(r)}for(let e=0;e<r;e++)a[e]=t();return Mo.makeTensor(a,e,n)}});var ld=n(6377);
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class cd{constructor(e,t,n,r,a){this.mean=e,this.stdDev=t,this.dtype=n,this.nextVal=NaN,this.truncated=r,this.truncated&&(this.upper=this.mean+2*this.stdDev,this.lower=this.mean-2*this.stdDev);const o=a||Math.random();this.random=ld.alea(o.toString())}nextValue(){if(!isNaN(this.nextVal)){const e=this.nextVal;return this.nextVal=NaN,e}let e,t,n=!1;for(;!n;){let r,a,o;do{r=2*this.random()-1,a=2*this.random()-1,o=r*r+a*a}while(o>=1||0===o);const s=Math.sqrt(-2*Math.log(o)/o);e=this.mean+this.stdDev*r*s,t=this.mean+this.stdDev*a*s,this.truncated&&!this.isValidTruncated(e)||(n=!0)}return this.truncated&&!this.isValidTruncated(t)||(this.nextVal=this.convertValue(t)),this.convertValue(e)}convertValue(e){return null==this.dtype||"float32"===this.dtype?e:Math.round(e)}isValidTruncated(e){return e<=this.upper&&e>=this.lower}}class pd{constructor(e,t,n,r){this.alpha=e,this.beta=1/t,this.dtype=n;const a=r||Math.random();this.randu=ld.alea(a.toString()),this.randn=new cd(0,1,n,!1,this.randu()),this.d=e<1?e+2/3:e-1/3,this.c=1/Math.sqrt(9*this.d)}nextValue(){let e,t,n,r,a,o;for(;;){do{r=this.randn.nextValue(),o=1+this.c*r}while(o<=0);if(o*=o*o,e=r*r,t=1-.331*e*e,n=.5*e+this.d*(1-o+Math.log(o)),a=this.randu(),a<t||Math.log(a)<n)break}return o=1/this.beta*this.d*o,this.alpha<1&&(o*=Math.pow(this.randu(),1/this.alpha)),this.convertValue(o)}convertValue(e){return"float32"===this.dtype?e:Math.round(e)}}class dd{constructor(e=0,t=1,n,r){if(this.canReturnFloat=()=>null==this.dtype||"float32"===this.dtype,this.min=e,this.range=t-e,this.dtype=n,null==r&&(r=Math.random()),"number"==typeof r&&(r=r.toString()),!this.canReturnFloat()&&this.range<=1)throw new Error(`The difference between ${e} - ${t} <= 1 and dtype is not float`);this.random=ld.alea(r)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}}const fd=jo({randomGamma_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=1,r="float32",a){if(Ce(e),null==n&&(n=1),null==r&&(r="float32"),"float32"!==r&&"int32"!==r)throw new Error(`Unsupported data type ${r}`);const o=new pd(t,n,r,a),s=Gs(e,r);for(let e=0;e<s.values.length;e++)s.values[e]=o.nextValue();return s.toTensor()}});const hd=jo({randomNormal_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0,n=1,r,a){if(Ce(e),null!=r&&"bool"===r)throw new Error(`Unsupported data type ${r}`);const o=new cd(t,n,r,!1,a),s=Gs(e,r);for(let e=0;e<s.values.length;e++)s.values[e]=o.nextValue();return s.toTensor()}});const md=jo({randomStandardNormal_:
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){if(null!=t&&"bool"===t)throw new Error(`Unsupported data type ${t}`);return hd(e,0,1,t,n)}});const gd=jo({randomUniform_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0,n=1,r="float32",a){Ce(e);const o=Gs(e,r),s=new dd(t,n,null,a);for(let e=0;e<o.values.length;e++)o.values[e]=s.nextValue();return o.toTensor()}});const yd=jo({randomUniformInt_:
/**
* @license
* Copyright 2023 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r){return gd(e,t,n,"int32",r)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function bd(e,t,n=1,r="float32"){if(0===n)throw new Error("Cannot have a step of zero");const a={start:e,stop:t,step:n,dtype:r};return Mo.runKernel(or,{},a)}const vd=jo({reciprocal_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","reciprocal")};return Mo.runKernel(ir,t)}});const wd=jo({relu_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","relu")};return Mo.runKernel(ur,t)}});const xd=jo({relu6_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","relu6")};return Mo.runKernel(hr,t)}});const kd=jo({reverse_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n={x:Bo(e,"x","reverse")},r={dims:t};return Mo.runKernel(mr,n,r)}});const Sd=jo({reverse1d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=Bo(e,"x","reverse");return X(1===t.rank,(()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`)),kd(t,0)}});const Ed=jo({reverse2d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","reverse");return X(2===n.rank,(()=>`Error in reverse2D: x must be rank 2 but got rank ${n.rank}.`)),kd(n,t)}});const Nd=jo({reverse3d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","reverse");return X(3===n.rank,(()=>`Error in reverse3D: x must be rank 3 but got rank ${n.rank}.`)),kd(n,t)}});const Td=jo({reverse4d_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","reverse");return X(4===n.rank,(()=>`Error in reverse4D: x must be rank 4 but got rank ${n.rank}.`)),kd(n,t)}});const _d=jo({round_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","round")};return Mo.runKernel(gr,t)}});const Ad=jo({rsqrt_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","rsqrt","float32")};return Mo.runKernel(yr,t)}});const Id=jo({selu_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","selu")};return Mo.runKernel(kr,t)}});const Md=jo({separableConv2d_:function(e,t,n,r,a,o=[1,1],s="NHWC"){const i=Bo(e,"x","separableConv2d"),u=Bo(t,"depthwiseFilter","separableConv2d"),l=Bo(n,"pointwiseFilter","separableConv2d");let c=i,p=!1;if(3===i.rank&&(p=!0,c=Xl(i,[1,i.shape[0],i.shape[1],i.shape[2]])),"NCHW"===s)throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");X(4===c.rank,(()=>`Error in separableConv2d: input must be rank 4, but got rank ${c.rank}.`)),X(4===u.rank,(()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${u.rank}.`)),X(4===l.rank,(()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${u.rank}.`)),X(1===l.shape[0],(()=>`Error in separableConv2d: the first dimension of pointwise filter must be 1, but got ${l.shape[0]}.`)),X(1===l.shape[1],(()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${l.shape[1]}.`));const d=u.shape[2],f=u.shape[3];X(l.shape[2]===d*f,(()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${d*f}, but got ${l.shape[2]}.`));const h=Cc(c,u,r,a,s,o),m=wc(h,l,1,"valid",s);return p?Xl(m,[m.shape[1],m.shape[2],m.shape[3]]):m}});const Od=
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function(e,t){const n=Bo(e,"x","setdiff1d"),r=Bo(t,"y","setdiff1d");X(n.dtype===r.dtype,(()=>`x and y should have the same dtype, but got x (${n.dtype}) and y (${r.dtype}).`)),X(1===n.rank,(()=>`x should be 1D tensor, but got x (${n.shape}).`)),X(1===r.rank,(()=>`y should be 1D tensor, but got y (${r.shape}).`));const a=await n.data(),o=await r.data(),s=new Set(o);let i=0;for(let e=0;e<a.length;e++)s.has(a[e])||i++;const u=new ro([i],n.dtype),l=new ro([i],"int32");for(let e=0,t=0;e<a.length;e++)s.has(a[e])||(u.values[t]=a[e],l.values[t]=e,t++);return[u.toTensor(),l.toTensor()]};const Dd=jo({sign_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","sign")};return Mo.runKernel(Tr,t)}});const Cd=jo({sin_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","sin","float32")};return Mo.runKernel(Er,t)}});const $d=jo({sinh_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","sinh")};return Mo.runKernel(Nr,t)}});const Rd=jo({slice1d_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","slice1d");return X(1===r.rank,(()=>`slice1d expects a rank-1 tensor, but got a rank-${r.rank} tensor`)),nc(r,[t],[n])}});const Fd=jo({slice2d_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","slice2d");return X(2===r.rank,(()=>`slice2d expects a rank-2 tensor, but got a rank-${r.rank} tensor`)),nc(r,t,n)}});const Pd=jo({slice3d_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","slice3d");return X(3===r.rank,(()=>`slice3d expects a rank-3 tensor, but got a rank-${r.rank} tensor`)),nc(r,t,n)}});const Ld=jo({slice4d_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","slice4d");return X(4===r.rank,(()=>`slice4d expects a rank-4 tensor, but got a rank-${r.rank} tensor`)),nc(r,t,n)}});const zd=jo({softmax_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=-1){const n=Bo(e,"logits","softmax","float32");if(-1===t&&(t=n.rank-1),t!==n.rank-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and dim was ${t}`);const r={logits:n},a={dim:t};return Mo.runKernel(Cr,r,a)}});const Bd=jo({fft_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){X("complex64"===e.dtype,(()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`));const t={input:e};return Mo.runKernel(Xt,t)}});const Vd=jo({ifft_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){X("complex64"===e.dtype,(()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`));const t={input:e};return Mo.runKernel(ln,t)}});const Ud=jo({irfft_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=e.shape[e.shape.length-1],n=e.size/t;let r;if(t<=2){const a=Xl(e,[n,t]);r=Vd(a)}else{const a=[n,2*(t-1)],o=Xl(Tu(e),[n,t]),s=Xl(Eu(e),[n,t]),i=kd(nc(o,[0,1],[n,t-2]),1),u=xi(kd(nc(s,[0,1],[n,t-2]),1),Di(-1)),l=ec([o,i],1),c=ec([s,u],1),p=Xl(Wo(l,c),[a[0],a[1]]);r=Vd(p)}if(r=Tu(r),3===e.rank&&0!==e.shape[0]){const t=r,n=e.shape[0];r=Xl(r,[n,r.shape[0]/n,r.shape[1]]),t.dispose()}return r}});const jd=jo({split_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=0){const r={x:Bo(e,"x","split")},a={numOrSizeSplits:t,axis:n};return Mo.runKernel(Dr,r,a)}});const Wd=jo({rfft_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){X("float32"===e.dtype,(()=>`The dtype for rfft() must be real value but got ${e.dtype}`));let n=e.shape[e.shape.length-1];const r=e.size/n;let a;if(null!=t&&t<n){const r=e.shape.map((e=>0)),o=e.shape.map((e=>e));o[e.shape.length-1]=t,a=nc(e,r,o),n=t}else if(null!=t&&t>n){const r=e.shape.map((e=>e));r[e.shape.length-1]=t-n,a=ec([e,Lp(r)],e.shape.length-1),n=t}else a=e;const o=Ei(a),s=Xl(Wo(a,o),[r,n]),i=Bd(s),u=Math.floor(n/2)+1,l=Tu(i),c=Eu(i),p=jd(l,[u,n-u],l.shape.length-1),d=jd(c,[u,n-u],c.shape.length-1),f=a.shape.slice();return f[a.shape.length-1]=u,Xl(Wo(p[0],d[0]),f)}});const Hd=jo({squaredDifference_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){let n=Bo(e,"a","squaredDifference"),r=Bo(t,"b","squaredDifference");[n,r]=xo(n,r),Qi(n.shape,r.shape);const a={a:n,b:r};return Mo.runKernel(zr,a,{})}});const qd=jo({squeeze_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"x","squeeze","string_or_numeric");return Xl(n,de(n.shape,t).newShape)}});const Gd=jo({stack_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){const n=Vo(e,"tensors","stack","string_or_numeric");X(n.length>=1,(()=>"Pass at least one tensor to tf.stack")),n.length>0&&X(t<=n[0].rank,(()=>"Axis must be <= rank of the tensor"));const r=n,a={axis:t};return Mo.runKernel(Yn,r,a)}});const Kd=jo({step_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){const n={x:Bo(e,"x","step")},r={alpha:t};return Mo.runKernel(aa,n,r)}});const Qd=jo({stridedSlice_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a=0,o=0,s=0,i=0,u=0){const l={x:Bo(e,"x","stridedSlice","string_or_numeric")},c={begin:t,end:n,strides:r,beginMask:a,endMask:o,ellipsisMask:s,newAxisMask:i,shrinkAxisMask:u};return Mo.runKernel(Ur,l,c)}});const Yd=jo({tan_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t={x:Bo(e,"x","tan","float32")};return Mo.runKernel(Gr,t)}});
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Xd(e,t){J(e);const n=Po(e,t);if(1!==n.length)throw new Error("tensor1d() requires values to be a flat/TypedArray");return Ho(e,null,n,t)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Zd(e,t,n){if(J(e),null!=t&&2!==t.length)throw new Error("tensor2d() requires shape to have two numbers");const r=Po(e,n);if(2!==r.length&&1!==r.length)throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");if(1===r.length&&null==t)throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");return Ho(e,t,r,n)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Jd(e,t,n){if(J(e),null!=t&&4!==t.length)throw new Error("tensor4d() requires shape to have four numbers");const r=Po(e,n);if(4!==r.length&&1!==r.length)throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");if(1===r.length&&null==t)throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");return Ho(e,t,r,n)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function ef(e,t,n){if(J(e),null!=t&&5!==t.length)throw new Error("tensor5d() requires shape to have five numbers");const r=Po(e,n);if(5!==r.length&&1!==r.length)throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");if(1===r.length&&null==t)throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");return Ho(e,t,r,n)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function tf(e,t,n){if(J(e),null!=t&&6!==t.length)throw new Error("tensor6d() requires shape to have six numbers");const r=Po(e,n);if(6!==r.length&&1!==r.length)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(1===r.length&&null==t)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return Ho(e,t=t||r,r,n)}const nf=jo({tensorScatterUpdate_:
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"tensor","tensorScatterupdate"),a=Bo(t,"indices","tensorScatterupdate","int32"),o=Bo(n,"updates","tensorScatterupdate");if(Vu(o,a,r.shape),r.dtype!==o.dtype)throw new Error(`tensor and updates must have the same dtype, instead they are ${r.dtype} and ${o.dtype}.`);const s={tensor:r,indices:a,updates:o};return Mo.runKernel(vr,s,{})}});const rf=jo({topk_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=1,n=!0){const r=Bo(e,"x","topk");if(0===r.rank)throw new Error("topk() expects the input to be of rank 1 or higher");const a=r.shape[r.shape.length-1];if(t<0)throw new Error(`'k' passed to topk() must be >= 0 but got ${t}`);if(t>a)throw new Error(`'k' passed to topk() must be <= the last dimension (${a}) but got ${t}`);const o={x:r},s={k:t,sorted:n},[i,u]=Mo.runKernel(Yr,o,s);return{values:i,indices:u}}});const af=jo({truncatedNormal_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0,n=1,r,a){if(Ce(e),null!=r&&"bool"===r)throw new Error("Unsupported data type $ { dtype }");const o=new cd(t,n,r,!0,a),s=Gs(e,r);for(let e=0;e<s.values.length;e++)s.values[e]=o.nextValue();return s.toTensor()}});const of=jo({unique_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){const n=Bo(e,"x","unique","string_or_numeric");X(n.rank>0,(()=>"The input tensor must be at least 1D"));const r={x:n},a={axis:t},[o,s]=Mo.runKernel(Jr,r,a);return{values:o,indices:s}}});const sf=jo({unsortedSegmentSum_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"x","unsortedSegmentSum"),a=Bo(t,"segmentIds","unsortedSegmentSum","int32");X(ae(n),(()=>"numSegments must be of dtype int"));const o={x:r,segmentIds:a},s={numSegments:n};return Mo.runKernel(ta,o,s)}});const uf=jo({unstack_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=0){const n=Bo(e,"x","unstack","string_or_numeric");X(t>=-n.shape.length&&t<n.shape.length,(()=>`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`));const r={value:n},a={axis:t};return Mo.runKernel(ea,r,a)}});
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function lf(e,t){return Dp(e,t,"right")}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function cf(e,t=!0,n,r){return Mo.makeVariable(e,t,n,r)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function pf(e,t){const n=[];for(let e=0;e<t.length;e++)t[e]&&n.push(e);const r=Gs(e,"int32"),a=Gs([n.length,e.length],"int32");for(let t=0;t<n.length;t++){const o=r.indexToLoc(n[t]),s=t*e.length;a.values.set(o,s)}return a.toTensor()}const df=
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function(e){const t=Bo(e,"condition","whereAsync","bool"),n=await t.data(),r=pf(t.shape,n);return e!==t&&t.dispose(),r};const ff=
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function(e,t,n){const r=Bo(e,"tensor","boolMask"),a=Bo(t,"mask","boolMask","bool"),o=null==n?0:n,s=a.rank,i=r.shape;X(s>0,(()=>"mask cannot be scalar")),Z(i.slice(o,o+s),a.shape,"mask's shape must match the first K dimensions of tensor's shape,");let u=1;for(let e=o;e<o+s;e++)u*=i[e];const l=i.slice(0,o).concat([u],i.slice(o+s)),c=Xl(r,l),p=Xl(a,[-1]),d=await df(p),f=qd(d,[1]),h=cp(c,f,o);return e!==r&&r.dispose(),t!==a&&a.dispose(),f.dispose(),c.dispose(),p.dispose(),d.dispose(),h};const hf=jo({movingAverage_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a=!0){const o=Bo(e,"v","movingAverage"),s=Bo(t,"x","movingAverage"),i=Bo(n,"decay","movingAverage");ko(o,s),X(re(o.shape,s.shape),(()=>"Shape mismatch in v and x"));const u=Di(1),l=Wi(u,i);let c=xi(Wi(s,o),l);if(a){X(null!=r,(()=>"When using zeroDebias: true, step is required."));const e=Bo(r,"step","movingAverage");c=wi(c,Wi(u,ji(i,e)))}return bi(o,c)}});const mf=jo({scatterND_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){Ce(n);const r=Bo(e,"indices","scatterND","int32"),a=Bo(t,"updates","scatterND");Vu(a,r,n);const o={indices:r,updates:a},s={shape:n};return Mo.runKernel(br,o,s)}});const gf=jo({sparseToDense_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=0){Ce(n);const a=Bo(e,"sparseIndices","sparseToDense","int32"),o=Bo(t,"sparseValues","sparseToDense","string_or_numeric"),s=Bo(r,"defaultValue","sparseToDense",o.dtype);!function(e,t,n,r){if("int32"!==e.dtype)throw new Error(`tf.sparseToDense() expects the indices to be int32 type, but the dtype was ${e.dtype}.`);if(e.rank>2)throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${e.shape}.`);const a=e.rank>0?e.shape[0]:1,o=e.rank>1?e.shape[1]:1;if(n.length!==o)throw new Error(`outputShape has incorrect number of elements:, ${n.length}, should be: ${o}.`);const s=t.size;if(0!==t.rank&&(1!==t.rank||s!==a))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${a}]`);if(t.dtype!==r.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}(a,o,n,s);const i={sparseIndices:a,sparseValues:o,defaultValue:s},u={outputShape:n};return Mo.runKernel(Lr,i,u)}});const yf=jo({gatherND_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(t,"indices","gatherND","int32"),r={params:Bo(e,"x","gatherND","string_or_numeric"),indices:n};return Mo.runKernel(an,r)}});const bf=jo({dropout_:
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r){const a=Bo(e,"x","dropout");if(X("float32"===a.dtype,(()=>`x has to be a floating point tensor since it's going to be scaled, but got a ${a.dtype} tensor instead.`)),X(t>=0&&t<1,(()=>`rate must be a float in the range [0, 1), but got ${t}.`)),0===t)return e instanceof io?a.clone():a;const o=
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){if(null==t)return e.shape.slice();if(re(e.shape,t))return t;if(e.shape.length===t.length){const n=[];for(let r=0;r<e.shape.length;r++)null==t[r]&&null!=e.shape[r]?n.push(e.shape[r]):n.push(t[r]);return n}return t}(a,n),s=1-t,i=wi(lp(bi(gd(o,0,1,"float32",r),s)),s);return xi(a,i)}});
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function vf(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function wf(e,t,n){const r=1-e%2,a=new Float32Array(e);for(let o=0;o<e;++o){const s=2*Math.PI*o/(e+r-1);a[o]=t-n*Math.cos(s)}return Xd(a,"float32")}const xf=
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function(e,t,n=1){const r=Bo(e,"predictions","inTopK"),a=Bo(t,"targets","inTopK");X(r.rank>1,(()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${r.rank}`)),X(r.rank-1===a.rank,(()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${r.rank} and targets rank ${a.rank}`)),Z(r.shape.slice(0,r.shape.length-1),a.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");const o=r.shape[r.shape.length-1];X(n>0&&n<=o,(()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${o}), but got ${n}`));const s=await r.data(),i=await a.data(),[u,l]=[s.length/o,o],c=fe("bool",u);for(let e=0;e<u;e++){const t=e*l,r=s.subarray(t,t+l),a=[];for(let e=0;e<r.length;e++)a.push({value:r[e],index:e});a.sort(((e,t)=>t.value-e.value)),c[e]=0;for(let t=0;t<n;t++)if(a[t].index===i[e]){c[e]=1;break}}return e!==r&&r.dispose(),t!==a&&a.dispose(),qo(c,a.shape,"bool")};const kf=jo({conv2DBackpropFilter_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o="NHWC",s){let i=e;3===e.rank&&(i=Xl(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let u=t;3===u.rank&&(u=Xl(t,[1,t.shape[0],t.shape[1],t.shape[2]])),X(4===i.rank,(()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${i.shape}.`)),X(4===u.rank,(()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${u.shape}.`)),X(4===n.length,(()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`));const l="NHWC"===o?i.shape[3]:i.shape[1],c="NHWC"===o?u.shape[3]:u.shape[1];X(l===n[2],(()=>`Error in conv2dDerFilter: depth of input ${l}) must match input depth in filter (${n[2]}.`)),X(c===n[3],(()=>`Error in conv2dDerFilter: depth of dy (${c}) must match output depth for filter (${n[3]}).`)),Yl("conv2dDerFilter",a,s);const p={x:i,dy:u},d={strides:r,pad:a,dataFormat:o,dimRoundingMode:s,filterShape:n};return Mo.runKernel(kt,p,d)}});
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Sf(e,t,n){if(null==n||"linear"===n)return e;if("relu"===n)return xi(e,Kd(t));throw new Error(`Cannot compute gradient for fused activation ${n}.`)}function Ef(e,t){let n=t;const r=Ki(e.shape,t.shape);return r.length>0&&(n=ep(n,r)),Xl(n,e.shape)}function Nf(e,t,n,r){if("linear"===t)return e;if("relu"===t)return wd(e);if("elu"===t)return Vc(e);if("relu6"===t)return xd(e);if("prelu"===t)return rd(e,n);if("leakyrelu"===t)return gp(e,r);if("sigmoid"===t)return tc(e);throw new Error(`Unknown fused activation ${t}.`)}const Tf=(e,t)=>!(e>0)||"linear"===t;const _f=jo({fusedConv2d_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function({x:e,filter:t,strides:n,pad:r,dataFormat:a="NHWC",dilations:o=[1,1],dimRoundingMode:s,bias:i,activation:u="linear",preluActivationWeights:l,leakyreluAlpha:c}){if(u=u||"linear",!1===Tf(Mo.state.gradientDepth,u)){X("NHWC"===a,(()=>`Error in fused conv2d: got dataFormat of ${a} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`));let p=wc(e,t,n,r,a,o,s);return null!=i&&(p=bi(p,i)),Nf(p,u,l,c)}const p=Bo(e,"x","conv2d","float32"),d=Bo(t,"filter","conv2d","float32");let f=p,h=!1;3===p.rank&&(h=!0,f=Xl(p,[1,p.shape[0],p.shape[1],p.shape[2]])),X(4===f.rank,(()=>`Error in fused conv2d: input must be rank 4, but got rank ${f.rank}.`)),X(4===d.rank,(()=>`Error in fused conv2d: filter must be rank 4, but got rank ${d.rank}.`)),Yl("fused conv2d",r,s);const m="NHWC"===a?f.shape[3]:f.shape[1];X(d.shape[2]===m,(()=>`Error in conv2d: depth of input (${m}) must match input depth for filter ${d.shape[2]}.`)),X(Gl(n,o),(()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`));const g=zl(f.shape,d.shape,n,o,r,s);let y,b;if(null!=i&&(y=Bo(i,"bias","fused conv2d"),[y]=xo(y,p),"NHWC"===a?Qi(g.outShape,y.shape):(X(y.shape.length<=1,(()=>`Error in fused conv2d: only supports scalar or 1-D Tensor bias for NCHW format but got the bias of rank-${y.shape.length}.`)),X(0===y.shape.length||y.shape[0]===g.outChannels||1===y.shape[0],(()=>`Error in fused conv2d: bias shape (${y.shape}) is not compatible with the number of output channels (${g.outChannels})`)))),null!=l){const e=l.shape;if(X(e.length<=1||3===e.length,(()=>`Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${e.length}.`)),1===e.length)X(1===e[0]||e[0]===g.outChannels,(()=>`Error in fused conv2d: PReLU activation weights (${e}) is not compatible with the number of output channels (${g.outChannels}).`));else if(3===e.length)try{Qi(e,g.outShape)}catch(t){const n=`Error in fused conv2d: PReLU activation weights (${e}) is not compatible with the output shape of the conv2d (${g.outShape}).`;throw Error(n)}b=Bo(l,"prelu weights","fused conv2d")}const v=(e,t)=>{X("NHWC"===a,(()=>`Error in gradient of fused conv2D: got dataFormat of ${a} but only NHWC is currently supported.`));const[s,i,l,c]=t,p=Sf(e,l,u);X(ql(o),(()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${o}'`));const d=[kc(i.shape,p,s,n,r),kf(i,p,s.shape,n,r)];if(null!=c){const e=Ef(c,p);d.push(e)}return d},w={x:f,filter:d,bias:y,preluActivationWeights:b},x={strides:n,pad:r,dataFormat:a,dilations:o,dimRoundingMode:s,activation:u,leakyreluAlpha:c};if(null==i){const e=Mi(((e,t,n)=>{let r=Mo.runKernel(ua,w,x);return n([t,e,r]),h&&(r=Xl(r,[r.shape[1],r.shape[2],r.shape[3]])),{value:r,gradFunc:v}}));return e(f,d)}{const e=Mi(((e,t,n,r)=>{let a=Mo.runKernel(ua,w,x);return r([t,e,a,n]),h&&(a=Xl(a,[a.shape[1],a.shape[2],a.shape[3]])),{value:a,gradFunc:v}}));return e(f,d,y)}}});const Af=jo({depthwiseConv2dNativeBackpropFilter_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o=[1,1],s){let i=e;3===e.rank&&(i=Xl(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let u=t;3===u.rank&&(u=Xl(t,[1,t.shape[0],t.shape[1],t.shape[2]]));const l={x:i,dy:u},c={strides:r,pad:a,dimRoundingMode:s,dilations:o,filterShape:n};return Mo.runKernel(Rt,l,c)}});const If=jo({depthwiseConv2dNativeBackpropInput_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o=[1,1],s){let i=t,u=!1;3===t.rank&&(u=!0,i=Xl(t,[1,t.shape[0],t.shape[1],t.shape[2]]));const l={dy:i,filter:n},c={strides:r,pad:a,dimRoundingMode:s,dilations:o,inputShape:e},p=Mo.runKernel(Ft,l,c);return u?Xl(p,[p.shape[1],p.shape[2],p.shape[3]]):p}});const Mf=jo({fusedDepthwiseConv2d_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function({x:e,filter:t,strides:n,pad:r,dataFormat:a="NHWC",dilations:o=[1,1],dimRoundingMode:s,bias:i,activation:u="linear",preluActivationWeights:l,leakyreluAlpha:c}){if(!1===Tf(Mo.state.gradientDepth,u)){let p=Cc(e,t,n,r,a,o,s);return null!=i&&(p=bi(p,i)),Nf(p,u,l,c)}const p=Bo(e,"x","depthwiseConv2d","float32"),d=Bo(t,"filter","depthwiseConv2d","float32");let f=p,h=!1;3===p.rank&&(h=!0,f=Xl(p,[1,p.shape[0],p.shape[1],p.shape[2]])),X(4===f.rank,(()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${f.rank}.`)),X(4===d.rank,(()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${d.rank}.`)),X(f.shape[3]===d.shape[2],(()=>`Error in fused depthwiseConv2d: number of input channels (${f.shape[3]}) must match the inChannels dimension in filter ${d.shape[2]}.`)),null==o&&(o=[1,1]),X(Gl(n,o),(()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`)),Yl("fused depthwiseConv2d",r,s);const m=zl(f.shape,d.shape,n,o,r,s,!0);let g,y;null!=i&&(g=Bo(i,"bias","fused conv2d"),[g]=xo(g,p),Qi(m.outShape,g.shape)),null!=l&&(y=Bo(l,"prelu weights","fused depthwiseConv2d"));const b=(e,t)=>{X(ql(o),(()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${o}'`));const[a,i,l,c]=t,p=Sf(e,l,u),d=If(i.shape,p,a,n,r,o,s),f=Af(i,p,a.shape,n,r,o,s);if(null!=c){return[d,f,Ef(g,p)]}return[d,f]},v={x:f,filter:d,bias:g,preluActivationWeights:y},w={strides:n,pad:r,dataFormat:a,dilations:o,dimRoundingMode:s,activation:u,leakyreluAlpha:c};if(null==i){const e=Mi(((e,t,n)=>{let r=Mo.runKernel(la,v,w);return n([t,e,r]),h&&(r=Xl(r,[r.shape[1],r.shape[2],r.shape[3]])),{value:r,gradFunc:b}}));return e(f,d)}{const e=Mi(((e,t,n,r)=>{let a=Mo.runKernel(la,v,w);return r([t,e,a,n]),h&&(a=Xl(a,[a.shape[1],a.shape[2],a.shape[3]])),{value:a,gradFunc:b}}));return e(f,d,g)}}});const Of=jo({fusedMatMul_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function({a:e,b:t,transposeA:n=!1,transposeB:r=!1,bias:a,activation:o="linear",preluActivationWeights:s,leakyreluAlpha:i=.2}){if(!1===Tf(Mo.state.gradientDepth,o)){let u=ku(e,t,n,r);return null!=a&&(u=bi(u,a)),Nf(u,o,s,i)}let u=Bo(e,"a","fused matMul"),l=Bo(t,"b","fused matMul");[u,l]=xo(u,l);const c=n?u.shape[u.rank-2]:u.shape[u.rank-1],p=r?l.shape[l.rank-1]:l.shape[l.rank-2],d=n?u.shape[u.rank-1]:u.shape[u.rank-2],f=r?l.shape[l.rank-2]:l.shape[l.rank-1],h=u.shape.slice(0,-2),m=l.shape.slice(0,-2),g=ee(h),y=ee(m);X(c===p,(()=>`Error in fused matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${u.shape} and ${l.shape} and transposeA=${n} and transposeB=${r} must match.`));const b=Qi(u.shape.slice(0,-2),l.shape.slice(0,-2)).concat([d,f]),v=Xl(u,n?[g,c,d]:[g,d,c]),w=Xl(l,r?[y,f,p]:[y,p,f]);let x,k;null!=a&&(x=Bo(a,"bias","fused matMul"),[x]=xo(x,u),Qi(b,x.shape)),null!=s&&(k=Bo(s,"prelu weights","fused matMul"));const S=(e,t)=>{const[s,i,u,l]=t,c=Sf(Xl(e,u.shape),u,o);let p,d;if(n||r?!n&&r?(p=ku(c,i,!1,!1),d=ku(c,s,!0,!1)):n&&!r?(p=ku(i,c,!1,!0),d=ku(s,c,!1,!1)):(p=ku(i,c,!0,!0),d=ku(c,s,!0,!0)):(p=ku(c,i,!1,!0),d=ku(s,c,!0,!1)),null!=a){return[p,d,Ef(l,c)]}return[p,d]},E={a:v,b:w,bias:x,preluActivationWeights:k},N={transposeA:n,transposeB:r,activation:o,leakyreluAlpha:i};if(null==a){const e=Mi(((e,t,n)=>{const r=Mo.runKernel(ia,E,N);return n([e,t,r]),{value:Xl(r,b),gradFunc:S}}));return e(v,w)}{const e=Mi(((e,t,n,r)=>{const a=Mo.runKernel(ia,E,N);return r([e,t,a,n]),{value:Xl(a,b),gradFunc:S}}));return e(v,w,x)}}});const Df=jo({hammingWindow_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){return wf(e,.54,.46)}});const Cf=jo({hannWindow_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){return wf(e,.5,.5)}});const $f=jo({frame_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=!1,a=0){let o=0;const s=[];for(;o+t<=e.size;)s.push(nc(e,o,t)),o+=n;if(r)for(;o<e.size;){const r=o+t-e.size,i=ec([nc(e,o,t-r),Vi([r],a)]);s.push(i),o+=n}return 0===s.length?Zd([],[0,t]):Xl(ec(s),[s.length,t])}});const Rf=jo({stft_:
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a=Cf){null==r&&(r=vf(t));const o=$f(e,t,n),s=xi(o,a(t));return Wd(s,r)}});const Ff=jo({cropAndResize_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a="bilinear",o=0){const s=Bo(e,"image","cropAndResize"),i=Bo(t,"boxes","cropAndResize","float32"),u=Bo(n,"boxInd","cropAndResize","int32"),l=i.shape[0];X(4===s.rank,(()=>`Error in cropAndResize: image must be rank 4,but got rank ${s.rank}.`)),X(2===i.rank&&4===i.shape[1],(()=>`Error in cropAndResize: boxes must be have size [${l},4] but had shape ${i.shape}.`)),X(1===u.rank&&u.shape[0]===l,(()=>`Error in cropAndResize: boxInd must be have size [${l}] but had shape ${i.shape}.`)),X(2===r.length,(()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${r.length}.`)),X(r[0]>=1&&r[1]>=1,(()=>`cropSize must be atleast [1,1], but was ${r}`)),X("bilinear"===a||"nearest"===a,(()=>`method must be bilinear or nearest, but was ${a}`));const c={image:s,boxes:i,boxInd:u},p={method:a,extrapolationValue:o,cropSize:r};return Mo.runKernel(Ot,c,p)}});const Pf=jo({flipLeftRight_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=Bo(e,"image","flipLeftRight","float32");X(4===t.rank,(()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`));const n={image:t};return Mo.runKernel(Jt,n,{})}});const Lf=jo({grayscaleToRGB_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=Bo(e,"image","grayscaleToRGB"),n=t.rank-1,r=t.shape[n];X(t.rank>=2,(()=>`Error in grayscaleToRGB: images must be at least rank 2, but got rank ${t.rank}.`)),X(1===r,(()=>`Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${r}.`));const a=new Array(t.rank);return a.fill(1,0,n),a[n]=3,ip(t,a)}});const zf=jo({rgbToGrayscale_:
/**
* @license
* Copyright 2023 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){const t=Bo(e,"image","RGBToGrayscale"),n=t.rank-1,r=t.shape[n];X(t.rank>=2,(()=>`Error in RGBToGrayscale: images must be at least rank 2, but got rank ${t.rank}.`)),X(3===r,(()=>`Error in RGBToGrayscale: last dimension of an RGB image should be size 3, but got size ${r}.`));const a=t.dtype,o=Ks(t,"float32"),s=Xd([.2989,.587,.114]);let i;switch(t.rank){case 2:i=Bc("ij,j->i",o,s);break;case 3:i=Bc("ijk,k->ij",o,s);break;case 4:i=Bc("ijkl,l->ijk",o,s);break;case 5:i=Bc("ijklm,m->ijkl",o,s);break;case 6:i=Bc("ijklmn,n->ijklm",o,s);break;default:throw new Error("Not a valid tensor rank.")}return i=op(i,-1),Ks(i,a)}});const Bf=jo({rotateWithOffset_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=0,r=.5){const a=Bo(e,"image","rotateWithOffset","float32");X(4===a.rank,(()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${a.rank}.`));const o={image:a},s={radians:t,fillValue:n,center:r};return Mo.runKernel(sa,o,s)}});
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Vf(e,t,n,r,a,o){null==r&&(r=.5),null==a&&(a=Number.NEGATIVE_INFINITY),null==o&&(o=0);const s=e.shape[0];return n=Math.min(n,s),X(0<=r&&r<=1,(()=>`iouThreshold must be in [0, 1], but was '${r}'`)),X(2===e.rank,(()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`)),X(4===e.shape[1],(()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`)),X(1===t.rank,(()=>"scores must be a 1D tensor")),X(t.shape[0]===s,(()=>`scores has incompatible shape with boxes. Expected ${s}, but was ${t.shape[0]}`)),X(0<=o&&o<=1,(()=>`softNmsSigma must be in [0, 1], but was '${o}'`)),{maxOutputSize:n,iouThreshold:r,scoreThreshold:a,softNmsSigma:o}}const Uf=jo({nonMaxSuppression_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){const o=Bo(e,"boxes","nonMaxSuppression","float32"),s=Bo(t,"scores","nonMaxSuppression","float32"),i=Vf(o,s,n,r,a),u={maxOutputSize:n=i.maxOutputSize,iouThreshold:r=i.iouThreshold,scoreThreshold:a=i.scoreThreshold};return Mo.runKernel(Hn,{boxes:o,scores:s},u)}});
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function jf(e,t,n){const r=function(e,t,n){return function(e,t,n){let r=0,a=e.length,o=0,s=!1;for(;r<a;){o=r+(a-r>>>1);const i=n(t,e[o]);i>0?r=o+1:(a=o,s=!i)}return s?r:-r-1}(e,t,n||Wf)}(e,t,n),a=r<0?-(r+1):r;e.splice(a,0,t)}function Wf(e,t){return e>t?1:e<t?-1:0}
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Hf(e,t,n,r,a){return Kf(e,t,n,r,a,0)}function qf(e,t,n,r,a,o){return Kf(e,t,n,r,a,0,!1,o,!0)}function Gf(e,t,n,r,a,o){return Kf(e,t,n,r,a,o,!0)}function Kf(e,t,n,r,a,o,s=!1,i=!1,u=!1){const l=[];for(let e=0;e<t.length;e++)t[e]>a&&l.push({score:t[e],boxIndex:e,suppressBeginIndex:0});l.sort(Xf);const c=o>0?-.5/o:0,p=[],d=[];for(;p.length<n&&l.length>0;){const t=l.pop(),{score:n,boxIndex:o,suppressBeginIndex:s}=t;if(n<a)break;let i=!1;for(let n=p.length-1;n>=s;--n){const s=Qf(e,o,p[n]);if(s>=r){i=!0;break}if(t.score=t.score*Yf(r,c,s),t.score<=a)break}t.suppressBeginIndex=p.length,i||(t.score===n?(p.push(o),d.push(t.score)):t.score>a&&jf(l,t,Xf))}const f=p.length,h=n-f;i&&h>0&&(p.push(...new Array(h).fill(0)),d.push(...new Array(h).fill(0)));const m={selectedIndices:p};return s&&(m.selectedScores=d),u&&(m.validOutputs=f),m}function Qf(e,t,n){const r=e.subarray(4*t,4*t+4),a=e.subarray(4*n,4*n+4),o=Math.min(r[0],r[2]),s=Math.min(r[1],r[3]),i=Math.max(r[0],r[2]),u=Math.max(r[1],r[3]),l=Math.min(a[0],a[2]),c=Math.min(a[1],a[3]),p=Math.max(a[0],a[2]),d=Math.max(a[1],a[3]),f=(i-o)*(u-s),h=(p-l)*(d-c);if(f<=0||h<=0)return 0;const m=Math.max(o,l),g=Math.max(s,c),y=Math.min(i,p),b=Math.min(u,d),v=Math.max(y-m,0)*Math.max(b-g,0);return v/(f+h-v)}function Yf(e,t,n){const r=Math.exp(t*n*n);return n<=e?r:0}function Xf(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}const Zf=
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){const o=Bo(e,"boxes","nonMaxSuppressionAsync"),s=Bo(t,"scores","nonMaxSuppressionAsync"),i=Vf(o,s,n,r,a);n=i.maxOutputSize,r=i.iouThreshold,a=i.scoreThreshold;const u=await Promise.all([o.data(),s.data()]),l=u[0],c=u[1],{selectedIndices:p}=Hf(l,c,n,r,a);return o!==e&&o.dispose(),s!==t&&s.dispose(),Xd(p,"int32")};const Jf=jo({nonMaxSuppressionWithScore_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=0){const s=Bo(e,"boxes","nonMaxSuppression"),i=Bo(t,"scores","nonMaxSuppression"),u=Vf(s,i,n,r,a,o),l={boxes:s,scores:i},c={maxOutputSize:n=u.maxOutputSize,iouThreshold:r=u.iouThreshold,scoreThreshold:a=u.scoreThreshold,softNmsSigma:o=u.softNmsSigma},p=Mo.runKernel(Gn,l,c);return{selectedIndices:p[0],selectedScores:p[1]}}});const eh=
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=0){const s=Bo(e,"boxes","nonMaxSuppressionAsync"),i=Bo(t,"scores","nonMaxSuppressionAsync"),u=Vf(s,i,n,r,a,o);n=u.maxOutputSize,r=u.iouThreshold,a=u.scoreThreshold,o=u.softNmsSigma;const l=await Promise.all([s.data(),i.data()]),c=l[0],p=l[1],{selectedIndices:d,selectedScores:f}=Gf(c,p,n,r,a,o);return s!==e&&s.dispose(),i!==t&&i.dispose(),{selectedIndices:Xd(d,"int32"),selectedScores:Xd(f)}};const th=jo({nonMaxSuppressionPadded_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=!1){const s=Bo(e,"boxes","nonMaxSuppression"),i=Bo(t,"scores","nonMaxSuppression"),u=Vf(s,i,n,r,a,null),l={boxes:s,scores:i},c={maxOutputSize:u.maxOutputSize,iouThreshold:u.iouThreshold,scoreThreshold:u.scoreThreshold,padToMaxOutputSize:o},p=Mo.runKernel(qn,l,c);return{selectedIndices:p[0],validOutputs:p[1]}}});const nh=
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=!1){const s=Bo(e,"boxes","nonMaxSuppressionAsync"),i=Bo(t,"scores","nonMaxSuppressionAsync"),u=Vf(s,i,n,r,a,null),l=u.maxOutputSize,c=u.iouThreshold,p=u.scoreThreshold,[d,f]=await Promise.all([s.data(),i.data()]),{selectedIndices:h,validOutputs:m}=qf(d,f,l,c,p,o);return s!==e&&s.dispose(),i!==t&&i.dispose(),{selectedIndices:Xd(h,"int32"),validOutputs:Di(m,"int32")}};const rh=jo({resizeBilinear_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=!1,r=!1){const a=Bo(e,"images","resizeBilinear");X(3===a.rank||4===a.rank,(()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${a.rank}.`)),X(2===t.length,(()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`)),X(!1===r||!1===n,(()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false."));let o=a,s=!1;3===a.rank&&(s=!0,o=Xl(a,[1,a.shape[0],a.shape[1],a.shape[2]]));const[]=t,i={images:o},u={alignCorners:n,halfPixelCenters:r,size:t},l=Mo.runKernel(dr,i,u);return s?Xl(l,[l.shape[1],l.shape[2],l.shape[3]]):l}});const ah=jo({resizeNearestNeighbor_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=!1,r=!1){const a=Bo(e,"images","resizeNearestNeighbor");X(3===a.rank||4===a.rank,(()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${a.rank}.`)),X(2===t.length,(()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`)),X("float32"===a.dtype||"int32"===a.dtype,(()=>"`images` must have `int32` or `float32` as dtype")),X(!1===r||!1===n,(()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false."));let o=a,s=!1;3===a.rank&&(s=!0,o=Xl(a,[1,a.shape[0],a.shape[1],a.shape[2]]));const[]=t,i={images:o},u={alignCorners:n,halfPixelCenters:r,size:t},l=Mo.runKernel(cr,i,u);return s?Xl(l,[l.shape[1],l.shape[2],l.shape[3]]):l}});const oh=jo({threshold_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t="binary",n=!1,r=.5){const a=Bo(e,"image","threshold"),o=a.shape[0]*a.shape[1];let s,i,u,l,c=xi(Xd([r]),255);if(X(3===a.rank,(()=>`Error in threshold: image must be rank 3,but got rank ${a.rank}.`)),X(3===a.shape[2]||1===a.shape[2],(()=>`Error in threshold: image color channel must be equal to 3 or 1but got ${a.shape[2]}.`)),X("int32"===a.dtype||"float32"===a.dtype,(()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${a.dtype}.`)),X("otsu"===t||"binary"===t,(()=>`Method must be binary or otsu, but was ${t}`)),3===a.shape[2]){[s,i,u]=jd(a,[1,1,1],-1);const e=xi(s,.2989),t=xi(i,.587),n=xi(u,.114);l=bi(bi(e,t),n)}else l=e;if("otsu"===t){c=function(e,t){let n,r,a,o,s,i,u=Xd([-1]),l=Xd([0]),c=Xd([0]);for(let p=0;p<e.size-1;p++){n=nc(e,0,p+1),r=nc(e,p+1),s=wi(ep(n),t),i=wi(ep(r),t);const d=ep(xi(n,bd(0,n.size)));a=wi(d,ep(n));const f=Vi(r.shape,n.size),h=bi(bd(0,r.size),f),m=xi(r,h);o=wi(ep(m),ep(r));const g=Wi(a,o),y=Wi(a,o),b=xi(s,i);c=xi(xi(b,g),y);const v=pp(c,l);l=Pc(v,c,l),u=Pc(v,Xd([p]),u)}return u}(cc(Ks(_d(l),"int32"),qo([]),256),o)}const p=n?bp(l,c):pp(l,c);return Ks(xi(p,255),"int32")}});const sh=jo({transform_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n="nearest",r="constant",a=0,o){const s=Bo(e,"image","transform","float32"),i=Bo(t,"transforms","transform","float32");X(4===s.rank,(()=>`Error in transform: image must be rank 4,but got rank ${s.rank}.`)),X(2===i.rank&&(i.shape[0]===s.shape[0]||1===i.shape[0])&&8===i.shape[1],(()=>"Error in transform: Input transform should be batch x 8 or 1 x 8")),X(null==o||2===o.length,(()=>`Error in transform: outputShape must be [height, width] or null, but got ${o}.`));const u={image:s,transforms:i},l={interpolation:n,fillMode:r,fillValue:a,outputShape:o};return Mo.runKernel(Xr,u,l)}});const ih=jo({bandPart_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"a","bandPart");X(r.rank>=2,(()=>`bandPart(): Rank must be at least 2, got ${r.rank}.`));const a=r.shape,[o,s]=r.shape.slice(-2);let i,u;"number"==typeof t?(X(t%1==0,(()=>`bandPart(): numLower must be an integer, got ${t}.`)),X(t<=o,(()=>`bandPart(): numLower (${t}) must not be greater than the number of rows (${o}).`)),i=Bo(t<0?o:t,"numLower","bandPart")):(X("int32"===t.dtype,(()=>"bandPart(): numLower's dtype must be an int32.")),i=Pc(yp(t,0),o,Vp(t,o))),"number"==typeof n?(X(n%1==0,(()=>`bandPart(): numUpper must be an integer, got ${n}.`)),X(n<=s,(()=>`bandPart(): numUpper (${n}) must not be greater than the number of columns (${s}).`)),u=Bo(n<0?s:n,"numUpper","bandPart")):(X("int32"===n.dtype,(()=>"bandPart(): numUpper's dtype must be an int32.")),u=Pc(yp(n,0),s,Vp(n,s)));const l=Xl(bd(0,o,1,"int32"),[-1,1]),c=bd(0,s,1,"int32"),p=Wi(l,c),d=_p(bp(p,i),dp(p,Nu(u))),f=Lp([o,s],r.dtype);return Xl(Gd(uf(Xl(r,[-1,o,s])).map((e=>Pc(d,e,f)))),a)}});const uh=jo({gramSchmidt_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e){let t;if(Array.isArray(e)){t=!1,X(null!=e&&e.length>0,(()=>"Gram-Schmidt process: input must not be null, undefined, or empty"));const n=e[0].shape[0];for(let t=1;t<e.length;++t)X(e[t].shape[0]===n,(()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[t].shape[0]} vs. ${n})`))}else t=!0,e=jd(e,e.shape[0],0).map((e=>qd(e,[0])));X(e.length<=e[0].shape[0],(()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`));const n=[],r=e;for(let t=0;t<e.length;++t)n.push(Mo.tidy((()=>{let e=r[t];if(t>0)for(let r=0;r<t;++r){const t=xi(ep(xi(n[r],e)),n[r]);e=Wi(e,t)}return wi(e,np(e,"euclidean"))})));return t?Gd(n,0):n}});function lh(e,t=!1){return Mo.tidy((()=>{X(2===e.shape.length,(()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`));const n=e.shape[0],r=e.shape[1];let a=up(n),o=Qs(e);const s=Zd([[1]],[1,1]);let i=Qs(s);const u=n>=r?r:n;for(let e=0;e<u;++e){const t=o,u=i,l=a;[i,o,a]=Mo.tidy((()=>{const t=nc(o,[e,e],[n-e,1]),u=np(t),l=nc(o,[e,e],[1,1]),c=Pc(pp(l,0),Zd([[-1]]),Zd([[1]])),p=Wi(l,xi(c,u)),d=wi(t,p);i=1===d.shape[0]?Qs(s):ec([s,nc(d,[1,0],[d.shape[0]-1,d.shape[1]])],0);const f=Nu(wi(ku(c,p),u)),h=nc(o,[e,0],[n-e,r]),m=xi(f,i),g=_u(i);if(0===e)o=Wi(h,ku(m,ku(g,h)));else{const t=Wi(h,ku(m,ku(g,h)));o=ec([nc(o,[0,0],[e,r]),t],0)}const y=_u(m),b=nc(a,[0,e],[n,a.shape[1]-e]);if(0===e)a=Wi(b,ku(ku(b,i),y));else{const t=Wi(b,ku(ku(b,i),y));a=ec([nc(a,[0,0],[n,e]),t],1)}return[i,o,a]})),si([t,u,l])}return!t&&n>r&&(a=nc(a,[0,0],[n,r]),o=nc(o,[0,0],[r,r])),[a,o]}))}const ch=jo({qr_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t=!1){if(X(e.rank>=2,(()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`)),2===e.rank)return lh(e,t);{const n=e.shape.slice(0,e.shape.length-2).reduce(((e,t)=>e*t)),r=uf(Xl(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),a=[],o=[];r.forEach((e=>{const[n,r]=lh(e,t);a.push(n),o.push(r)}));return[Xl(Gd(a,0),e.shape),Xl(Gd(o,0),e.shape)]}}});
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
var ph;!function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"}(ph||(ph={}));const dh=jo({computeWeightedLoss_:function(e,t,n=ph.SUM_BY_NONZERO_WEIGHTS){const r=Bo(e,"losses","computeWeightedLoss");let a=null;null!=t&&(a=Bo(t,"weights","computeWeightedLoss"));const o=null==a?r:xi(r,a);if(n===ph.NONE)return o;if(n===ph.SUM)return ep(o);if(n===ph.MEAN){if(null==a)return Pp(o);{const e=r.size/a.size,t=wi(ep(o),ep(a));return e>1?wi(t,Di(e)):t}}if(n===ph.SUM_BY_NONZERO_WEIGHTS){if(null==a)return wi(ep(o),Di(r.size));{const e=xi(a,zp(r.shape)),t=Ks(ep(Gp(e,Di(0))),"float32");return wi(ep(o),t)}}throw Error(`Unknown reduction: ${n}`)}});const fh=jo({absoluteDifference_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=ph.SUM_BY_NONZERO_WEIGHTS){const a=Bo(e,"labels","absoluteDifference"),o=Bo(t,"predictions","absoluteDifference");let s=null;null!=n&&(s=Bo(n,"weights","absoluteDifference")),Z(a.shape,o.shape,"Error in absoluteDifference: ");const i=qi(Wi(a,o));return dh(i,s,r)}});const hh=jo({cosineDistance_:function(e,t,n,r,a=ph.SUM_BY_NONZERO_WEIGHTS){const o=Bo(e,"labels","cosineDistance"),s=Bo(t,"predictions","cosineDistance");let i=null;null!=r&&(i=Bo(r,"weights","cosineDistance")),Z(o.shape,s.shape,"Error in cosineDistance: ");const u=Di(1),l=Wi(u,ep(xi(o,s),n,!0));return dh(l,i,a)}});const mh=jo({hingeLoss_:function(e,t,n,r=ph.SUM_BY_NONZERO_WEIGHTS){let a=Bo(e,"labels","hingeLoss");const o=Bo(t,"predictions","hingeLoss");let s=null;null!=n&&(s=Bo(n,"weights","hingeLoss")),Z(a.shape,o.shape,"Error in hingeLoss: ");const i=Di(1);a=Wi(xi(Di(2),a),i);const u=wd(Wi(i,xi(a,o)));return dh(u,s,r)}});const gh=jo({huberLoss_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=1,a=ph.SUM_BY_NONZERO_WEIGHTS){const o=Bo(e,"labels","huberLoss"),s=Bo(t,"predictions","huberLoss");let i=null;null!=n&&(i=Bo(n,"weights","huberLoss")),Z(o.shape,s.shape,"Error in huberLoss: ");const u=Di(r),l=qi(Wi(s,o)),c=Vp(l,u),p=Wi(l,c),d=bi(xi(Di(.5),Si(c)),xi(u,p));return dh(d,i,a)}});const yh=jo({logLoss_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=1e-7,a=ph.SUM_BY_NONZERO_WEIGHTS){const o=Bo(e,"labels","logLoss"),s=Bo(t,"predictions","logLoss");let i=null;null!=n&&(i=Bo(n,"weights","logLoss")),Z(o.shape,s.shape,"Error in logLoss: ");const u=Di(1),l=Di(r),c=Nu(xi(o,xp(bi(s,l)))),p=xi(Wi(u,o),xp(bi(Wi(u,s),l))),d=Wi(c,p);return dh(d,i,a)}});const bh=jo({meanSquaredError_:
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=ph.SUM_BY_NONZERO_WEIGHTS){const a=Bo(e,"labels","meanSquaredError"),o=Bo(t,"predictions","meanSquaredError");let s=null;null!=n&&(s=Bo(n,"weights","meanSquaredError")),Z(a.shape,o.shape,"Error in meanSquaredError: ");const i=Hd(a,o);return dh(i,s,r)}});const vh=jo({sigmoidCrossEntropy_:function(e,t,n,r=0,a=ph.SUM_BY_NONZERO_WEIGHTS){let o=Bo(e,"multiClassLabels","sigmoidCrossEntropy");const s=Bo(t,"logits","sigmoidCrossEntropy");let i=null;if(null!=n&&(i=Bo(n,"weights","sigmoidCrossEntropy")),Z(o.shape,s.shape,"Error in sigmoidCrossEntropy: "),r>0){const e=Di(r),t=Di(1),n=Di(.5);o=bi(xi(o,Wi(t,e)),xi(n,e))}const u=
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"labels","sigmoidCrossEntropyWithLogits"),r=Bo(t,"logits","sigmoidCrossEntropyWithLogits");Z(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");const a=wd(r),o=xi(r,n),s=kp(ap(Nu(qi(r))));return bi(Wi(a,o),s)}(o,s);return dh(u,i,a)}});const wh=jo({softmaxCrossEntropy_:function(e,t,n,r=0,a=ph.SUM_BY_NONZERO_WEIGHTS){let o=Bo(e,"onehotLabels","softmaxCrossEntropy");const s=Bo(t,"logits","softmaxCrossEntropy");let i=null;if(null!=n&&(i=Bo(n,"weights","softmaxCrossEntropy")),Z(o.shape,s.shape,"Error in softmaxCrossEntropy: "),r>0){const e=Di(r),t=Di(1),n=Di(o.shape[1]);o=bi(xi(o,Wi(t,e)),wi(e,n))}const u=
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=-1){if(-1===n&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${t.rank} and dim was ${n}`);const r=Mi(((e,t,r)=>{const a=Tp(t,[n],!0),o=Wi(Ks(t,"float32"),a);r([e,o]);const s=Nu(xi(o,e));return{value:ep(s,[n]),gradFunc:(e,t)=>{const[r,a]=t,o=Gc(e.shape,[n]);return[xi(Xl(e,o),Wi(Ks(r,"float32"),ap(a))),xi(Xl(e,o),Wi(ap(a),Ks(r,"float32")))]}}}));return r(e,t)}(o,s);return dh(u,i,a)}});const xh=jo({sparseFillEmptyRows_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r){const a=Bo(e,"indices","sparseFillEmptyRows","int32"),o=Bo(t,"values","sparseFillEmptyRows"),s=Bo(n,"denseShape","sparseFillEmptyRows","int32"),i=Bo(r,"defaultValue","sparseFillEmptyRows",o.dtype);if(2!==a.rank)throw new Error(`Indices should be Tensor2D but received shape\n ${a.shape}`);if(1!==o.rank)throw new Error(`Values should be Tensor1D but received shape ${o.shape}`);if(1!==s.rank)throw new Error(`Dense shape should be Tensor1D but received shape ${s.shape}`);if(0!==i.rank)throw new Error(`Default value should be a scalar but received shape ${i.shape}`);const u={indices:a,values:o,denseShape:s,defaultValue:i},l=Mo.runKernel($r,u);return{outputIndices:l[0],outputValues:l[1],emptyRowIndicator:l[2],reverseIndexMap:l[3]}}});const kh=jo({sparseReshape_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"inputIndices","sparseReshape","int32"),a=Bo(t,"inputShape","sparseReshape","int32"),o=Bo(n,"newShape","sparseReshape","int32");if(2!==r.rank)throw new Error(`Input indices should be Tensor2D but received shape\n ${r.shape}`);if(1!==a.rank)throw new Error(`Input shape should be Tensor1D but received shape ${a.shape}`);if(1!==o.rank)throw new Error(`New shape should be Tensor1D but received shape ${o.shape}`);const s={inputIndices:r,inputShape:a,newShape:o},i=Mo.runKernel(Rr,s);return{outputIndices:i[0],outputShape:i[1]}}});const Sh=jo({sparseSegmentMean_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"data","sparseSegmentMean"),a=Bo(t,"indices","sparseSegmentMean","int32"),o=Bo(n,"segmentIds","sparseSegmentMean","int32");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.rank)throw new Error(`Indices should be Tensor1D but received shape\n ${a.shape}`);if(1!==o.rank)throw new Error(`Segment ids should be Tensor1D but received shape\n ${o.shape}`);const s={data:r,indices:a,segmentIds:o};return Mo.runKernel(Fr,s)}});const Eh=jo({sparseSegmentSum_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n){const r=Bo(e,"data","sparseSegmentSum"),a=Bo(t,"indices","sparseSegmentSum","int32"),o=Bo(n,"segmentIds","sparseSegmentSum","int32");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.rank)throw new Error(`Indices should be Tensor1D but received shape\n ${a.shape}`);if(1!==o.rank)throw new Error(`Segment ids should be Tensor1D but received shape\n ${o.shape}`);const s={data:r,indices:a,segmentIds:o};return Mo.runKernel(Pr,s)}});const Nh=jo({stringNGrams_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r,a,o,s,i){const u=Bo(e,"data","stringNGrams","string");if("string"!==u.dtype)throw new Error("Data must be of datatype string");if(1!==u.shape.length)throw new Error(`Data must be a vector, saw: ${u.shape}`);const l=Bo(t,"dataSplits","stringNGrams");if("int32"!==l.dtype)throw new Error("Data splits must be of datatype int32");const c={separator:n,nGramWidths:r,leftPad:a,rightPad:o,padWidth:s,preserveShortSequences:i},p={data:u,dataSplits:l},d=Mo.runKernel(jr,p,c);return{nGrams:d[0],nGramsSplits:d[1]}}});const Th={fft:Bd,ifft:Vd,rfft:Wd,irfft:Ud},_h={hammingWindow:Df,hannWindow:Cf,frame:$f,stft:Rf},Ah={flipLeftRight:Pf,grayscaleToRGB:Lf,resizeNearestNeighbor:ah,resizeBilinear:rh,rgbToGrayscale:zf,rotateWithOffset:Bf,cropAndResize:Ff,nonMaxSuppression:Uf,nonMaxSuppressionAsync:Zf,nonMaxSuppressionWithScore:Jf,nonMaxSuppressionWithScoreAsync:eh,nonMaxSuppressionPadded:th,nonMaxSuppressionPaddedAsync:nh,threshold:oh,transform:sh},Ih={bandPart:ih,gramSchmidt:uh,qr:ch},Mh={absoluteDifference:fh,computeWeightedLoss:dh,cosineDistance:hh,hingeLoss:mh,huberLoss:gh,logLoss:yh,meanSquaredError:bh,sigmoidCrossEntropy:vh,softmaxCrossEntropy:wh},Oh={sparseFillEmptyRows:xh,sparseReshape:kh,sparseSegmentMean:Sh,sparseSegmentSum:Eh},Dh={stringNGrams:Nh,stringSplit:jo({stringSplit_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n=!0){const r=Bo(e,"input","stringSplit","string"),a=Bo(t,"delimiter","stringSplit","string");if(1!==r.rank)throw new Error(`Input should be Tensor1D but received shape ${r.shape}`);if(0!==a.rank)throw new Error(`Delimiter should be a scalar but received shape ${a.shape}`);const o={skipEmpty:n},s={input:r,delimiter:a},i=Mo.runKernel(Wr,s,o);return{indices:i[0],values:i[1],shape:i[2]}}}),stringToHashBucketFast:jo({stringToHashBucketFast_:
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t){const n=Bo(e,"input","stringToHashBucketFast","string"),r={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");const a={input:n};return Mo.runKernel(Hr,a,r)}}),staticRegexReplace:jo({staticRegexReplace_:
/**
* @license
* Copyright 2023 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function(e,t,n,r=!0){const a=Bo(e,"input","staticRegexReplace","string"),o={pattern:t,rewrite:n,replaceGlobal:r};return Mo.runKernel(Vr,{x:a},o)}})},Ch=Sl,$h="undefined"!=typeof requestAnimationFrame?requestAnimationFrame:"undefined"!=typeof setImmediate?setImmediate:e=>e();function Rh(){return new Promise((e=>$h((()=>e()))))}
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Fh(e,t){const n=e[0].length;e.forEach(((e,t)=>{X(e.length===n,(()=>`Error in concat${n}D: rank of tensors[${t}] must be the same as the rank of the rest (${n})`))})),X(t>=0&&t<n,(()=>`Error in concat${n}D: axis must be between 0 and ${n-1}.`));const r=e[0];e.forEach(((e,a)=>{for(let o=0;o<n;o++)X(o===t||e[o]===r[o],(()=>`Error in concat${n}D: Shape of tensors[${a}] (${e}) does not match the shape of the rest (${r}) along the non-concatenated axis ${a}.`))}))}function Ph(e,t){const n=e[0].slice();for(let r=1;r<e.length;r++)n[t]+=e[r][t];return n}
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
var Lh;function zh(e,t,n){let r=new Array;if(null==n&&null==t)return r;if(null==t)for(;r.length<e+n.length;)r.push(-1);else r=t.slice();if(null==n)return r;if(e+n.length!==r.length)throw new Error(`rt input.shape and shape=${t} are incompatible: rt input.rank = ${e+n.length}, but shape.rank = ${r.length}`);for(let a=1;a<n.length;++a){const o=n[a],s=r[r.length-n.length+a],i=r[s];if(o>=0)if(i>=0){if(i!==o)throw new Error(`rt input.shape and shape=${t} are incompatible: rt input.shape[${a+e}] = ${o} but shape[${a+e}] = ${i}`)}else r[s]=o}return r}function Bh(e){const t={FIRST_DIM_SIZE:Lh.FIRST_DIM_SIZE,VALUE_ROWIDS:Lh.VALUE_ROWIDS,ROW_LENGTHS:Lh.ROW_LENGTHS,ROW_SPLITS:Lh.ROW_SPLITS,ROW_LIMITS:Lh.ROW_LIMITS,ROW_STARTS:Lh.ROW_STARTS},n=[];for(const r of e){if(!(r in t))break;n.push(t[r])}return n}function Vh(e){return 0===e.length?0:e[0]===Lh.FIRST_DIM_SIZE?e.length-1:e.length}function Uh(e,t){if(null==e||null==t)return;const n=e.length,r=t.length;if(n>=r)throw new Error(`defaultValue.shape=${e} and ragged tensor flatValues.shape=${t}, are incompatible: defaultValue.rank = ${n} must be less than ragged tensor input flatValues.rank = ${r})`);for(let a=0;a<Math.min(n,r-1);++a){const n=e[a],r=t[a+1];if(n>=0&&r>=0&&1!==n&&n!==r)throw new Error(`defaultValue.shape=${e}, and ragged tensor input flatValues.shape=${t} are incompatible: defaultValue.shape[${a-e.length}] = ${n} but ragged tensor input.flatValues.shape[${a-e.length}] = ${r}`)}}!function(e){e[e.FIRST_DIM_SIZE=0]="FIRST_DIM_SIZE",e[e.VALUE_ROWIDS=1]="VALUE_ROWIDS",e[e.ROW_LENGTHS=2]="ROW_LENGTHS",e[e.ROW_SPLITS=3]="ROW_SPLITS",e[e.ROW_LIMITS=4]="ROW_LIMITS",e[e.ROW_STARTS=5]="ROW_STARTS"}(Lh||(Lh={}));
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const jh=30;function Wh(e){return e<=jh?e:Ne(e,Math.floor(Math.sqrt(e)))}
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Hh(e,t,n){return[n*("number"==typeof e?e:e[0]),t*("number"==typeof e?e:e[1])]}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function qh(e,t,n,r=!0){let a=[];if(r)a=a.concat(t.slice(0)),a.push(e[0]/n),a=a.concat(e.slice(1));else{a=a.concat(e[0]);const n=t.length;for(let r=0;r<n;++r)a=a.concat([e[r+1]/t[r],t[r]]);a=a.concat(e.slice(n+1))}return a}function Gh(e,t,n=!0){const r=[];if(n){r.push(t);for(let n=t+1;n<e;++n)n<=2*t?(r.push(n),r.push(n-(t+1))):r.push(n)}else{const n=[],a=[];for(let r=1;r<e;++r)r>=2*t+1||r%2==1?a.push(r):n.push(r);r.push(...n),r.push(0),r.push(...a)}return r}function Kh(e,t,n,r=!0){const a=[];r?a.push(e[0]/n):a.push(e[0]*n);for(let n=1;n<e.length;++n)n<=t.length?r?a.push(t[n-1]*e[n]):a.push(e[n]/t[n-1]):a.push(e[n]);return a}function Qh(e,t){const n=[0];for(let r=0;r<t;++r)n.push(e[r][0]);return n}function Yh(e,t,n){const r=e.slice(0,1);for(let a=0;a<n;++a)r.push(e[a+1]-t[a][0]-t[a][1]);return r}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Xh=1.7580993408473768,Zh=1.0507009873554805,Jh=.3275911,em=.254829592,tm=-.284496736,nm=1.421413741,rm=-1.453152027,am=1.061405429;
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function om(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);const n=new Float32Array(2*e.length);for(let r=0;r<n.length;r+=2)n[r]=e[r/2],n[r+1]=t[r/2];return n}function sm(e){const t=new Float32Array(e.length/2),n=new Float32Array(e.length/2);for(let r=0;r<e.length;r+=2)t[r/2]=e[r],n[r/2]=e[r+1];return{real:t,imag:n}}function im(e){const t=Math.ceil(e.length/4),n=new Float32Array(t),r=new Float32Array(t);for(let t=0;t<e.length;t+=4)n[Math.floor(t/4)]=e[t],r[Math.floor(t/4)]=e[t+1];return{real:n,imag:r}}function um(e){const t=Math.floor(e.length/4),n=new Float32Array(t),r=new Float32Array(t);for(let t=2;t<e.length;t+=4)n[Math.floor(t/4)]=e[t],r[Math.floor(t/4)]=e[t+1];return{real:n,imag:r}}function lm(e,t){return{real:e[2*t],imag:e[2*t+1]}}function cm(e,t,n,r){e[2*r]=t,e[2*r+1]=n}function pm(e,t){const n=new Float32Array(e/2),r=new Float32Array(e/2);for(let a=0;a<Math.ceil(e/2);a++){const o=(t?2:-2)*Math.PI*(a/e);n[a]=Math.cos(o),r[a]=Math.sin(o)}return{real:n,imag:r}}function dm(e,t,n){const r=(n?2:-2)*Math.PI*(e/t);return{real:Math.cos(r),imag:Math.sin(r)}}
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const fm="->",hm=/->/g,mm=",",gm="...";function ym(e,t){const n=((e=e.replace(/\s/g,"")).length-e.replace(hm,"").length)/fm.length;if(n<1)throw new Error("Equations without an arrow are not supported.");if(n>1)throw new Error(`Equation must contain exactly one arrow ("${fm}").`);const[r,a]=e.split(fm);X(-1===r.indexOf(gm),(()=>`The ellipsis notation ("${gm}") is not supported yet.`));const o=r.split(mm),s=o.length;if(t!==s)throw new Error(`Expected ${s} input tensors, received ${t}`);if(s>2)throw new Error("Support for more than 2 input tensors is not implemented yet.");const i=[];for(let e=0;e<a.length;++e){const t=a[e];if(!o.some((e=>-1!==e.indexOf(t))))throw new Error(`Output subscripts contain the label ${t} not present in the input subscripts.`);-1===i.indexOf(t)&&i.push(t)}for(let e=0;e<r.length;++e){const t=r[e];-1===i.indexOf(t)&&t!==mm&&i.push(t)}const u=new Array(o.length);for(let e=0;e<s;++e){if(new Set(o[e].split("")).size!==o[e].length)throw new Error(`Found duplicate axes in input component ${o[e]}. Support for duplicate axes in input is not implemented yet.`);u[e]=[];for(let t=0;t<o[e].length;++t)u[e].push(i.indexOf(o[e][t]))}const l=i.length,c=[];for(let e=a.length;e<l;++e)c.push(e);return{allDims:i,summedDims:c,idDims:u}}function bm(e,t){let n=new Array(e);n.fill(-1);for(let e=0;e<t.length;++e)n[t[e]]=e;const r=[];for(let t=0;t<e;++t)-1===n[t]&&r.push(t);return n=n.filter((e=>-1!==e)),{permutationIndices:n,expandDims:r}}function vm(e,t,n){const r=new Array(e);for(let e=0;e<n.length;++e){const a=n[e].shape;for(let n=0;n<t[e].length;++n)void 0===r[t[e][n]]?r[t[e][n]]=a[n]:X(r[t[e][n]]===a[n],(()=>`Expected dimension ${r[t[e][n]]} at axis ${n} of input shaped ${JSON.stringify(a)}, but got dimension ${a[n]}`))}}function wm(e,t){const n=e,r=[];let a=0;0===e.length&&n.push(-1),a=e.length+1;for(let e=0;e<a;++e)r.push([]);const o=[];for(let e=0;e<n.length;++e){const a=km(t,n[e]);for(const t of a)-1===o.indexOf(t)&&(r[e].push(t),o.push(t))}return{path:n,steps:r}}function xm(e){return e.every(((e,t)=>e===t))}function km(e,t){const n=[];for(let r=0;r<e.length;++r)0!==e[r].length&&-1===e[r].indexOf(t)&&-1!==t||n.push(r);return n}function Sm(e,t,n=0){let r=[];if("number"==typeof t)X(e.shape[n]%t==0,(()=>"Number of splits must evenly divide the axis.")),r=new Array(t).fill(e.shape[n]/t);else{X(t.reduce(((e,t)=>(-1===t&&(e+=1),e)),0)<=1,(()=>"There should be only one negative value in split array."));const a=t.indexOf(-1);if(-1!==a){const r=t.reduce(((e,t)=>t>0?e+t:e));t[a]=e.shape[n]-r}X(e.shape[n]===t.reduce(((e,t)=>e+t)),(()=>"The sum of sizes must match the size of the axis dimension.")),r=t}return r}
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Em(e){return`Received SparseTensor with denseShape[0] = 0 but\n indices.shape[0] = ${e}`}function Nm(e,t){return`indices(${e}, 0) is invalid: ${t} < 0`}function Tm(e,t,n){return`indices(${e}, 0) is invalid: ${t} >= ${n}`}
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function _m(e,t){return`only one output dimension may be -1, not both ${e} and ${t}`}function Am(e,t){return`size ${e} must be non-negative, not ${t}`}function Im(){return"reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero"}function Mm(e,t){return`Input to reshape is a SparseTensor with ${ee(e)}\n dense values, but the requested shape requires a multiple of ${ee(t)}. inputShape=${e} outputShape= ${t}`}function Om(e,t){return`Input to reshape is a tensor with ${ee(e)} dense values, but the requested shape has ${ee(t)}. inputShape=${e} outputShape=${t}`}
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Dm(){return"segment ids must be >= 0"}function Cm(){return"segment ids are not increasing"}function $m(e,t){return`Segment id ${e} out of range [0, ${t}), possibly because segmentIds input is not sorted.`}function Rm(e,t,n){return`Bad: indices[${e}] == ${t} out of range [0, ${n})`}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Fm(e,t){let n,r=!1;for(e<=jh?(n=e,r=!0):n=Ne(e,Math.floor(Math.sqrt(e)));!r;)n>t||n===e?r=!0:n=Ne(e,n+1);return n}function Pm(e,t,n){const r=[],a=e.length;for(let o=0;o<a;o++)o!==t?r.push(e[o]):r.push(n);return r}function Lm(e,t,n,r){const a=t.shape.length,o=e.shape.length;if(0!==r&&(r<-a||r>a))throw new Error(`Expect batchDims in the range of [-${a}, ${a}], but got ${r}`);if(r<0&&(r+=a),r>o)throw new Error(`batchDims (${r}) must be less than rank(x) (\n ${o}).`);if(n<r)throw new Error(`batchDims (${r}) must be less than or equal to axis (${n}).`);for(let n=0;n<r;++n)if(e.shape[n]!==t.shape[n])throw new Error(`x.shape[${n}]: ${e.shape[n]} should be equal to indices.shape[${n}]: ${t.shape[n]}.`);const s=e.shape[n],i=[];let u=1,l=1,c=1;for(let t=0;t<r;++t)i.push(e.shape[t]),u*=e.shape[t];for(let t=r;t<n;t++)i.push(e.shape[t]),l*=e.shape[t];for(let e=r;e<a;e++)i.push(t.shape[e]);for(let t=n+1;t<o;t++)i.push(e.shape[t]),c*=e.shape[t];return{batchSize:u,sliceSize:c,outerSize:l,dimSize:s,outputShape:i}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function zm(e){try{return e.map((e=>ja(e)))}catch(e){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${e}`)}}function Bm(e){return e.map((e=>Ua(e)))}
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
!function(){for(const e of tu)Pi(e)}();
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
var Vm,Um;Be().registerFlag("KEEP_INTERMEDIATE_TENSORS",(()=>!1),(e=>{e&&console.warn("Keep intermediate tensors is ON. This will print the values of all intermediate tensors during model inference. Not all models support this mode. For details, check e2e/benchmarks/ model_config.js. This significantly impacts performance.")})),function(e){e[e.DT_INVALID=0]="DT_INVALID",e[e.DT_FLOAT=1]="DT_FLOAT",e[e.DT_DOUBLE=2]="DT_DOUBLE",e[e.DT_INT32=3]="DT_INT32",e[e.DT_UINT8=4]="DT_UINT8",e[e.DT_INT16=5]="DT_INT16",e[e.DT_INT8=6]="DT_INT8",e[e.DT_STRING=7]="DT_STRING",e[e.DT_COMPLEX64=8]="DT_COMPLEX64",e[e.DT_INT64=9]="DT_INT64",e[e.DT_BOOL=10]="DT_BOOL",e[e.DT_QINT8=11]="DT_QINT8",e[e.DT_QUINT8=12]="DT_QUINT8",e[e.DT_QINT32=13]="DT_QINT32",e[e.DT_BFLOAT16=14]="DT_BFLOAT16",e[e.DT_QINT16=15]="DT_QINT16",e[e.DT_QUINT16=16]="DT_QUINT16",e[e.DT_UINT16=17]="DT_UINT16",e[e.DT_COMPLEX128=18]="DT_COMPLEX128",e[e.DT_HALF=19]="DT_HALF",e[e.DT_RESOURCE=20]="DT_RESOURCE",e[e.DT_VARIANT=21]="DT_VARIANT",e[e.DT_UINT32=22]="DT_UINT32",e[e.DT_UINT64=23]="DT_UINT64",e[e.DT_FLOAT_REF=101]="DT_FLOAT_REF",e[e.DT_DOUBLE_REF=102]="DT_DOUBLE_REF",e[e.DT_INT32_REF=103]="DT_INT32_REF",e[e.DT_UINT8_REF=104]="DT_UINT8_REF",e[e.DT_INT16_REF=105]="DT_INT16_REF",e[e.DT_INT8_REF=106]="DT_INT8_REF",e[e.DT_STRING_REF=107]="DT_STRING_REF",e[e.DT_COMPLEX64_REF=108]="DT_COMPLEX64_REF",e[e.DT_INT64_REF=109]="DT_INT64_REF",e[e.DT_BOOL_REF=110]="DT_BOOL_REF",e[e.DT_QINT8_REF=111]="DT_QINT8_REF",e[e.DT_QUINT8_REF=112]="DT_QUINT8_REF",e[e.DT_QINT32_REF=113]="DT_QINT32_REF",e[e.DT_BFLOAT16_REF=114]="DT_BFLOAT16_REF",e[e.DT_QINT16_REF=115]="DT_QINT16_REF",e[e.DT_QUINT16_REF=116]="DT_QUINT16_REF",e[e.DT_UINT16_REF=117]="DT_UINT16_REF",e[e.DT_COMPLEX128_REF=118]="DT_COMPLEX128_REF",e[e.DT_HALF_REF=119]="DT_HALF_REF",e[e.DT_RESOURCE_REF=120]="DT_RESOURCE_REF",e[e.DT_VARIANT_REF=121]="DT_VARIANT_REF",e[e.DT_UINT32_REF=122]="DT_UINT32_REF",e[e.DT_UINT64_REF=123]="DT_UINT64_REF"}(Vm||(Vm={})),function(e){let t;!function(e){e[e.LEGACY=0]="LEGACY",e[e.V1=1]="V1",e[e.V2=2]="V2"}(t=e.CheckpointFormatVersion||(e.CheckpointFormatVersion={}))}(Um||(Um={}));
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const jm={};function Wm(e){return jm[e]}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Hm(e,t,n,r,a){const o=t.inputParams[e];if(o&&void 0!==o.inputIndexStart){const e=o.inputIndexStart,s=0===o.inputIndexEnd?void 0:void 0===o.inputIndexEnd?e+1:o.inputIndexEnd,i=e<0?t.inputNames.length+e:e;if("tensor"===o.type)return qm(t.inputNames[i],n,r,a);if("tensors"===o.type){const o=t.inputs.slice(e,s);return t.inputNames.slice(e,s).filter(((e,t)=>{var n;return"NoOp"!==(null===(n=o[t])||void 0===n?void 0:n.op)})).map((e=>qm(e,n,r,a)))}const u=qm(t.inputNames[i],n,r,a),l=u.dataSync();return"number"===o.type?l[0]:Ae(u.shape,l)}const s=t.attrParams[e];return s&&s.value}function qm(e,t,n,r){const[a,o]=Ym(e,n);if(null!=r){const e=r.getHashTableHandleByName(a);if(null!=e)return e}const s=n.currentContextIds.find((e=>!!t[Qm(a,e)]));return void 0!==s?t[Qm(a,s)][o]:void 0}function Gm(e,t,n){return t[Qm(e,n.currentContextId)]}function Km(e,t){const[n,r,a]=Ym(e,t);return[Qm(n,t&&t.currentContextId),r,a]}function Qm(e,t){return t?`${e}-${t}`:e}function Ym(e,t){if(""===e)return["",0,void 0];const n=null!=t&&null!=t.parseNodeNameCache;if(n){const n=t.parseNodeNameCache.get(e);if(null!=n)return n}const r=e.split(":");let a;if(1===r.length)a=[e,0,void 0];else{const e=r[0],t=3===r.length?r[1]:void 0;a=[e,Number(r[r.length-1]),t]}return n&&t.parseNodeNameCache.set(e,a),a}function Xm(e,t,n){let r=Hm("pad",e,t,n);if("explicit"===r){r=Hm("explicitPaddings",e,t,n);const a=[[0,0],[0,0],[0,0],[0,0]];for(let e=0;e<4;e++)a[e][0]=r[2*e],a[e][1]=r[2*e+1];return a}return r}function Zm(e){return e.kept?e:Qs(e)}
/**
* @license
* Copyright 2023 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Jm=[{tfOpName:"Add",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddV2",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddN",category:"arithmetic",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"BiasAdd",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"Sub",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"RealDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Div",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"DivNoNan",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mul",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Maximum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Minimum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Pow",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SquaredDifference",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorMod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],eg=[{tfOpName:"Abs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan2",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ceil",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ClipByValue",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"clipValueMin",type:"number"},{start:2,name:"clipValueMax",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Complex",category:"basic_math",inputs:[{start:0,name:"real",type:"tensor"},{start:1,name:"imag",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ComplexAbs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Elu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Exp",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Floor",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Imag",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Neg",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Real",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Prelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"alpha",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu6",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Selu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sigmoid",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Rsqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Square",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sign",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Round",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Expm1",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log1p",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Reciprocal",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Softplus",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Erf",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LeakyRelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"alpha",name:"alpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsNan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsFinite",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsInf",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],tg=[{tfOpName:"EmptyTensorList",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"maxNumElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"LoopCond",category:"control",inputs:[{start:0,name:"pred",type:"tensor"}]},{tfOpName:"Sw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/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class bg{static get Instance(){return this._instance||(this._instance=new this)}constructor(){const e=[].concat(...[b,v,w,x,k,S,E,N,T,_,A,I,M,O,D,C,$,R,F].map((e=>e.json)));this.opMappers=e.reduce(((e,t)=>(e[t.tfOpName]=t,e)),{})}transformGraph(e,t={}){const n=e.node,r=[],a=[],o=[],s=n.reduce(((e,t)=>(e[t.name]=this.mapNode(t),t.op.startsWith("Placeholder")?r.push(e[t.name]):"Const"===t.op?a.push(e[t.name]):null!=t.input&&0!==t.input.length||o.push(e[t.name]),e)),{});let i=[];const u=[];let l={},c={};null!=t&&(l=this.mapSignatureEntries(t.inputs),c=this.mapSignatureEntries(t.outputs));const p=Object.keys(s);p.forEach((e=>{const t=s[e];t.inputNames.forEach(((e,n)=>{const[r,,a]=Km(e),o=s[r];if(null!=o.outputs){const e=o.outputs.indexOf(a);if(-1!==e){const a=`${r}:${e}`;t.inputNames[n]=a}}t.inputs.push(o),o.children.push(t)}))})),0===Object.keys(c).length?p.forEach((e=>{const t=s[e];0===t.children.length&&u.push(t)})):Object.keys(c).forEach((e=>{const[t]=Km(e),n=s[t];null!=n&&(n.signatureKey=c[e],u.push(n))})),Object.keys(l).length>0?Object.keys(l).forEach((e=>{const[t]=Km(e),n=s[t];n&&(n.signatureKey=l[e],i.push(n))})):i=r;let d={};null!=e.library&&null!=e.library.function&&(d=e.library.function.reduce(((e,t)=>(e[t.signature.name]=this.mapFunction(t),e)),{}));const f={nodes:s,inputs:i,outputs:u,weights:a,placeholders:r,signature:t,functions:d};return o.length>0&&(f.initNodes=o),f}mapSignatureEntries(e){return Object.keys(e||{}).reduce(((t,n)=>(t[e[n].name]=n,t)),{})}mapNode(e){const t=Wm(e.op)||this.opMappers[e.op]||{};null==e.attr&&(e.attr={});const n={name:e.name,op:e.op,category:t.category,inputNames:(e.input||[]).map((e=>e.startsWith("^")?e.slice(1):e)),inputs:[],children:[],inputParams:{},attrParams:{},rawAttrs:e.attr,outputs:t.outputs};return null!=t.inputs&&(n.inputParams=t.inputs.reduce(((e,t)=>(e[t.name]={type:t.type,inputIndexStart:t.start,inputIndexEnd:t.end},e)),{})),null!=t.attrs&&(n.attrParams=t.attrs.reduce(((t,n)=>{const r=n.type;let a;switch(n.type){case"string":a=wg(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=wg(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"string[]":a=Mg(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Mg(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"number":a=kg(e.attr,n.tfName,n.defaultValue||0),void 0===a&&n.tfDeprecatedName&&(a=kg(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"number[]":a=Ig(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Ig(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"bool":a=xg(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=xg(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"bool[]":a=Dg(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Dg(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"shape":a=Ag(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Ag(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"shape[]":a=Og(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Og(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"dtype":a=Ng(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Ng(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"dtype[]":a=Tg(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Tg(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"func":a=Eg(e.attr,n.tfName,n.defaultValue),void 0===a&&n.tfDeprecatedName&&(a=Eg(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${n.type} for op: ${e.op}`)}return t[n.name]={value:a,type:r},t}),{})),n}mapFunction(e){const t=e.nodeDef,n=[];let r={};null!=t&&(r=t.reduce(((e,t)=>(e[t.name]=this.mapNode(t),"Const"===t.op&&n.push(e[t.name]),e)),{}));const a=[],o=[];e.signature.inputArg.forEach((e=>{const[t]=Km(e.name),n={name:t,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:Sg(e.type),type:"dtype"}},children:[]};n.signatureKey=e.name,a.push(n),r[t]=n}));Object.keys(r).forEach((e=>{const t=r[e];t.inputNames.forEach(((e,n)=>{const[a,,o]=Km(e),s=r[a];if(null!=s.outputs){const e=s.outputs.indexOf(o);if(-1!==e){const r=`${a}:${e}`;t.inputNames[n]=r}}t.inputs.push(s),s.children.push(t)}))}));const s=e.ret;e.signature.outputArg.forEach((e=>{const[t,n]=Km(s[e.name]),a=r[t];null!=a&&(a.defaultOutput=n,o.push(a))}));const i=this.mapArgsToSignature(e);return{nodes:r,inputs:a,outputs:o,weights:n,placeholders:[],signature:i}}mapArgsToSignature(e){return{methodName:e.signature.name,inputs:e.signature.inputArg.reduce(((e,t)=>(e[t.name]=this.mapArgToTensorInfo(t),e)),{}),outputs:e.signature.outputArg.reduce(((t,n)=>(t[n.name]=this.mapArgToTensorInfo(n,e.ret),t)),{})}}mapArgToTensorInfo(e,t){let n=e.name;return null!=t&&(n=t[n]),{name:n,dtype:e.type}}}function vg(e,t){const n=Array.isArray(e)?String.fromCharCode.apply(null,e):function(e){const t=Be().global;if(void 0!==t.atob)return t.atob(e);if("undefined"!=typeof Buffer)return new Buffer(e,"base64").toString();throw new Error("Unable to decode base64 in this environment. Missing built-in atob() or Buffer()")}(e);return t?n:n.toLowerCase()}function wg(e,t,n,r=!1){const a=e[t];return null!=a?vg(a.s,r):n}function xg(e,t,n){const r=e[t];return r?r.b:n}function kg(e,t,n){const r=e[t]||{},a=null!=r.i?r.i:null!=r.f?r.f:n;return"number"==typeof a?a:parseInt(a,10)}function Sg(e){switch("string"==typeof e&&(e=Vm[e]),e){case Vm.DT_FLOAT:case Vm.DT_HALF:return"float32";case Vm.DT_INT32:case Vm.DT_INT64:case Vm.DT_INT8:case Vm.DT_UINT8:return"int32";case Vm.DT_BOOL:return"bool";case Vm.DT_DOUBLE:return"float32";case Vm.DT_STRING:return"string";default:return null}}function Eg(e,t,n){const r=e[t];return r&&r.func?r.func.name:n}function Ng(e,t,n){const r=e[t];return r&&r.type?Sg(r.type):n}function Tg(e,t,n){const r=e[t];return r&&r.list&&r.list.type?r.list.type.map((e=>Sg(e))):n}function _g(e){if(!e.unknownRank)return null!=e.dim?e.dim.map((e=>"number"==typeof e.size?e.size:parseInt(e.size,10))):[]}function Ag(e,t,n){const r=e[t];return r&&r.shape?_g(r.shape):n}function Ig(e,t,n){const r=e[t];return r?((r.list.f&&r.list.f.length?r.list.f:r.list.i)||[]).map((e=>"number"==typeof e?e:parseInt(e,10))):n}function Mg(e,t,n,r=!1){const a=e[t];return a&&a.list&&a.list.s?a.list.s.map((e=>vg(e,r))):n}function Og(e,t,n){const r=e[t];return r&&r.list&&r.list.shape?r.list.shape.map((e=>_g(e))):n}function Dg(e,t,n){const r=e[t];return r&&r.list&&r.list.b?r.list.b:n}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Cg{constructor(e,t,n){this.node=e,this.tensorMap=t,this.context=n,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map((e=>this.getInput(e))),null!=e.rawAttrs&&(this.attrs=Object.keys(e.rawAttrs).reduce(((e,t)=>(e[t]=this.getAttr(t),e)),{}))}getInput(e){return qm(e,this.tensorMap,this.context)}getAttr(e,t){const n=this.node.rawAttrs[e];if(null!=n.tensor)return qm(e,this.tensorMap,this.context);if(null!=n.i||null!=n.f)return kg(this.node.rawAttrs,e,t);if(null!=n.s)return wg(this.node.rawAttrs,e,t);if(null!=n.b)return xg(this.node.rawAttrs,e,t);if(null!=n.shape)return Ag(this.node.rawAttrs,e,t);if(null!=n.type)return Ng(this.node.rawAttrs,e,t);if(null!=n.list){if(null!=n.list.i||null!=n.list.f)return Ig(this.node.rawAttrs,e,t);if(null!=n.list.s)return Mg(this.node.rawAttrs,e,t);if(null!=n.list.shape)return Og(this.node.rawAttrs,e,t);if(null!=n.list.b)return Dg(this.node.rawAttrs,e,t);if(null!=n.list.type)return Tg(this.node.rawAttrs,e,t)}return t}}
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function $g(e,t,n=""){if("number"!=typeof e&&"number"!=typeof t){X(e.length===t.length,(()=>n+` Shapes ${e} and ${t} must match`));for(let r=0;r<e.length;r++){const a=e[r],o=t[r];X(a<0||o<0||a===o,(()=>n+` Shapes ${e} and ${t} must match`))}}}function Rg(e){return"number"!=typeof e&&!e.some((e=>e<0))}function Fg(e,t,n){let r=Pg(e,n);const a=!Rg(r);if(a&&0===t.length)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${r}`);if(a&&t.forEach((e=>{r=Pg(e.shape,r)})),!Rg(r))throw new Error(`Non-fully-defined elementShape: ${r}`);return r}function Pg(e,t){if("number"==typeof e)return t;if("number"==typeof t)return e;if(e.length!==t.length)throw new Error(`Incompatible ranks during merge: ${e} vs. ${t}`);const n=[];for(let r=0;r<e.length;++r){const a=e[r],o=t[r];if(a>=0&&o>=0&&a!==o)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[r]=a>=0?a:o}return n}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class Lg{constructor(e,t,n,r,a,o,s){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=r,this.identicalElementShapes=a,this.dynamicSize=o,this.clearAfterRead=s,this.tensors=[],this.closed_=!1,this.idTensor=Di(0),ii(this.idTensor)}get id(){return this.idTensor.id}get closed(){return this.closed_}clearAndClose(e){this.tensors.forEach((t=>{null!=e&&e.has(t.tensor.id)||t.tensor.dispose()})),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}size(){return this.tensors.length}read(e){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||e>=this.size())throw new Error(`Tried to read from index ${e}, but array size is: ${this.size()}`);const t=this.tensors[e];if(t.cleared)throw new Error(`TensorArray ${this.name}: Could not read index ${e} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}readMany(e){return e.map((e=>this.read(e)))}write(e,t){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||!this.dynamicSize&&e>=this.maxSize)throw new Error(`Tried to write to index ${e}, but array is not resizeable and size is: ${this.maxSize}`);const n=this.tensors[e]||{};if(t.dtype!==this.dtype)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e},\n because the value dtype is ${t.dtype}, but TensorArray dtype is ${this.dtype}.`);if(0!==this.size()||null!=this.elementShape&&0!==this.elementShape.length||(this.elementShape=t.shape),$g(this.elementShape,t.shape,`TensorArray ${this.name}: Could not write to TensorArray index ${e}.`),n.read)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been read.`);if(n.written)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been written.`);n.tensor=t,ii(t),n.written=!0,this.tensors[e]=n}writeMany(e,t){if(e.length!==t.length)throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${e.length} is not the same as tensors size: ${t.length}.`);e.forEach(((e,n)=>this.write(e,t[n])))}gather(e,t){if(t&&t!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${t}`);if(e)e=e.slice(0,this.size());else{e=[];for(let t=0;t<this.size();t++)e.push(t)}if(0===e.length)return qo([],[0].concat(this.elementShape));const n=this.readMany(e);return $g(this.elementShape,n[0].shape,"TensorArray shape mismatch: "),Gd(n,0)}concat(e){if(e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(0===this.size())return qo([],[0].concat(this.elementShape));const t=[];for(let e=0;e<this.size();e++)t.push(e);const n=this.readMany(t);return $g(this.elementShape,n[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${n[0].shape})`),ec(n,0)}scatter(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);if(e.length!==t.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${e.length} vs. ${t.shape[0]}`);const n=Math.max(...e);if(!this.dynamicSize&&n>=this.maxSize)throw new Error(`Max index must be < array size (${n} vs. ${this.maxSize})`);this.writeMany(e,uf(t,0))}split(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);let n=0;const r=e.map((e=>(n+=e,n)));if(n!==t.shape[0])throw new Error(`Expected sum of lengths to be equal to\n tensor.shape[0], but sum of lengths is\n ${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`);const a=0===n?0:t.size/n,o=[];oi((()=>{t=Xl(t,[1,n,a]);for(let n=0;n<e.length;++n){const s=[0,0===n?0:r[n-1],0],i=[1,e[n],a];o[n]=Xl(nc(t,s,i),this.elementShape)}return o}));const s=[];for(let t=0;t<e.length;t++)s[t]=t;this.writeMany(s,o)}}
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class zg{get id(){return this.idTensor.id}constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,null!=e&&e.forEach((e=>{if(n!==e.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${e.dtype}`);$g(t,e.shape,"TensorList shape mismatch: "),ii(e)})),this.idTensor=Di(0),this.maxNumElements=r,ii(this.idTensor)}copy(){return new zg([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach((t=>{null!=e&&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(-1!==n&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);$g(e,this.elementShape,"TensorList shape mismatch: ");const r=Fg(this.elementShape,this.tensors,e);return oi((()=>{const e=this.tensors.map((e=>Xl(e,r)));return Gd(e,0)}))}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(0===this.size())throw new Error("Trying to pop from an empty list.");const n=Fg(this.elementShape,this.tensors,e),r=this.tensors.pop();return r.kept=!1,$g(r.shape,e,"TensorList shape mismatch: "),Xl(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if($g(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");ii(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(-1!==this.maxNumElements&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);const t=new zg([],this.elementShape,this.elementDtype,this.maxNumElements);t.tensors.length=e;for(let n=0;n<Math.min(this.tensors.length,e);++n)t.tensors[n]=this.tensors[n];return t}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(null==this.tensors[e])throw new Error(`element at index ${e} is null.`);$g(this.tensors[e].shape,t,"TensorList shape mismatch: ");const r=Fg(this.elementShape,this.tensors,t);return Xl(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||-1!==this.maxNumElements&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);$g(this.elementShape,t.shape,"TensorList shape mismatch: "),ii(t),null!=this.tensors[e]&&(this.tensors[e].kept=!1),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);$g(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());const r=Fg(this.elementShape,this.tensors,n);return 0===e.length?qo([],[0].concat(r)):oi((()=>{const t=e.map((e=>Xl(this.tensors[e],r)));return Gd(t,0)}))}concat(e,t){if(e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);$g(this.elementShape,t,"TensorList shape mismatch: ");const n=Fg(this.elementShape,this.tensors,t);return 0===this.size()?qo([],[0].concat(n)):oi((()=>{const e=this.tensors.map((e=>Xl(e,n)));return ec(e,0)}))}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const Bg=async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{const r=Hm("thenBranch",e,t,n),a=Hm("elseBranch",e,t,n),o=Hm("cond",e,t,n),s=Hm("args",e,t,n);return(await o.data())[0]?n.functionMap[r].executeFunctionAsync(s,n.tensorArrayMap,n.tensorListMap):n.functionMap[a].executeFunctionAsync(s,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{const r=Hm("body",e,t,n),a=Hm("cond",e,t,n),o=Hm("args",e,t,n),s=await n.functionMap[a].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap),i=o.map((e=>e.id));let u=await s[0].data();s.forEach((e=>{e.kept||-1!==i.indexOf(e.id)||e.dispose()}));let l=o;for(;u[0];){const e=l;l=await n.functionMap[r].executeFunctionAsync(l,n.tensorArrayMap,n.tensorListMap);const t=l.map((e=>e.id));e.forEach((e=>{e.kept||-1!==i.indexOf(e.id)||-1!==t.indexOf(e.id)||e.dispose()}));const o=await n.functionMap[a].executeFunctionAsync(l,n.tensorArrayMap,n.tensorListMap);u=await o[0].data(),o.forEach((e=>{e.kept||-1!==i.indexOf(e.id)||-1!==t.indexOf(e.id)||e.dispose()}))}return l}case"LoopCond":return[Zm(Hm("pred",e,t,n))];case"Switch":{const r=Hm("pred",e,t,n);let a=Hm("data",e,t,n);return a.kept||(a=Zm(a)),(await r.data())[0]?[void 0,a]:[a,void 0]}case"Merge":{const r=e.inputNames.find((e=>void 0!==qm(e,t,n)));if(r){return[Zm(qm(r,t,n))]}return}case"Enter":{const r=Hm("frameName",e,t,n),a=Hm("tensor",e,t,n);return n.enterFrame(r),[Zm(a)]}case"Exit":{const r=Hm("tensor",e,t,n);return n.exitFrame(),[Zm(r)]}case"NextIteration":{const r=Hm("tensor",e,t,n);return n.nextIteration(),[Zm(r)]}case"TensorArrayV3":{const r=Hm("size",e,t,n),a=Hm("dtype",e,t,n),o=Hm("elementShape",e,t,n),s=Hm("dynamicSize",e,t,n),i=Hm("clearAfterRead",e,t,n),u=Hm("identicalElementShapes",e,t,n),l=Hm("name",e,t,n),c=new Lg(l,a,r,o,u,s,i);return n.addTensorArray(c),[c.idTensor,Di(1)]}case"TensorArrayWriteV3":{const r=Hm("tensorArrayId",e,t,n),a=Hm("index",e,t,n),o=Hm("tensor",e,t,n),s=n.getTensorArray(r.id);return s.write(a,o),[s.idTensor]}case"TensorArrayReadV3":{const r=Hm("tensorArrayId",e,t,n),a=Hm("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{const r=Hm("tensorArrayId",e,t,n),a=Hm("indices",e,t,n),o=Hm("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,o)]}case"TensorArrayScatterV3":{const r=Hm("tensorArrayId",e,t,n),a=Hm("indices",e,t,n),o=Hm("tensor",e,t,n),s=n.getTensorArray(r.id);return s.scatter(a,o),[s.idTensor]}case"TensorArrayConcatV3":{const r=Hm("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),o=Hm("dtype",e,t,n);return[a.concat(o)]}case"TensorArraySplitV3":{const r=Hm("tensorArrayId",e,t,n),a=Hm("tensor",e,t,n),o=Hm("lengths",e,t,n),s=n.getTensorArray(r.id);return s.split(o,a),[s.idTensor]}case"TensorArraySizeV3":{const r=Hm("tensorArrayId",e,t,n);return[Di(n.getTensorArray(r.id).size(),"int32")]}case"TensorArrayCloseV3":{const r=Hm("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{const r=Hm("tensorListId",e,t,n),a=Hm("index",e,t,n),o=Hm("tensor",e,t,n),s=n.getTensorList(r.id);return s.setItem(a,o),[s.idTensor]}case"TensorListGetItem":{const r=Hm("tensorListId",e,t,n),a=Hm("index",e,t,n),o=Hm("elementShape",e,t,n),s=Hm("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,o,s)]}case"TensorListScatterV2":case"TensorListScatter":{const r=Hm("indices",e,t,n),a=function(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);const a=Math.max(...t);if(null!=r&&-1!==r&&a>=r)throw new Error(`Max index must be < array size (${a} vs. ${r})`);const o=new zg([],n,e.dtype,r),s=uf(e,0);return t.forEach(((e,t)=>{o.setItem(e,s[t])})),o}(Hm("tensor",e,t,n),r,Hm("elementShape",e,t,n),Hm("numElements",e,t,n));return n.addTensorList(a),[a.idTensor]}case"TensorListReserve":case"EmptyTensorList":{const r=Hm("elementShape",e,t,n),a=Hm("elementDType",e,t,n);let o;o="TensorListReserve"===e.op?"numElements":"maxNumElements";const s=Hm(o,e,t,n),i=function(e,t,n,r){return new zg([],e,t,r)}(r,a,0,"TensorListReserve"===e.op?-1:s);return n.addTensorList(i),[i.idTensor]}case"TensorListGather":{const r=Hm("tensorListId",e,t,n),a=Hm("indices",e,t,n),o=Hm("elementShape",e,t,n),s=Hm("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,s,o)]}case"TensorListStack":{const r=Hm("tensorListId",e,t,n),a=Hm("elementShape",e,t,n),o=Hm("elementDType",e,t,n),s=Hm("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,o,s)]}case"TensorListFromTensor":{const r=function(e,t,n){const 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 ${n}`);$g(e.shape.slice(1),t,"TensorList shape mismatch: ");const a=uf(e);return new zg(a,t,r)}(Hm("tensor",e,t,n),Hm("elementShape",e,t,n),Hm("elementDType",e,t,n));return n.addTensorList(r),[r.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{const r=Hm("tensorListId",e,t,n),a=n.getTensorList(r.id),o=Hm("dtype",e,t,n),s=Hm("elementShape",e,t,n);return[a.concat(o,s)]}case"TensorListPushBack":{const r=Hm("tensorListId",e,t,n),a=Hm("tensor",e,t,n),o=n.getTensorList(r.id);return o.pushBack(a),[o.idTensor]}case"TensorListPopBack":{const r=Hm("tensorListId",e,t,n),a=Hm("elementShape",e,t,n),o=Hm("elementDType",e,t,n);return[n.getTensorList(r.id).popBack(a,o)]}case"TensorListSplit":{const r=Hm("tensor",e,t,n),a=Hm("elementShape",e,t,n),o=function(e,t,n){let r=0;const a=t.map((e=>(r+=e,r)));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to\n tensor.shape[0], but sum of lengths is\n ${r}, and tensor's shape is: ${e.shape}`);const o=Pg(e.shape.slice(1),n),s=0===r?0:e.size/r,i=oi((()=>{const n=[];e=Xl(e,[1,r,s]);for(let r=0;r<t.length;++r){const i=[0,0===r?0:a[r-1],0],u=[1,t[r],s];n[r]=Xl(nc(e,i,u),o)}return e.dispose(),n})),u=new zg([],n,e.dtype,t.length);for(let e=0;e<i.length;e++)u.setItem(e,i[e]);return u}(r,Hm("lengths",e,t,n),a);return n.addTensorList(o),[o.idTensor]}case"TensorListLength":{const r=Hm("tensorListId",e,t,n);return[Di(n.getTensorList(r.id).size(),"int32")]}case"TensorListResize":{const r=Hm("tensorListId",e,t,n),a=Hm("size",e,t,n),o=n.getTensorList(r.id).resize(a);return n.addTensorList(o),[o.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Vg(e,t,n){const[r,a]=Hm("fusedOps",e,t,n),o="biasadd"===r,s=!o,i="prelu"===a,u="fusedbatchnorm"===r,l=Hm("numArgs",e,t,n);if(o){if(i&&2!==l)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&o&&1!==l)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(u)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported");const c=Hm("strides",e,t,n),p=Xm(e,t,n),d=Hm("dataFormat",e,t,n).toUpperCase(),f=Hm("dilations",e,t,n);let[h,m]=Hm("args",e,t,n);s&&(m=h,h=void 0);return{stride:c,pad:p,dataFormat:d,dilations:f,biasArg:h,preluArg:m,activationFunc:a,leakyreluAlpha:Hm("leakyreluAlpha",e,t,n)}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Ug(e,t,n){return{boxes:Hm("boxes",e,t,n),scores:Hm("scores",e,t,n),maxOutputSize:Hm("maxOutputSize",e,t,n),iouThreshold:Hm("iouThreshold",e,t,n),scoreThreshold:Hm("scoreThreshold",e,t,n),softNmsSigma:Hm("softNmsSigma",e,t,n)}}
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class jg{get id(){return this.handle.id}constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Di(0),this.tensorMap=new Map,ii(this.handle)}clearAndClose(){this.tensorMap.forEach((e=>e.dispose())),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return Di(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);const n=await e.data();return this.tensorMap.forEach((e=>e.dispose())),this.tensorMap.clear(),oi((()=>{const e=uf(t),r=n.length,a=e.length;X(r===a,(()=>`The number of elements doesn't match, keys has ${r} elements, the values has ${a} elements.`));for(let t=0;t<r;t++){const r=n[t],a=e[t];ii(a),this.tensorMap.set(r,a)}return this.handle}))}async find(e,t){this.checkKeyAndValueTensor(e,t);const n=await e.data();return oi((()=>{const e=[];for(let r=0;r<n.length;r++){const a=n[r],o=this.findWithDefault(a,t);e.push(o)}return Gd(e)}))}findWithDefault(e,t){const n=this.tensorMap.get(e);return null!=n?n:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function Wg(e,t,n,r,a=oi){const o=((e,t,n)=>{switch(e.category){case"arithmetic":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[r.add(Hm("a",e,t,n),Hm("b",e,t,n))];case"AddN":return[r.addN(Hm("tensors",e,t,n))];case"FloorMod":case"Mod":return[r.mod(Hm("a",e,t,n),Hm("b",e,t,n))];case"Mul":return[r.mul(Hm("a",e,t,n),Hm("b",e,t,n))];case"RealDiv":case"Div":return[r.div(Hm("a",e,t,n),Hm("b",e,t,n))];case"DivNoNan":return[r.divNoNan(Hm("a",e,t,n),Hm("b",e,t,n))];case"FloorDiv":return[r.floorDiv(Hm("a",e,t,n),Hm("b",e,t,n))];case"Sub":return[r.sub(Hm("a",e,t,n),Hm("b",e,t,n))];case"Minimum":return[r.minimum(Hm("a",e,t,n),Hm("b",e,t,n))];case"Maximum":return[r.maximum(Hm("a",e,t,n),Hm("b",e,t,n))];case"Pow":return[r.pow(Hm("a",e,t,n),Hm("b",e,t,n))];case"SquaredDifference":return[r.squaredDifference(Hm("a",e,t,n),Hm("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"basic_math":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"Abs":case"ComplexAbs":return[r.abs(Hm("x",e,t,n))];case"Acos":return[r.acos(Hm("x",e,t,n))];case"Acosh":return[r.acosh(Hm("x",e,t,n))];case"Asin":return[r.asin(Hm("x",e,t,n))];case"Asinh":return[r.asinh(Hm("x",e,t,n))];case"Atan":return[r.atan(Hm("x",e,t,n))];case"Atan2":return[r.atan2(Hm("x",e,t,n),Hm("y",e,t,n))];case"Atanh":return[r.atanh(Hm("x",e,t,n))];case"Ceil":return[r.ceil(Hm("x",e,t,n))];case"Complex":return[r.complex(Hm("real",e,t,n),Hm("imag",e,t,n))];case"Cos":return[r.cos(Hm("x",e,t,n))];case"Cosh":return[r.cosh(Hm("x",e,t,n))];case"Elu":return[r.elu(Hm("x",e,t,n))];case"Erf":return[r.erf(Hm("x",e,t,n))];case"Exp":return[r.exp(Hm("x",e,t,n))];case"Expm1":return[r.expm1(Hm("x",e,t,n))];case"Floor":return[r.floor(Hm("x",e,t,n))];case"Log":return[r.log(Hm("x",e,t,n))];case"Log1p":return[r.log1p(Hm("x",e,t,n))];case"Imag":return[r.imag(Hm("x",e,t,n))];case"Neg":return[r.neg(Hm("x",e,t,n))];case"Reciprocal":return[r.reciprocal(Hm("x",e,t,n))];case"Real":return[r.real(Hm("x",e,t,n))];case"Relu":return[r.relu(Hm("x",e,t,n))];case"Round":return[r.round(Hm("x",e,t,n))];case"Selu":return[r.selu(Hm("x",e,t,n))];case"Sigmoid":return[r.sigmoid(Hm("x",e,t,n))];case"Sin":return[r.sin(Hm("x",e,t,n))];case"Sign":return[r.sign(Hm("x",e,t,n))];case"Sinh":return[r.sinh(Hm("x",e,t,n))];case"Softplus":return[r.softplus(Hm("x",e,t,n))];case"Sqrt":return[r.sqrt(Hm("x",e,t,n))];case"Square":return[r.square(Hm("x",e,t,n))];case"Tanh":return[r.tanh(Hm("x",e,t,n))];case"Tan":return[r.tan(Hm("x",e,t,n))];case"ClipByValue":return[r.clipByValue(Hm("x",e,t,n),Hm("clipValueMin",e,t,n),Hm("clipValueMax",e,t,n))];case"Relu6":return[r.relu6(Hm("x",e,t,n))];case"Rsqrt":return[r.rsqrt(qm(e.inputNames[0],t,n))];case"LeakyRelu":return[r.leakyRelu(Hm("x",e,t,n),Hm("alpha",e,t,n))];case"Prelu":return[r.prelu(Hm("x",e,t,n),Hm("alpha",e,t,n))];case"IsNan":return[r.isNaN(qm(e.inputNames[0],t,n))];case"IsInf":return[r.isInf(qm(e.inputNames[0],t,n))];case"IsFinite":return[r.isFinite(qm(e.inputNames[0],t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"control":return Bg(e,t,n);case"convolution":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"Conv1D":{const a=Hm("stride",e,t,n),o=Hm("pad",e,t,n),s=Hm("dataFormat",e,t,n).toUpperCase(),i=Hm("dilation",e,t,n);return[r.conv1d(Hm("x",e,t,n),Hm("filter",e,t,n),a,o,s,i)]}case"Conv2D":{const a=Hm("strides",e,t,n),o=Xm(e,t,n),s=Hm("dataFormat",e,t,n).toUpperCase(),i=Hm("dilations",e,t,n);return[r.conv2d(Hm("x",e,t,n),Hm("filter",e,t,n),[a[1],a[2]],o,s,[i[1],i[2]])]}case"_FusedConv2D":{const{stride:a,pad:o,dataFormat:s,dilations:i,biasArg:u,preluArg:l,activationFunc:c,leakyreluAlpha:p}=Vg(e,t,n);return[r.fused.conv2d({x:Hm("x",e,t,n),filter:Hm("filter",e,t,n),strides:[a[1],a[2]],pad:o,dataFormat:s,dilations:[i[1],i[2]],bias:u,activation:c,preluActivationWeights:l,leakyreluAlpha:p})]}case"FusedDepthwiseConv2dNative":{const{stride:a,pad:o,dataFormat:s,dilations:i,biasArg:u,preluArg:l,activationFunc:c,leakyreluAlpha:p}=Vg(e,t,n);return[r.fused.depthwiseConv2d({x:Hm("x",e,t,n),filter:Hm("filter",e,t,n),strides:[a[1],a[2]],pad:o,dataFormat:s,dilations:[i[1],i[2]],bias:u,activation:c,preluActivationWeights:l,leakyreluAlpha:p})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{const a=Hm("outputShape",e,t,n),o=Hm("strides",e,t,n),s=Xm(e,t,n);return[r.conv2dTranspose(Hm("x",e,t,n),Hm("filter",e,t,n),a,[o[1],o[2]],s)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{const a=Hm("strides",e,t,n),o=Xm(e,t,n),s=Hm("dilations",e,t,n),i=Hm("dataFormat",e,t,n).toUpperCase();return[r.depthwiseConv2d(Hm("input",e,t,n),Hm("filter",e,t,n),[a[1],a[2]],o,i,[s[1],s[2]])]}case"Conv3D":{const a=Hm("strides",e,t,n),o=Hm("pad",e,t,n),s=Hm("dataFormat",e,t,n).toUpperCase(),i=Hm("dilations",e,t,n);return[r.conv3d(Hm("x",e,t,n),Hm("filter",e,t,n),[a[1],a[2],a[3]],o,s,[i[1],i[2],i[3]])]}case"AvgPool":{const a=Hm("strides",e,t,n),o=Hm("pad",e,t,n),s=Hm("kernelSize",e,t,n);return[r.avgPool(Hm("x",e,t,n),[s[1],s[2]],[a[1],a[2]],o)]}case"MaxPool":{const a=Hm("strides",e,t,n),o=Hm("pad",e,t,n),s=Hm("kernelSize",e,t,n);return[r.maxPool(Hm("x",e,t,n),[s[1],s[2]],[a[1],a[2]],o)]}case"MaxPoolWithArgmax":{const a=Hm("strides",e,t,n),o=Hm("pad",e,t,n),s=Hm("kernelSize",e,t,n),i=Hm("includeBatchInIndex",e,t,n),{result:u,indexes:l}=r.maxPoolWithArgmax(Hm("x",e,t,n),[s[1],s[2]],[a[1],a[2]],o,i);return[u,l]}case"AvgPool3D":{const a=Hm("strides",e,t,n),o=Hm("pad",e,t,n),s=Hm("kernelSize",e,t,n);return[r.avgPool3d(Hm("x",e,t,n),[s[1],s[2],s[3]],[a[1],a[2],a[3]],o)]}case"MaxPool3D":{const a=Hm("strides",e,t,n),o=Hm("pad",e,t,n),s=Hm("kernelSize",e,t,n);return[r.maxPool3d(Hm("x",e,t,n),[s[1],s[2],s[3]],[a[1],a[2],a[3]],o)]}case"Dilation2D":{const a=Hm("strides",e,t,n),o=Hm("pad",e,t,n),s=Hm("dilations",e,t,n),i=a[1],u=a[2],l=s[1],c=s[2];return[r.dilation2d(Hm("x",e,t,n),Hm("filter",e,t,n),[i,u],o,[l,c],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"creation":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"Fill":{const a=Hm("shape",e,t,n),o=Hm("dtype",e,t,n),s=Hm("value",e,t,n);return[r.fill(a,s,o)]}case"LinSpace":{const a=Hm("start",e,t,n),o=Hm("stop",e,t,n),s=Hm("num",e,t,n);return[r.linspace(a,o,s)]}case"Multinomial":{const a=Hm("logits",e,t,n),o=Hm("numSamples",e,t,n),s=Hm("seed",e,t,n);return[r.multinomial(a,o,s)]}case"OneHot":{const a=Hm("indices",e,t,n),o=Hm("depth",e,t,n),s=Hm("onValue",e,t,n),i=Hm("offValue",e,t,n),u=Hm("dtype",e,t,n);return[r.oneHot(a,o,s,i,u)]}case"Ones":return[r.ones(Hm("shape",e,t,n),Hm("dtype",e,t,n))];case"OnesLike":return[r.onesLike(Hm("x",e,t,n))];case"RandomStandardNormal":return[r.randomStandardNormal(Hm("shape",e,t,n),Hm("dtype",e,t,n),Hm("seed",e,t,n))];case"RandomUniform":return[r.randomUniform(Hm("shape",e,t,n),Hm("minval",e,t,n),Hm("maxval",e,t,n),Hm("dtype",e,t,n))];case"RandomUniformInt":return[r.randomUniformInt(Hm("shape",e,t,n),Hm("minval",e,t,n),Hm("maxval",e,t,n),Hm("seed",e,t,n))];case"Range":{const a=Hm("start",e,t,n),o=Hm("stop",e,t,n),s=Hm("step",e,t,n);return[r.range(a,o,s,Hm("dtype",e,t,n))]}case"TruncatedNormal":{const 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a.image.nonMaxSuppressionAsync(r,o,s,i,u)]}case"Where":{const r=a.cast(Hm("condition",e,t,n),"bool"),o=[await a.whereAsync(r)];return r.dispose(),o}case"ListDiff":return a.setdiff1dAsync(Hm("x",e,t,n),Hm("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n);case"evaluation":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"LowerBound":{const a=Hm("sortedSequence",e,t,n),o=Hm("values",e,t,n);return[r.lowerBound(a,o)]}case"TopKV2":{const a=Hm("x",e,t,n),o=Hm("k",e,t,n),s=Hm("sorted",e,t,n),i=r.topk(a,o,s);return[i.values,i.indices]}case"UpperBound":{const a=Hm("sortedSequence",e,t,n),o=Hm("values",e,t,n);return[r.upperBound(a,o)]}case"Unique":{const a=Hm("x",e,t,n),o=r.unique(a);return[o.values,o.indices]}case"UniqueV2":{const a=Hm("x",e,t,n),o=Hm("axis",e,t,n),s=r.unique(a,o);return[s.values,s.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"image":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"ResizeBilinear":{const 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a=Hm("default",e,t,n);return[qm(e.name,t,n)||a];case"Placeholder":return[qm(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":case"Snapshot":return[Zm(Hm("x",e,t,n))];case"IdentityN":return Hm("x",e,t,n).map((e=>Zm(e)));case"Shape":return[r.tensor1d(Hm("x",e,t,n).shape,"int32")];case"ShapeN":return Hm("x",e,t,n).map((e=>r.tensor1d(e.shape)));case"Size":return[r.scalar(Hm("x",e,t,n).size,"int32")];case"Rank":return[r.scalar(Hm("x",e,t,n).rank,"int32")];case"NoOp":return[r.scalar(1)];case"Print":const o=Hm("x",e,t,n),s=Hm("data",e,t,n),i=Hm("message",e,t,n),u=Hm("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(i);for(let e=0;e<s.length;e++)console.log(Array.prototype.slice.call(s[e].dataSync()).slice(0,u));return[o];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"logical":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"Equal":return[r.equal(Hm("a",e,t,n),Hm("b",e,t,n))];case"NotEqual":return[r.notEqual(Hm("a",e,t,n),Hm("b",e,t,n))];case"Greater":return[r.greater(Hm("a",e,t,n),Hm("b",e,t,n))];case"GreaterEqual":return[r.greaterEqual(Hm("a",e,t,n),Hm("b",e,t,n))];case"Less":return[r.less(Hm("a",e,t,n),Hm("b",e,t,n))];case"LessEqual":return[r.lessEqual(Hm("a",e,t,n),Hm("b",e,t,n))];case"LogicalAnd":return[r.logicalAnd(Hm("a",e,t,n),Hm("b",e,t,n))];case"LogicalNot":return[r.logicalNot(Hm("a",e,t,n))];case"LogicalOr":return[r.logicalOr(Hm("a",e,t,n),Hm("b",e,t,n))];case"Select":case"SelectV2":return[r.where(Hm("condition",e,t,n),Hm("a",e,t,n),Hm("b",e,t,n))];case"BitwiseAnd":return[r.bitwiseAnd(Hm("a",e,t,n),Hm("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"matrices":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[r.matMul(Hm("a",e,t,n),Hm("b",e,t,n),Hm("transposeA",e,t,n),Hm("transposeB",e,t,n))];case"Einsum":return[r.einsum(Hm("equation",e,t,n),...Hm("tensors",e,t,n))];case"Transpose":return[r.transpose(Hm("x",e,t,n),Hm("perm",e,t,n))];case"_FusedMatMul":const[a,o]=Hm("fusedOps",e,t,n),s="biasadd"===a,i="prelu"===o,u=Hm("numArgs",e,t,n),l=Hm("leakyreluAlpha",e,t,n);if(s){if(i&&2!==u)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&1!==u)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}const[c,p]=Hm("args",e,t,n);return[r.fused.matMul({a:Hm("a",e,t,n),b:Hm("b",e,t,n),transposeA:Hm("transposeA",e,t,n),transposeB:Hm("transposeB",e,t,n),bias:c,activation:o,preluActivationWeights:p,leakyreluAlpha:l})];case"MatrixBandPart":return[r.linalg.bandPart(Hm("a",e,t,n),Hm("numLower",e,t,n),Hm("numUpper",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"normalization":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"EuclideanNorm":return[r.euclideanNorm(Hm("x",e,t,n),Hm("axis",e,t,n),Hm("keepDims",e,t,n))];case"FusedBatchNorm":case"FusedBatchNormV2":case"FusedBatchNormV3":return[r.batchNorm(Hm("x",e,t,n),Hm("mean",e,t,n),Hm("variance",e,t,n),Hm("offset",e,t,n),Hm("scale",e,t,n),Hm("epsilon",e,t,n))];case"LRN":return[r.localResponseNormalization(Hm("x",e,t,n),Hm("radius",e,t,n),Hm("bias",e,t,n),Hm("alpha",e,t,n),Hm("beta",e,t,n))];case"Softmax":return[r.softmax(Hm("x",e,t,n))];case"LogSoftmax":return[r.logSoftmax(Hm("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"ragged":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"RaggedGather":{const{outputNestedSplits:a,outputDenseValues:o}=r.raggedGather(Hm("paramsNestedSplits",e,t,n),Hm("paramsDenseValues",e,t,n),Hm("indices",e,t,n),Hm("outputRaggedRank",e,t,n));return a.concat(o)}case"RaggedRange":{const{rtNestedSplits:a,rtDenseValues:o}=r.raggedRange(Hm("starts",e,t,n),Hm("limits",e,t,n),Hm("splits",e,t,n));return[a,o]}case"RaggedTensorToTensor":return[r.raggedTensorToTensor(Hm("shape",e,t,n),Hm("values",e,t,n),Hm("defaultValue",e,t,n),Hm("rowPartitionTensors",e,t,n),Hm("rowPartitionTypes",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"reduction":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"Max":{const a=Hm("axis",e,t,n),o=Hm("keepDims",e,t,n);return[r.max(Hm("x",e,t,n),a,o)]}case"Mean":{const a=Hm("axis",e,t,n),o=Hm("keepDims",e,t,n);return[r.mean(Hm("x",e,t,n),a,o)]}case"Min":{const a=Hm("axis",e,t,n),o=Hm("keepDims",e,t,n);return[r.min(Hm("x",e,t,n),a,o)]}case"Sum":{const a=Hm("axis",e,t,n),o=Hm("keepDims",e,t,n);return[r.sum(Hm("x",e,t,n),a,o)]}case"All":{const a=Hm("axis",e,t,n),o=Hm("keepDims",e,t,n);return[r.all(Hm("x",e,t,n),a,o)]}case"Any":{const a=Hm("axis",e,t,n),o=Hm("keepDims",e,t,n);return[r.any(Hm("x",e,t,n),a,o)]}case"ArgMax":{const a=Hm("axis",e,t,n);return[r.argMax(Hm("x",e,t,n),a)]}case"ArgMin":{const a=Hm("axis",e,t,n);return[r.argMin(Hm("x",e,t,n),a)]}case"Prod":{const a=Hm("axis",e,t,n),o=Hm("keepDims",e,t,n);return[r.prod(Hm("x",e,t,n),a,o)]}case"Cumprod":{const a=Hm("axis",e,t,n),o=Hm("exclusive",e,t,n),s=Hm("reverse",e,t,n);return[r.cumprod(Hm("x",e,t,n),a,o,s)]}case"Cumsum":{const a=Hm("axis",e,t,n),o=Hm("exclusive",e,t,n),s=Hm("reverse",e,t,n);return[r.cumsum(Hm("x",e,t,n),a,o,s)]}case"Bincount":const a=Hm("x",e,t,n),o=Hm("weights",e,t,n),s=Hm("size",e,t,n);return[r.bincount(a,o,s)];case"DenseBincount":{const a=Hm("x",e,t,n),o=Hm("weights",e,t,n),s=Hm("size",e,t,n),i=Hm("binaryOutput",e,t,n);return[r.denseBincount(a,o,s,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"slice_join":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"ConcatV2":case"Concat":{const 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a=Hm("axis",e,t,n),o=Hm("tensors",e,t,n),s=o[0].shape,i=r.squeeze(o[0]).shape,u=o.map((e=>{const t=re(e.shape,s);if(!t&&!re(r.squeeze(e).shape,i))throw new Error("the input tensors shape does not match");return t?e:r.reshape(e,s)}));return[r.stack(u,a)]}));case"Unpack":{const a=Hm("axis",e,t,n),o=Hm("tensor",e,t,n);return r.unstack(o,a)}case"Tile":{const a=Hm("reps",e,t,n);return[r.tile(Hm("x",e,t,n),a)]}case"Split":case"SplitV":{const a=Hm("axis",e,t,n),o=Hm("numOrSizeSplits",e,t,n),s=Hm("x",e,t,n);return r.split(s,o,a)}case"ScatterNd":{const a=Hm("indices",e,t,n),o=Hm("values",e,t,n),s=Hm("shape",e,t,n);return[r.scatterND(a,o,s)]}case"GatherNd":{const a=Hm("x",e,t,n),o=Hm("indices",e,t,n);return[r.gatherND(a,o)]}case"SparseToDense":{const a=Hm("sparseIndices",e,t,n),o=Hm("outputShape",e,t,n),s=Hm("sparseValues",e,t,n),i=Hm("defaultValue",e,t,n);return[r.sparseToDense(a,s,o,s.dtype===i.dtype?i:r.cast(i,s.dtype))]}case"TensorScatterUpdate":{const a=Hm("indices",e,t,n),o=Hm("values",e,t,n),s=Hm("tensor",e,t,n);return[r.tensorScatterUpdate(s,a,o)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"sparse":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"SparseFillEmptyRows":{const{outputIndices:a,outputValues:o,emptyRowIndicator:s,reverseIndexMap:i}=r.sparse.sparseFillEmptyRows(Hm("indices",e,t,n),Hm("values",e,t,n),Hm("denseShape",e,t,n),Hm("defaultValue",e,t,n));return[a,o,s,i]}case"SparseReshape":{const{outputIndices:a,outputShape:o}=r.sparse.sparseReshape(Hm("inputIndices",e,t,n),Hm("inputShape",e,t,n),Hm("newShape",e,t,n));return[a,o]}case"SparseSegmentMean":return[r.sparse.sparseSegmentMean(Hm("data",e,t,n),Hm("indices",e,t,n),Hm("segmentIds",e,t,n))];case"SparseSegmentSum":return[r.sparse.sparseSegmentSum(Hm("data",e,t,n),Hm("indices",e,t,n),Hm("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"spectral":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"FFT":return[r.fft(Hm("x",e,t,n))];case"IFFT":return[r.ifft(Hm("x",e,t,n))];case"RFFT":return[r.rfft(Hm("x",e,t,n))];case"IRFFT":return[r.irfft(Hm("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"string":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"StaticRegexReplace":return[r.string.staticRegexReplace(Hm("input",e,t,n),Hm("pattern",e,t,n),Hm("rewrite",e,t,n),Hm("replaceGlobal",e,t,n))];case"StringNGrams":{const{nGrams:a,nGramsSplits:o}=r.string.stringNGrams(Hm("data",e,t,n),Hm("dataSplits",e,t,n),Hm("separator",e,t,n),Hm("nGramWidths",e,t,n),Hm("leftPad",e,t,n),Hm("rightPad",e,t,n),Hm("padWidth",e,t,n),Hm("preserveShortSequences",e,t,n));return[a,o]}case"StringSplit":{const{indices:a,values:o,shape:s}=r.string.stringSplit(Hm("input",e,t,n),Hm("delimiter",e,t,n),Hm("skipEmpty",e,t,n));return[a,o,s]}case"StringToHashBucketFast":return[r.string.stringToHashBucketFast(Hm("input",e,t,n),Hm("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"transformation":return a((()=>((e,t,n,r=P)=>{switch(e.op){case"Cast":return[r.cast(Hm("x",e,t,n),Hm("dtype",e,t,n))];case"ExpandDims":{const a=Hm("axis",e,t,n);return[r.expandDims(Hm("x",e,t,n),a)]}case"Squeeze":{const a=Hm("axis",e,t,n);return[r.squeeze(Hm("x",e,t,n),a)]}case"Reshape":return[r.reshape(Hm("x",e,t,n),Hm("shape",e,t,n))];case"EnsureShape":return[r.ensureShape(Hm("x",e,t,n),Hm("shape",e,t,n))];case"MirrorPad":return[r.mirrorPad(Hm("x",e,t,n),Hm("padding",e,t,n),Hm("mode",e,t,n))];case"PadV2":case"Pad":return[r.pad(Hm("x",e,t,n),Hm("padding",e,t,n),Hm("constantValue",e,t,n))];case"SpaceToBatchND":{const a=Hm("blockShape",e,t,n),o=Hm("paddings",e,t,n);return[r.spaceToBatchND(Hm("x",e,t,n),a,o)]}case"BatchToSpaceND":{const a=Hm("blockShape",e,t,n),o=Hm("crops",e,t,n);return[r.batchToSpaceND(Hm("x",e,t,n),a,o)]}case"DepthToSpace":{const a=Hm("blockSize",e,t,n),o=Hm("dataFormat",e,t,n).toUpperCase();return[r.depthToSpace(Hm("x",e,t,n),a,o)]}case"BroadcastTo":return[r.broadcastTo(Hm("x",e,t,n),Hm("shape",e,t,n))];case"BroadcastArgs":return[r.broadcastArgs(Hm("s0",e,t,n),Hm("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"hash_table":return(async(e,t,n,r)=>{switch(e.op){case"HashTable":case"HashTableV2":{const a=r.getHashTableHandleByName(e.name);if(null!=a)return[a];{const a=Hm("keyDType",e,t,n),o=Hm("valueDType",e,t,n),s=new jg(a,o);return r.addHashTable(e.name,s),[s.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{const a=Hm("tableHandle",e,t,n,r),o=Hm("keys",e,t,n),s=Hm("values",e,t,n),i=r.getHashTableById(a.id);return[await i.import(o,s)]}case"LookupTableFind":case"LookupTableFindV2":{const a=Hm("tableHandle",e,t,n,r),o=Hm("keys",e,t,n),s=Hm("defaultValue",e,t,n),i=r.getHashTableById(a.id);return[await i.find(o,s)]}case"LookupTableSize":case"LookupTableSizeV2":{const a=Hm("tableHandle",e,t,n,r);return[r.getHashTableById(a.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n,r);case"custom":const o=Wm(e.op);if(o&&o.customExecutor)return o.customExecutor(new Cg(e,t,n));throw TypeError(`Custom op ${e.op} is not registered.`);default:throw TypeError(`Unknown op '${e.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return Fe(o)?o.then((e=>[].concat(e))):[].concat(o)}class Hg{constructor(e={},t={},n={},r={},a){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=r,this.parseNodeNameCache=a,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){const e=[];for(let t=0;t<this.contexts.length-1;t++){const n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map((e=>0===e.id&&0===e.iterationId?"":`${e.frameName}-${e.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))throw new Error("Cannot exit frame, the context is empty");this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift()}nextIteration(){if(!(this.contexts&&this.contexts.length>0))throw new Error("Cannot increase frame iteration, the context is empty");{this.contexts=this.contexts.slice(),this.lastId++;const 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))}}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(const t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(const t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}}
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function qg(e,t,n,r){const a=new Set,o=[];let s=null,i=null;const u=new Set,l=new Set(Object.keys(e).map((e=>Ym(e)[0])));r=r||[];const c=new Set(r.map((e=>Ym(e.name)[0]))),p=[...t];for(;p.length>0;){const e=p.pop();(Zg(e)||Jg(e)||ey(e))&&null==s&&(s=e,i=s.children.map((e=>e.name)).filter((e=>a.has(e)))),a.add(e.name),null==n[e.name]&&(l.has(e.name)||c.has(e.name)||(0!==e.inputs.length?e.inputs.forEach((e=>{u.has(e.name)||(u.add(e.name),p.push(e))})):o.push(e.name)))}return{inputs:e,outputs:t,usedNodes:a,missingInputs:o,dynamicNode:s,syncInputs:i}}function Gg(e,t){const{usedNodes:n,inputs:r}=t,a=Object.keys(r).map((e=>Ym(e)[0])).map((t=>e.nodes[t])),o=e.initNodes||[],s=e=>n.has("string"==typeof e?e:e.name);function i(e){return[...new Map(e.map((e=>[e.name,e]))).values()]}const u=i([...a,...e.weights,...o]).filter(s),l=i([...u,...Object.values(e.nodes)]).filter(s),c=new Map(l.map((e=>[e.name,e]))),p={};for(const e of l){p[e.name]=p[e.name]||0;for(const t of e.children)s(t)||(p[t.name]=Number.POSITIVE_INFINITY),p[t.name]=(p[t.name]||0)+1}const d=Object.entries(p).filter((([,e])=>0===e)).map((([e])=>e)),f=[...d];for(;d.length>0;){const e=d.pop(),t=c.get(e);for(const e of t.children.filter(s))0==--p[e.name]&&(f.push(e.name),d.push(e.name))}const h=function(e,t){const n=new Map(e.map((e=>[e.name,e]))),r=t.map((e=>e.name)),a=new Set(r);for(;r.length>0;){const e=r.pop(),t=n.get(e);for(const e of t.children)n.has(e.name)&&!a.has(e.name)&&(a.add(e.name),r.push(e.name))}const o=e.filter((e=>a.has(e.name)));return o}(f.map((e=>c.get(e))),u);return function(e,t){const n=new Map(e.map(((e,t)=>[e.name,t]))),r=new Set(t.map((e=>e.name))),a=e=>r.has("string"==typeof e?e:e.name),o=new Set(e.map((e=>e.name))),s=e=>o.has("string"==typeof e?e:e.name);for(const t of e){for(const e of t.children.filter(s)){if(!n.has(e.name))throw new Kg(`Child ${e.name} of node ${t.name} is unreachable.`);if(n.get(t.name)>n.get(e.name))throw new Kg(`Node ${t.name} is scheduled to run after its child ${e.name}.`)}if(!a(t))for(const e of t.inputs){if(!n.has(e.name))throw new Kg(`Input ${e.name} of node ${t.name} is unreachable.`);if(n.get(e.name)>n.get(t.name))throw new Kg(`Node ${t.name} is scheduled to run before its input ${e.name}.`)}}}(h,u),h}class Kg extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}}const Qg=new Set(["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"]),Yg=new Set(["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"]),Xg=new Set(["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"]);function Zg(e){return Qg.has(e.op)}function Jg(e){return Yg.has(e.op)}function ey(e){return Xg.has(e.op)}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
class ty{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){const t=Object.keys(e).map((t=>e[t].map((e=>e.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=>{const t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t}))}get functions(){return Object.keys(this._functions).reduce(((e,t)=>(e[t]=this._functions[t].signature,e)),{})}constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,null!=e.functions&&Object.keys(e.functions).forEach((t=>{this._functionExecutorMap[t]=new ty(e.functions[t],this)}))}getCompilationKey(e,t){const n=e.map((e=>e.name)).sort(),r=t.map((e=>e.name)).sort();return n.join(this.SEPARATOR)+"--"+r.join(this.SEPARATOR)}compile(e,t){const n=qg(e,t,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:a,syncInputs:o}=n;if(null!=a)throw new Error(`This execution contains the node '${a.name}', which has the dynamic op '${a.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${o}]`);if(r.length>0){const n=t.map((e=>e.name)),a=Object.keys(e);throw new Error(`Cannot compute the outputs [${n}] from the provided inputs [${a}]. Missing the following inputs: [${r}]`)}const s=Gg(this.graph,n),i=function(e){const t=new Map(e.map(((e,t)=>[e.name,t]))),n=Number.MAX_SAFE_INTEGER,r=e.map(((e,t)=>Zg(e)?n:t)),a=e=>{const n=r[t.get(e.name)];return null==n?-1:n},o=e.map(((e,t)=>e.children.map(a).reduce(((e,t)=>Math.max(e,t)),r[t]))),s=new Map;for(let t=0;t<e.length;++t){const r=o[t];if(r===n)continue;const a=e[t],i=e[r];s.has(i.name)||s.set(i.name,[]),s.get(i.name).push(a)}return s}(s);return{orderedNodes:s,nodeLiveUntilMap:i}}cloneAndKeepTensor(e){if(null==e)return null;const t=e.clone();return ii(t),t}cloneTensorList(e){if(!e)return null;const t=e.map((e=>this.cloneAndKeepTensor(e)));return t}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map((([e,t])=>[e,this.cloneTensorList(t)])))}execute(e,t){this.disposeIntermediateTensors(),e=this.mapInputs(e);const n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);const r=n.map((e=>this.graph.nodes[Ym(e)[0]])),a=t.map((e=>Ym(e)[0])),o=new Set(a);let s=a.map((e=>this.graph.nodes[e]));0===s.length&&(s=this._outputs);const i=this.getCompilationKey(r,s);let u=this.compiledMap.get(i);null==u&&(u=this.compile(e,s),this.compiledMap.set(i,u));try{this.keepIntermediateTensors=Be().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){this.keepIntermediateTensors=!1,console.warn(e.message)}const l={},c={};return oi((()=>{const n=new Hg(this.weightMap,l,c,this.functionExecutorMap,this.parseNodeNameCache),r=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach((t=>{const[a,o]=Ym(t,n),s=[];s[o]=e[t],r[a]=s,this.keepIntermediateTensors&&(this.clonedTensorsMap[a]=this.cloneTensorList(s))}));const a=this.getFrozenTensorIds(r),{orderedNodes:s,nodeLiveUntilMap:i}=u;for(const e of s){if(r[e.name])continue;const t=Wg(e,r,n,this._resourceManager);if(Fe(t))throw new Error(`The execution of the op '${e.op}' returned a promise. Please use model.executeAsync() instead.`);r[e.name]=t,this.keepIntermediateTensors&&(this.clonedTensorsMap[e.name]=this.cloneTensorList(t)),this.checkTensorForDisposalWithNodeLiveUntilInfo(e,r,n,a,o,i.get(e.name))}return null==this.parent&&n.dispose(a),t.map((e=>qm(e,r,n)))}))}getFrozenTensorIds(e){const t=[].concat.apply([],Object.keys(e).map((t=>e[t])).map((e=>e.map((e=>e.id)))));return new Set(t)}checkTensorForDisposal(e,t,n,r,a,o,s){if(!Zg(t)&&!o.has(e)){for(const r of n[e])null!=r&&(s[r.id]=(s[r.id]||0)+t.children.length);for(const e of t.inputs){if(Zg(e))continue;const t=Gm(e.name,n,r);if(null!=t)for(const e of t){if(!e||e.kept||a.has(e.id))continue;const t=s[e.id];1===t?(e.dispose(),delete s[e.id]):null!=t&&s[e.id]--}}}}checkTensorForDisposalWithNodeLiveUntilInfo(e,t,n,r,a,o){function s(e){return Zg(e)||a.has(e.name)}if(!Zg(e)&&null!=o)for(const e of o){if(s(e))continue;const a=Gm(e.name,t,n);for(const e of a)!e||e.kept||r.has(e.id)||e.dispose()}}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach((e=>{for(const t of e)t&&!t.isDisposed&&t.dispose()})),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(e,t,n=!1,r={},a={}){this.disposeIntermediateTensors(),n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepIntermediateTensors=Be().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){this.keepIntermediateTensors=!1,console.warn(e.message)}const o=new Hg(this.weightMap,r,a,this.functionExecutorMap,this.parseNodeNameCache);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));const s=await this.executeWithControlFlow(e,o,t,n),i=t.map((e=>qm(e,s,o))),u=i.map((e=>e.id)),l=Object.keys(e).map((t=>e[t].id)),c=new Set([...u,...l,...this.weightIds]);return Object.values(s).forEach((e=>{e.forEach((e=>{!e||e.isDisposed||c.has(e.id)||e.dispose()}))})),null==this.parent&&o.dispose(c),i}async executeFunctionAsync(e,t,n){const r=e.reduce(((e,t,n)=>(e[this.inputs[n].name]=t,e)),{});return this._executeAsync(r,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,r){const a=Object.keys(e),o=a.map((e=>this.graph.nodes[Ym(e)[0]])),s=n.map((e=>Ym(e)[0])),i=new Set(s);let u=s.map((e=>this.graph.nodes[e]));0===u.length&&(u=this._outputs);const{usedNodes:l,missingInputs:c,dynamicNode:p,syncInputs:d}=qg(e,u,this.weightMap,this._initNodes),f=[...o,...this.graph.weights,...this._initNodes||[]].map((e=>({node:e,contexts:t.currentContext}))),h=Object.assign({},this.weightMap);Object.keys(e).forEach((t=>{const[n,r]=Ym(t),a=[];a[r]=e[t],h[n]=a}));const m={},g=this.getFrozenTensorIds(h),y={};for(;f.length>0;){const e=this.processStack(o,f,t,h,y,g,i,m,l);await Promise.all(e)}null!=p||r||console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");const b=u.filter((e=>!Zg(e)&&!qm(e.name,h,t))).map((e=>e.name));if(b.length>0){let e="";throw null!=p&&(e=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${d}]`),new Error(`Cannot compute the outputs [${b}] from the provided inputs [${a}]. Consider providing the following inputs: [${c}]. ${e}`)}return h}processStack(e,t,n,r,a,o,s,i,u){const l=[];for(;t.length>0;){const e=t.pop();n.currentContext=e.contexts;let c="";if("Enter"===e.node.op&&Hm("isConstant",e.node,r,n)&&([c]=Km(e.node.name,n)),null==r[e.node.name]){const p=Wg(e.node,r,n,this._resourceManager);c||([c]=Km(e.node.name,n));const d=n.currentContext;Fe(p)?l.push(p.then((l=>(r[c]=l,this.keepIntermediateTensors&&(this.clonedTensorsMap[c]=this.cloneTensorList(l)),n.currentContext=d,this.checkTensorForDisposal(c,e.node,r,n,o,s,i),this.processChildNodes(e.node,t,n,r,a,u),l)))):(r[c]=p,this.keepIntermediateTensors&&(this.clonedTensorsMap[c]=this.cloneTensorList(p)),this.checkTensorForDisposal(c,e.node,r,n,o,s,i),this.processChildNodes(e.node,t,n,r,a,u))}else this.processChildNodes(e.node,t,n,r,a,u)}return l}processChildNodes(e,t,n,r,a,o){e.children.forEach((e=>{const[s]=Km(e.name,n);!a[s]&&o.has(e.name)&&("Merge"===e.op?e.inputNames.some((e=>!!qm(e,r,n)))&&(a[s]=!0,t.push({contexts:n.currentContext,node:e})):e.inputNames.every((e=>!!qm(e,r,n)))&&(a[s]=!0,t.push({contexts:n.currentContext,node:e})))}))}dispose(){Object.keys(this.weightMap).forEach((e=>this.weightMap[e].forEach((e=>e.dispose()))))}checkInputShapeAndType(e){Object.keys(e).forEach((t=>{const n=e[t],[r]=Ym(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){const e=a.attrParams.shape.value;X(e.length===n.shape.length&&n.shape.every(((t,n)=>-1===e[n]||e[n]===t)),(()=>`The shape of dict['${a.name}'] provided in model.execute(dict) must be [${e}], but was [${n.shape}]`))}a.attrParams.dtype&&a.attrParams.dtype.value&&X(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 ${n.dtype}`))}))}mapInputs(e){var t,n;const r={};for(const a in e){const o=null===(n=null===(t=this._signature)||void 0===t?void 0:t.inputs)||void 0===n?void 0:n[a];null!=o?r[o.name]=e[a]:r[a]=e[a]}return r}checkInputs(e){const t=Object.keys(e).filter((e=>{const[t]=Ym(e);return null==this.graph.nodes[t]}));if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map((e=>{var t,n;const r=null===(n=null===(t=this._signature)||void 0===t?void 0:t.outputs)||void 0===n?void 0:n[e];return null!=r?r.name:e}),{})}checkOutputs(e){e.forEach((e=>{const[t]=Ym(e);if(!this.graph.nodes[t])throw new Error(`The output '${e}' is not found in the graph`)}))}}class ny{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(const e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(const e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const ry="?tfjs-format=file",ay="model.json";class oy{get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}constructor(e,t={},n=s){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=n,null==t&&(this.loadOptions={}),this.resourceManager=new ny}findIOHandler(){const e=this.modelUrl;if(null!=e.load)this.handler=e;else if(null!=this.loadOptions.requestInit)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{const t=this.io.getLoadHandlers(e,this.loadOptions);if(0===t.length)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),null==this.handler.load)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");const e=this.handler.load();return Fe(e)?e.then((e=>this.loadSync(e))):this.loadSync(e)}loadSync(e){this.artifacts=e;const t=this.artifacts.modelTopology;let n=this.artifacts.signature;if(null!=this.artifacts.userDefinedMetadata){const e=this.artifacts.userDefinedMetadata;null!=e.signature&&(n=e.signature),null!=e.structuredOutputKeys&&(this.structuredOutputKeys=e.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;const r=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new ty(bg.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,null!=e.modelInitializer&&null!=e.modelInitializer.node){const t=bg.Instance.transformGraph(e.modelInitializer);this.initializer=new ty(t),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if("string"==typeof e){const t=this.io.getSaveHandlers(e);if(0===t.length)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(t.length>1)throw new Error(`Found more than one (${t.length}) save handlers for URL '${e}'`);e=t[0]}if(null==e.save)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}addStructuredOutputNames(e){if(this.structuredOutputKeys){const t={};return(e instanceof io?[e]:e).forEach(((e,n)=>t[this.structuredOutputKeys[n]]=e)),t}return e}predict(e,t){const n=this.execute(e,this.outputNodes);return this.addStructuredOutputNames(n)}async predictAsync(e,t){const n=await this.executeAsync(e,this.outputNodes);return this.addStructuredOutputNames(n)}normalizeInputs(e){var t;if(!(e instanceof io||Array.isArray(e))){const n=null===(t=this.signature)||void 0===t?void 0:t.inputs;if(null!=n)for(const t in n){const r=n[t];null!=r.resourceId&&(e[t]=this.resourceIdToCapturedInput[r.resourceId])}return e}e=Array.isArray(e)?e:[e];const n=Object.keys(this.resourceIdToCapturedInput).length;if(e.length+n!==this.inputNodes.length)throw new Error(`Input tensor count mismatch, the graph model has ${this.inputNodes.length-n} non-resource placeholders, while there are ${e.length} input tensors provided.`);let r=0;return this.inputNodes.reduce(((t,n)=>{var a,o,s;const i=null===(s=null===(o=null===(a=this.signature)||void 0===a?void 0:a.inputs)||void 0===o?void 0:o[n])||void 0===s?void 0:s.resourceId;return t[n]=null!=i?this.resourceIdToCapturedInput[i]:e[r++],t}),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}executeInitializerGraph(){return null==this.initializer?[]:null==this.initializerSignature?this.initializer.execute({},[]):this.initializer.execute({},Object.keys(this.initializerSignature.outputs))}async executeInitializerGraphAsync(){return null==this.initializer?[]:null==this.initializerSignature?this.initializer.executeAsync({},[]):this.initializer.executeAsync({},Object.keys(this.initializerSignature.outputs))}setResourceIdToCapturedInput(e){if(this.resourceIdToCapturedInput={},this.initializerSignature){const t=this.initializerSignature.outputs,n=Object.keys(t);for(let r=0;r<n.length;r++){const a=t[n[r]];this.resourceIdToCapturedInput[a.resourceId]=e[r]}}}execute(e,t){null==this.resourceIdToCapturedInput&&this.setResourceIdToCapturedInput(this.executeInitializerGraph()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);const n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){null==this.resourceIdToCapturedInput&&this.setResourceIdToCapturedInput(await this.executeInitializerGraphAsync()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);const n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce(((t,n)=>(t[n]=[e[n]],t)),{})}dispose(){this.executor.dispose(),this.initializer&&(this.initializer.dispose(),this.resourceIdToCapturedInput&&si(this.resourceIdToCapturedInput)),this.resourceManager.dispose()}}async function sy(e,t={},n=s){if(null==e)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");null==t&&(t={}),t.fromTFHub&&"string"==typeof e&&(e=function(e){e.endsWith("/")||(e+="/");return`${e}${ay}${ry}`}(e));const r=new oy(e,t,n);return await r.load(),r}
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
var iy=n(513),uy=function(e,t){return uy=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])},uy(e,t)};function ly(e,t){function n(){this.constructor=e}uy(e,t),e.prototype=null===t?Object.create(t):(n.prototype=t.prototype,new n)}var cy=function(){return cy=Object.assign||function(e){for(var t,n=1,r=arguments.length;n<r;n++)for(var a in t=arguments[n])Object.prototype.hasOwnProperty.call(t,a)&&(e[a]=t[a]);return e},cy.apply(this,arguments)};function py(e,t,n,r){return new(n||(n=Promise))((function(a,o){function s(e){try{u(r.next(e))}catch(e){o(e)}}function i(e){try{u(r.throw(e))}catch(e){o(e)}}function u(e){var t;e.done?a(e.value):(t=e.value,t instanceof n?t:new n((function(e){e(t)}))).then(s,i)}u((r=r.apply(e,t||[])).next())}))}function dy(e,t){var n,r,a,o,s={label:0,sent:function(){if(1&a[0])throw a[1];return a[1]},trys:[],ops:[]};return 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oi((function(){var n=t.preprocessInput(Ks(e,"float32")),r=op(n,0),a=t.model.predict(r).map((function(e){return qd(e,[0])})),o=t.nameOutputResults(a);return{heatmapScores:tc(o.heatmap),offsets:o.offsets,displacementFwd:o.displacementFwd,displacementBwd:o.displacementBwd,segmentation:o.segmentation,partHeatmaps:o.partHeatmaps,longOffsets:o.longOffsets,partOffsets:o.partOffsets}}))},e.prototype.dispose=function(){this.model.dispose()},e}(),ky=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return ly(t,e),t.prototype.preprocessInput=function(e){return oi((function(){return 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r=0,a=0,o=0;o<e.length;o++)t.keypoints[o].score>n&&(a+=1,r+=Math.pow(e[o].x-t.keypoints[o].position.x,2)+Math.pow(e[o].y-t.keypoints[o].position.y,2));return 0===a?r=1/0:r/=a,r}function Dy(e,t,n,r,a,o,s){for(var i=s[0],u=s[1],l=n(e),c=l.y*r+l.x,p=a[Ey*(2*c)+t],d=a[Ey*(2*c+1)+t],f=e.y+p,h=e.x+d,m=0;m<o;m++){f=Math.min(f,i-1);var g=n({x:h=Math.min(h,u-1),y:f}),y=g.y*r+g.x;f+=p=a[Ey*(2*y)+t],h+=d=a[Ey*(2*y+1)+t]}return{x:h,y:f}}function Cy(e,t,n,r,a,o,s,i,u,l){for(var c=a[0],p=a[1],d=o[0],f=o[1],h=i[0],m=i[1],g=[],y=function(e){return function(e,t,n,r){var a=t[0],o=t[1],s=n[0],i=n[1],u=Math.round(((a+e.y+1)*i-1)/r);return{x:Math.round(((o+e.x+1)*s-1)/r),y:u}}(e,[c,p],[d,f],u)},b=0;b<r;b++){var v=Dy(e,b,y,s,t,l,[h,m]);g.push(v)}for(var w=-1,x=1/0,k=0;k<n.length;k++){var S=Oy(g,n[k]);S<x&&(w=k,x=S)}return w}function $y(e,t){var n=e[0],r=e[1];return[Math.round((r-1)/t+1),Math.round((n-1)/t+1)]}function Ry(e,t,n,r,a,o,s,i,u,l,c){for(var p=s[0],d=s[1],f=e.shape,h=f[0],m=f[1],g=t.shape.slice(0,2),y=g[0],b=g[1],v=Xl(t,[y,b,2,Ey]),w=new Float32Array(c*Ey*3).fill(0),x=0;x<n.length;x++)for(var k=x*Ey*3,S=n[x],E=0;E<Ey;E++){var N=S.keypoints[E],T=k+3*E;w[T]=N.score,w[T+1]=N.position.y,w[T+2]=N.position.x}var _=Ty([r,a],[p,d],i),A=_[0],I=_[1],M=qo(w,[c,Ey,3]),O=i.top,D=i.left,C={variableNames:["segmentation","longOffsets","poses"],outputShape:[h,m],userCode:"\n int convertToPositionInOutput(int pos, int pad, float scale, int stride) {\n return round(((float(pos + pad) + 1.0) * scale - 1.0) / float(stride));\n }\n\n float convertToPositionInOutputFloat(\n int pos, int pad, float scale, int stride) {\n return ((float(pos + pad) + 1.0) * scale - 1.0) / float(stride);\n }\n\n float dist(float x1, float y1, float x2, float y2) {\n return pow(x1 - x2, 2.0) + pow(y1 - y2, 2.0);\n }\n\n float sampleLongOffsets(float h, float w, int d, int k) {\n float fh = fract(h);\n float fw = fract(w);\n int clH = int(ceil(h));\n int clW = int(ceil(w));\n int flH = int(floor(h));\n int flW = int(floor(w));\n float o11 = getLongOffsets(flH, flW, d, k);\n float o12 = getLongOffsets(flH, clW, d, k);\n float o21 = getLongOffsets(clH, flW, d, k);\n float o22 = getLongOffsets(clH, clW, d, k);\n float o1 = mix(o11, o12, fw);\n float o2 = mix(o21, o22, fw);\n return mix(o1, o2, fh);\n }\n\n int findNearestPose(int h, int w) {\n float prob = getSegmentation(h, w);\n if (prob < 1.0) {\n return -1;\n }\n\n // Done(Tyler): convert from output space h/w to strided space.\n float stridedH = convertToPositionInOutputFloat(\n h, "+O+", "+I+", "+o+");\n float stridedW = convertToPositionInOutputFloat(\n w, "+D+", "+A+", "+o+");\n\n float minDist = 1000000.0;\n int iMin = -1;\n for (int i = 0; i < "+c+"; i++) {\n float curDistSum = 0.0;\n int numKpt = 0;\n for (int k = 0; k < "+Ey+"; k++) {\n float dy = sampleLongOffsets(stridedH, stridedW, 0, k);\n float dx = sampleLongOffsets(stridedH, stridedW, 1, k);\n\n float y = float(h) + dy;\n float x = float(w) + dx;\n\n for (int s = 0; s < "+u+"; s++) {\n int yRounded = round(min(y, float("+(r-1)+")));\n int xRounded = round(min(x, float("+(a-1)+")));\n\n float yStrided = convertToPositionInOutputFloat(\n yRounded, "+O+", "+I+", "+o+");\n float xStrided = convertToPositionInOutputFloat(\n xRounded, "+D+", "+A+", "+o+");\n\n float dy = sampleLongOffsets(yStrided, xStrided, 0, k);\n float dx = sampleLongOffsets(yStrided, xStrided, 1, k);\n\n y = y + dy;\n x = x + dx;\n }\n\n float poseScore = getPoses(i, k, 0);\n float poseY = getPoses(i, k, 1);\n float poseX = getPoses(i, k, 2);\n if (poseScore > "+l+") {\n numKpt = numKpt + 1;\n curDistSum = curDistSum + dist(x, y, poseX, poseY);\n }\n }\n if (numKpt > 0 && curDistSum / float(numKpt) < minDist) {\n minDist = curDistSum / float(numKpt);\n iMin = i;\n }\n }\n return iMin;\n }\n\n void main() {\n ivec2 coords = getOutputCoords();\n int nearestPose = findNearestPose(coords[0], coords[1]);\n setOutput(float(nearestPose));\n }\n 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pb={architecture:"MobileNetV1",outputStride:16,quantBytes:4,multiplier:.75},db=["MobileNetV1","ResNet50"],fb={MobileNetV1:[8,16,32],ResNet50:[32,16]},hb={MobileNetV1:[.5,.75,1],ResNet50:[1]},mb=[1,2,4],gb={flipHorizontal:!1,internalResolution:"medium",segmentationThreshold:.7,maxDetections:10,scoreThreshold:.4,nmsRadius:20},yb={flipHorizontal:!1,internalResolution:"medium",segmentationThreshold:.7,maxDetections:10,scoreThreshold:.4,nmsRadius:20,minKeypointScore:.3,refineSteps:10};function bb(e){var t=e.segmentationThreshold,n=e.maxDetections,r=e.scoreThreshold,a=e.nmsRadius;if(t<0||t>1)throw new Error("segmentationThreshold "+t+". 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t=this.baseModel.predict(e);return{segmentLogits:t.segmentation,longOffsets:t.longOffsets,heatmapScores:t.heatmapScores,offsets:t.offsets,displacementFwd:t.displacementFwd,displacementBwd:t.displacementBwd,partHeatmaps:t.partHeatmaps}},e.prototype.segmentPersonActivation=function(e,t,n){var r=this;void 0===n&&(n=.5);var a=nb(e),o=a[0],s=a[1],i=sb(t,this.baseModel.outputStride,[o,s]),u=ub(e,i),l=u.resized,c=u.padding,p=oi((function(){var e=r.predictForPersonSegmentation(l),t=e.segmentLogits,a=e.heatmapScores,i=e.offsets,u=e.displacementFwd,p=e.displacementBwd,d=l.shape,f=d[0],h=d[1],m=ib(t,[o,s],[f,h],[[c.top,c.bottom],[c.left,c.right]],!0);return{segmentation:vy(qd(m),n),heatmapScores:a,offsets:i,displacementFwd:u,displacementBwd:p}})),d=p.segmentation,f=p.heatmapScores,h=p.offsets,m=p.displacementFwd,g=p.displacementBwd;return l.dispose(),{segmentation:d,heatmapScores:f,offsets:h,displacementFwd:m,displacementBwd:g,padding:c,internalResolutionHeightAndWidth:i}},e.prototype.segmentPerson=function(e,t){return void 0===t&&(t=gb),py(this,void 0,void 0,(function(){var n,r,a,o,s,i,u,l,c,p,d,f,h,m,g,y,b,v;return dy(this,(function(w){switch(w.label){case 0:return bb(t=cy(cy({},gb),t)),n=this.segmentPersonActivation(e,t.internalResolution,t.segmentationThreshold),r=n.segmentation,a=n.heatmapScores,o=n.offsets,s=n.displacementFwd,i=n.displacementBwd,u=n.padding,l=n.internalResolutionHeightAndWidth,c=r.shape,p=c[0],d=c[1],[4,r.data()];case 1:return f=w.sent(),r.dispose(),[4,lb([a,o,s,i])];case 2:return h=w.sent(),m=h[0],g=h[1],y=h[2],b=h[3],v=cb(v=Yy(m,g,y,b,this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[p,d],l,u,!1),a.dispose(),o.dispose(),s.dispose(),i.dispose(),[2,{height:p,width:d,data:f,allPoses:v}]}}))}))},e.prototype.segmentMultiPerson=function(e,t){return void 0===t&&(t=yb),py(this,void 0,void 0,(function(){var n,r,a,o,s,i,u,l,c,p,d,f,h,m,g,y,b,v,w,x,k,S=this;return dy(this,(function(E){switch(E.label){case 0:return vb(t=cy(cy({},yb),t)),n=nb(e),r=n[0],a=n[1],o=sb(t.internalResolution,this.baseModel.outputStride,[r,a]),s=ub(e,o),i=s.resized,u=s.padding,l=oi((function(){var e,n=S.predictForMultiPersonInstanceSegmentationAndPart(i),s=n.segmentLogits,l=n.longOffsets,c=n.heatmapScores,p=n.offsets,d=n.displacementFwd,f=n.displacementBwd,h=ib(s,[r,a],o,[[u.top,u.bottom],[u.left,u.right]],!0);return e=l,{segmentation:vy(qd(h),t.segmentationThreshold),longOffsets:e,heatmapScoresRaw:c,offsetsRaw:p,displacementFwdRaw:d,displacementBwdRaw:f}})),c=l.segmentation,p=l.longOffsets,d=l.heatmapScoresRaw,f=l.offsetsRaw,h=l.displacementFwdRaw,m=l.displacementBwdRaw,[4,lb([d,f,h,m])];case 1:return g=E.sent(),y=g[0],b=g[1],v=g[2],w=g[3],x=cb(x=Yy(y,b,v,w,this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[r,a],o,u,!1),[4,Py(c,p,x,r,a,this.baseModel.outputStride,o,u,t.scoreThreshold,t.refineSteps,t.minKeypointScore,t.maxDetections)];case 2:return k=E.sent(),i.dispose(),c.dispose(),p.dispose(),d.dispose(),f.dispose(),h.dispose(),m.dispose(),[2,k]}}))}))},e.prototype.segmentPersonPartsActivation=function(e,t,n){var r=this;void 0===n&&(n=.5);var a=nb(e),o=a[0],s=a[1],i=sb(t,this.baseModel.outputStride,[o,s]),u=ub(e,i),l=u.resized,c=u.padding,p=oi((function(){var e=r.predictForPersonSegmentationAndPart(l),t=e.segmentLogits,a=e.partHeatmapLogits,i=e.heatmapScores,u=e.offsets,p=e.displacementFwd,d=e.displacementBwd,f=l.shape,h=f[0],m=f[1],g=ib(t,[o,s],[h,m],[[c.top,c.bottom],[c.left,c.right]],!0),y=ib(a,[o,s],[h,m],[[c.top,c.bottom],[c.left,c.right]],!0);return{partSegmentation:wy(vy(qd(g),n),y),heatmapScores:i,offsets:u,displacementFwd:p,displacementBwd:d}})),d=p.partSegmentation,f=p.heatmapScores,h=p.offsets,m=p.displacementFwd,g=p.displacementBwd;return l.dispose(),{partSegmentation:d,heatmapScores:f,offsets:h,displacementFwd:m,displacementBwd:g,padding:c,internalResolutionHeightAndWidth:i}},e.prototype.segmentPersonParts=function(e,t){return void 0===t&&(t=gb),py(this,void 0,void 0,(function(){var n,r,a,o,s,i,u,l,c,p,d,f,h,m,g,y,b,v;return dy(this,(function(w){switch(w.label){case 0:return bb(t=cy(cy({},gb),t)),n=this.segmentPersonPartsActivation(e,t.internalResolution,t.segmentationThreshold),r=n.partSegmentation,a=n.heatmapScores,o=n.offsets,s=n.displacementFwd,i=n.displacementBwd,u=n.padding,l=n.internalResolutionHeightAndWidth,c=r.shape,p=c[0],d=c[1],[4,r.data()];case 1:return f=w.sent(),r.dispose(),[4,lb([a,o,s,i])];case 2:return h=w.sent(),m=h[0],g=h[1],y=h[2],b=h[3],v=cb(v=Yy(m,g,y,b,this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[p,d],l,u,!1),a.dispose(),o.dispose(),s.dispose(),i.dispose(),[2,{height:p,width:d,data:f,allPoses:v}]}}))}))},e.prototype.segmentMultiPersonParts=function(e,t){return void 0===t&&(t=yb),py(this,void 0,void 0,(function(){var n,r,a,o,s,i,u,l,c,p,d,f,h,m,g,y,b,v,w,x,k,S,E=this;return dy(this,(function(N){switch(N.label){case 0:return vb(t=cy(cy({},yb),t)),n=nb(e),r=n[0],a=n[1],o=sb(t.internalResolution,this.baseModel.outputStride,[r,a]),s=ub(e,o),i=s.resized,u=s.padding,l=oi((function(){var e=E.predictForMultiPersonInstanceSegmentationAndPart(i),n=e.segmentLogits,s=e.longOffsets,l=e.heatmapScores,c=e.offsets,p=e.displacementFwd,d=e.displacementBwd,f=e.partHeatmaps,h=ib(n,[r,a],o,[[u.top,u.bottom],[u.left,u.right]],!0),m=ib(f,[r,a],o,[[u.top,u.bottom],[u.left,u.right]],!0),g=s,y=vy(qd(h),t.segmentationThreshold),b=function(e){var t=e.shape,n=t[0],r=t[1],a=t[2];return oi((function(){var t=by(e),o=op(bd(0,a,1,"int32"),1),s=Ks(ku(t,o),"int32");return Xl(s,[n,r])}))}(m);return{segmentation:y,longOffsets:g,heatmapScoresRaw:l,offsetsRaw:c,displacementFwdRaw:p,displacementBwdRaw:d,partSegmentation:b}})),c=l.segmentation,p=l.longOffsets,d=l.heatmapScoresRaw,f=l.offsetsRaw,h=l.displacementFwdRaw,m=l.displacementBwdRaw,g=l.partSegmentation,[4,lb([d,f,h,m])];case 1:return y=N.sent(),b=y[0],v=y[1],w=y[2],x=y[3],k=cb(k=Yy(b,v,w,x,this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[r,a],o,u,!1),[4,Ly(c,p,g,k,r,a,this.baseModel.outputStride,o,u,t.scoreThreshold,t.refineSteps,t.minKeypointScore,t.maxDetections)];case 2:return S=N.sent(),i.dispose(),c.dispose(),p.dispose(),d.dispose(),f.dispose(),h.dispose(),m.dispose(),g.dispose(),[2,S]}}))}))},e.prototype.dispose=function(){this.baseModel.dispose()},e}();function xb(e){return py(this,void 0,void 0,(function(){var t,n,r,a,o,s;return dy(this,(function(i){switch(i.label){case 0:if(t=e.outputStride,n=e.quantBytes,r=e.multiplier,null==y)throw new Error("Cannot find TensorFlow.js. If you are using a <script> tag, please also include @tensorflow/tfjs on the page before using this\n model.");return a=function(e,t,n){var r={1:"100",.75:"075",.5:"050"},a="model-stride"+e+".json";return 4===n?tb+"float/"+r[t]+"/"+a:tb+"quant"+n+"/"+r[t]+"/"+a}(t,r,n),[4,sy(e.modelUrl||a)];case 1:return o=i.sent(),s=new ky(o,t),[2,new wb(s)]}}))}))}function kb(e){return py(this,void 0,void 0,(function(){var t,n,r,a,o;return dy(this,(function(s){switch(s.label){case 0:if(t=e.outputStride,n=e.quantBytes,null==y)throw new Error("Cannot find TensorFlow.js. If you are using a <script> tag, please also include @tensorflow/tfjs on the page before using this\n model.");return r=function(e,t){var n="model-stride"+e+".json";return 4===t?eb+"float/"+n:eb+"quant"+t+"/"+n}(t,n),[4,sy(e.modelUrl||r)];case 1:return a=s.sent(),o=new Jy(a,t),[2,new wb(o)]}}))}))}function Sb(e){return void 0===e&&(e=pb),py(this,void 0,void 0,(function(){return dy(this,(function(t){return"ResNet50"===(e=function(e){if(null==(e=e||pb).architecture&&(e.architecture="MobileNetV1"),db.indexOf(e.architecture)<0)throw new Error("Invalid architecture "+e.architecture+". Should be one of "+db);if(null==e.outputStride&&(e.outputStride=16),fb[e.architecture].indexOf(e.outputStride)<0)throw new Error("Invalid outputStride "+e.outputStride+". Should be one of "+fb[e.architecture]+" for architecture "+e.architecture+".");if(null==e.multiplier&&(e.multiplier=1),hb[e.architecture].indexOf(e.multiplier)<0)throw new Error("Invalid multiplier "+e.multiplier+". Should be one of "+hb[e.architecture]+" for architecture "+e.architecture+".");if(null==e.quantBytes&&(e.quantBytes=4),mb.indexOf(e.quantBytes)<0)throw new Error("Invalid quantBytes "+e.quantBytes+". Should be one of "+mb+" for architecture "+e.architecture+".");return e}(e)).architecture?[2,kb(e)]:"MobileNetV1"===e.architecture?[2,xb(e)]:[2,null]}))}))}var Eb=["left_face","right_face","left_upper_arm_front","left_upper_arm_back","right_upper_arm_front","right_upper_arm_back","left_lower_arm_front","left_lower_arm_back","right_lower_arm_front","right_lower_arm_back","left_hand","right_hand","torso_front","torso_back","left_upper_leg_front","left_upper_leg_back","right_upper_leg_front","right_upper_leg_back","left_lower_leg_front","left_lower_leg_back","right_lower_leg_front","right_lower_leg_back","left_feet","right_feet"],Nb=function(){function e(e){this.mask=e}return e.prototype.toCanvasImageSource=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,hy(this.mask)]}))}))},e.prototype.toImageData=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,this.mask]}))}))},e.prototype.toTensor=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,gy(this.mask)]}))}))},e.prototype.getUnderlyingType=function(){return"imagedata"},e}();function Tb(e){if(yy(e),255!==e)throw new Error("Foreground id must be 255 but got "+e);return"person"}function _b(e){if(yy(e),e>=Eb.length)throw new Error("Invalid body part value "+e);return Eb[e]}var Ab=function(){function e(e){this.bodyPixModel=e}return e.prototype.segmentPeople=function(e,t){return py(this,void 0,void 0,(function(){var n,r,a,o;return dy(this,(function(s){switch(s.label){case 0:return e instanceof ImageBitmap&&((n=document.createElement("canvas")).getContext("2d").drawImage(e,0,0),e=n),t.segmentBodyParts?t.multiSegmentation?[4,this.bodyPixModel.segmentMultiPersonParts(e,t)]:[3,2]:[3,5];case 1:return a=s.sent(),[3,4];case 2:return[4,this.bodyPixModel.segmentPersonParts(e,t)];case 3:a=[s.sent()],s.label=4;case 4:return r=a.map((function(e){var t=e.data,n=e.width,r=e.height,a=new Uint8ClampedArray(n*r*4).fill(0);return t.forEach((function(e,t){-1===e?(a[4*t]=Eb.length,a[4*t+3]=0):(a[4*t]=e,a[4*t+3]=255)})),{maskValueToLabel:_b,mask:new Nb(new ImageData(a,n,r))}})),[3,10];case 5:return t.multiSegmentation?[4,this.bodyPixModel.segmentMultiPerson(e,t)]:[3,7];case 6:return o=s.sent(),[3,9];case 7:return[4,this.bodyPixModel.segmentPerson(e,t)];case 8:o=[s.sent()],s.label=9;case 9:r=o.map((function(e){var t=e.data,n=e.width,r=e.height,a=new Uint8ClampedArray(n*r*4).fill(0);return t.forEach((function(e,t){0===e?(a[4*t]=0,a[4*t+3]=0):(a[4*t]=255,a[4*t+3]=255)})),{maskValueToLabel:Tb,mask:new Nb(new ImageData(a,n,r))}})),s.label=10;case 10:return[2,r]}}))}))},e.prototype.dispose=function(){this.bodyPixModel.dispose()},e.prototype.reset=function(){},e}();function Ib(e){return py(this,void 0,void 0,(function(){return dy(this,(function(t){return[2,Sb(e).then((function(e){return new Ab(e)}))]}))}))}var Mb={runtime:"mediapipe",modelType:"general"},Ob=function(){function e(e){this.mask=e}return e.prototype.toCanvasImageSource=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,this.mask]}))}))},e.prototype.toImageData=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,my(this.mask)]}))}))},e.prototype.toTensor=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,gy(this.mask)]}))}))},e.prototype.getUnderlyingType=function(){return"canvasimagesource"},e}();function Db(e){return yy(e),"person"}var Cb=function(){function e(e){var t,n,r=this;this.selfieMode=!1,this.selfieSegmentationSolution=new iy.SelfieSegmentation({locateFile:null!==(t=e.locateFile)&&void 0!==t?t:function(t,n){return e.solutionPath?e.solutionPath.replace(/\/+$/,"")+"/"+t:n+"/"+t}}),n="landscape"===e.modelType?1:0,this.selfieSegmentationSolution.setOptions({modelSelection:n,selfieMode:this.selfieMode}),this.selfieSegmentationSolution.onResults((function(e){r.segmentation=[{maskValueToLabel:Db,mask:new Ob(e.segmentationMask)}]}))}return e.prototype.segmentPeople=function(e,t){return py(this,void 0,void 0,(function(){var n,r;return dy(this,(function(a){switch(a.label){case 0:return t&&t.flipHorizontal&&t.flipHorizontal!==this.selfieMode&&(this.selfieMode=t.flipHorizontal,this.selfieSegmentationSolution.setOptions({selfieMode:this.selfieMode})),e instanceof io?(r=ImageData.bind,[4,Fu(e)]):[3,2];case 1:return n=new(r.apply(ImageData,[void 0,a.sent(),e.shape[1],e.shape[0]])),[3,3];case 2:n=e,a.label=3;case 3:return e=n,[4,this.selfieSegmentationSolution.send({image:e})];case 4:return a.sent(),[2,this.segmentation]}}))}))},e.prototype.dispose=function(){this.selfieSegmentationSolution.close()},e.prototype.reset=function(){this.selfieSegmentationSolution.reset(),this.segmentation=null,this.selfieMode=!1},e.prototype.initialize=function(){return this.selfieSegmentationSolution.initialize()},e}();function $b(e){return py(this,void 0,void 0,(function(){var t,n;return dy(this,(function(r){switch(r.label){case 0:return t=function(e){if(null==e)return cy({},Mb);var t=cy({},e);return t.runtime="mediapipe",null==t.modelType&&(t.modelType=Mb.modelType),t}(e),[4,(n=new Cb(t)).initialize()];case 1:return r.sent(),[2,n]}}))}))}function Rb(e){return e instanceof io?{height:e.shape[0],width:e.shape[1]}:{height:e.height,width:e.width}}function Fb(e,t){X(0!==e.width,(function(){return t+" width cannot be 0."})),X(0!==e.height,(function(){return t+" height cannot be 0."}))}function Pb(e,t,n){var r=t.outputTensorSize,a=t.keepAspectRatio,o=t.borderMode,s=t.outputTensorFloatRange,i=Rb(e),u=function(e,t){return t?{xCenter:t.xCenter*e.width,yCenter:t.yCenter*e.height,width:t.width*e.width,height:t.height*e.height,rotation:t.rotation}:{xCenter:.5*e.width,yCenter:.5*e.height,width:e.width,height:e.height,rotation:0}}(i,n),l=function(e,t,n){if(void 0===n&&(n=!1),!n)return{top:0,left:0,right:0,bottom:0};var r=t.height,a=t.width;Fb(t,"targetSize"),Fb(e,"roi");var o,s,i=r/a,u=e.height/e.width,l=0,c=0;return i>u?(o=e.width,s=e.width*i,c=(1-u/i)/2):(o=e.height/i,s=e.height,l=(1-i/u)/2),e.width=o,e.height=s,{top:c,left:l,right:l,bottom:c}}(u,r,a),c=function(e,t,n,r){var a=e.width,o=e.height,s=r?-1:1,i=Math.cos(e.rotation),u=Math.sin(e.rotation),l=e.xCenter,c=e.yCenter,p=1/t,d=1/n,f=new Array(16);return f[0]=a*i*s*p,f[1]=-o*u*p,f[2]=0,f[3]=(-.5*a*i*s+.5*o*u+l)*p,f[4]=a*u*s*d,f[5]=o*i*d,f[6]=0,f[7]=(-.5*o*i-.5*a*u*s+c)*d,f[8]=0,f[9]=0,f[10]=a*p,f[11]=0,f[12]=0,f[13]=0,f[14]=0,f[15]=1,function(e){if(16!==e.length)throw new Error("Array length must be 16 but got "+e.length);return[[e[0],e[1],e[2],e[3]],[e[4],e[5],e[6],e[7]],[e[8],e[9],e[10],e[11]],[e[12],e[13],e[14],e[15]]]}(f)}(u,i.width,i.height,!1),p=oi((function(){var t,n=(t=e)instanceof io?t:Lu(t),a=Zd(function(e,t,n){return Fb(n,"inputResolution"),[1/n.width*e[0][0]*t.width,1/n.height*e[0][1]*t.width,e[0][3]*t.width,1/n.width*e[1][0]*t.height,1/n.height*e[1][1]*t.height,e[1][3]*t.height,0,0]}(c,i,r),[1,8]),u="zero"===o?"constant":"nearest",l=Ah.transform(op(Ks(n,"float32")),a,"bilinear",u,0,[r.height,r.width]);return null!=s?function(e,t){var n=function(e,t,n,r){var a=(r-n)/255;return{scale:a,offset:n-0*a}}(0,0,t[0],t[1]);return oi((function(){return bi(xi(e,n.scale),n.offset)}))}(l,s):l}));return{imageTensor:p,padding:l,transformationMatrix:c}}var Lb={runtime:"tfjs",modelType:"general",modelUrl:"https://tfhub.dev/mediapipe/tfjs-model/selfie_segmentation/general/1"},zb={flipHorizontal:!1},Bb={outputTensorSize:{width:256,height:256},keepAspectRatio:!1,borderMode:"zero",outputTensorFloatRange:[0,1]},Vb={outputTensorSize:{width:256,height:144},keepAspectRatio:!1,borderMode:"zero",outputTensorFloatRange:[0,1]},Ub={activation:"none"},jb=function(){function e(e){this.mask=e}return e.prototype.toCanvasImageSource=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,hy(this.mask)]}))}))},e.prototype.toImageData=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,my(this.mask)]}))}))},e.prototype.toTensor=function(){return py(this,void 0,void 0,(function(){return dy(this,(function(e){return[2,this.mask]}))}))},e.prototype.getUnderlyingType=function(){return"tensor"},e}();function Wb(e){return yy(e),"person"}var Hb,qb,Gb=function(){function e(e,t){this.modelType=e,this.model=t}return e.prototype.segmentPeople=function(e,t){return py(this,void 0,void 0,(function(){var n,r=this;return dy(this,(function(a){return t=function(e){if(null==e)return cy({},zb);var t=cy({},e);return null==t.flipHorizontal&&(t.flipHorizontal=zb.flipHorizontal),t}(t),null==e?(this.reset(),[2,[]]):(n=oi((function(){var t=Pb(e,"general"===r.modelType?Bb:Vb).imageTensor,n=nc(r.model.predict(t),[0,0,0,1],-1),a=Rb(e),o=function(e,t,n){return oi((function(){var r=qd(e,[0]),a=r.shape[2];if(1===a){var o=r;switch(t.activation){case"none":break;case"sigmoid":o=tc(o);break;case"softmax":throw new Error("Softmax activation requires two channels.");default:throw new Error("Activation not supported ("+t.activation+")")}var s=n?Ah.resizeBilinear(o,[n.height,n.width]):o;return qd(s,[2])}throw new Error("Unsupported number of tensor channels "+a)}))}(n,Ub,a),s=op(o,2),i=Yp(s,[[0,0],[0,0],[0,1]]);return Up(i,[[0,0],[0,0],[0,2]],"symmetric")})),[2,[{maskValueToLabel:Wb,mask:new jb(n)}]])}))}))},e.prototype.dispose=function(){this.model.dispose()},e.prototype.reset=function(){},e}();function Kb(e){return py(this,void 0,void 0,(function(){var t,n,r;return dy(this,(function(a){switch(a.label){case 0:return t=function(e){if(null==e)return cy({},Lb);var t=cy({},e);if(t.runtime="tfjs",null==t.modelType&&(t.modelType=Lb.modelType),"general"!==t.modelType&&"landscape"!==t.modelType)throw new Error("Model type must be one of general or landscape, but got "+t.modelType);return null==t.modelUrl&&("general"===t.modelType?t.modelUrl="https://tfhub.dev/mediapipe/tfjs-model/selfie_segmentation/general/1":t.modelUrl="https://tfhub.dev/mediapipe/tfjs-model/selfie_segmentation/landscape/1"),t}(e),n="string"==typeof t.modelUrl&&t.modelUrl.indexOf("https://tfhub.dev")>-1,[4,sy(t.modelUrl,{fromTFHub:n})];case 1:return r=a.sent(),[2,new Gb(t.modelType,r)]}}))}))}function Qb(e,t){return py(this,void 0,void 0,(function(){var n,r;return dy(this,(function(a){switch(e){case Hb.MediaPipeSelfieSegmentation:if(n=void 0,null!=(r=t)){if("tfjs"===r.runtime)return[2,Kb(r)];if("mediapipe"===r.runtime)return[2,$b(r)];n=r.runtime}throw new Error("Expect modelConfig.runtime to be either 'tfjs' or 'mediapipe', but got "+n);case Hb.BodyPix:return[2,Ib(r=t)];default:throw new Error(e+" is not a supported model name.")}}))}))}(qb=Hb||(Hb={})).BodyPix="BodyPix",qb.MediaPipeSelfieSegmentation="MediaPipeSelfieSegmentation";var Yb="blurred",Xb="blurred-mask",Zb="mask",Jb="draw-image",ev={};function tv(e,t,n,r){var a=e.width,o=e.height,s=t.width,i=t.height;if(a!==s||o!==i)throw new Error("error: dimensions must match. 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