✨ Rounded corners with intense neon glow effect on hover. Modern and eye-catching.
+
+
+
+
Option 2: Hexagon Futuristic
+
+
+
+
+
+
🔷 Hexagonal shape with rotation effect. Very sci-fi and distinctive.
+
+
+
+
Option 3: Glass Morphism
+
+
+
+
+
+
🔮 Frosted glass effect with soft glow. Clean and premium feel.
+
+
+
+
Option 4: Cyberpunk Slant
+
+
+
+
+
+
âš¡ Skewed design with layered borders. Very cyberpunk aesthetic.
+
+
+
+
Option 5: Minimalist Border Animation
+
+
+
+
+
+
💫 Clean borders with shimmer effect on hover. Subtle and elegant.
+
+
+
+
+
+
diff --git a/src/lib/webgazer.js b/src/lib/webgazer.js
new file mode 100644
index 0000000..5f533b3
--- /dev/null
+++ b/src/lib/webgazer.js
@@ -0,0 +1,14041 @@
+/*!
+ *
+ * WebGazer.js: Democratizing Webcam Eye Tracking on the Browser
+ * Copyright (c) 2016, Brown WebGazer Team
+ * Licensed under GPLv3. Companies with a valuation of less than $1M can use WebGazer.js under LGPLv3.
+ *
+ */
+var webgazer;(()=>{var e={790:(e,t,n)=>{
+/*!
+ localForage -- Offline Storage, Improved
+ Version 1.7.3
+ https://localforage.github.io/localForage
+ (c) 2013-2017 Mozilla, Apache License 2.0
+*/
+e.exports=function e(t,n,s){function r(i,o){if(!n[i]){if(!t[i]){if(a)return a(i,!0);var l=new Error("Cannot find module '"+i+"'");throw l.code="MODULE_NOT_FOUND",l}var u=n[i]={exports:{}};t[i][0].call(u.exports,(function(e){var n=t[i][1][e];return r(n||e)}),u,u.exports,e,t,n,s)}return n[i].exports}for(var a=void 0,i=0;i=43)}})).catch((function(){return!1}))}function k(e){return"boolean"==typeof m?u.resolve(m):v(e).then((function(e){return m=e}))}function I(e){var t=g[e.name],n={};n.promise=new u((function(e,t){n.resolve=e,n.reject=t})),t.deferredOperations.push(n),t.dbReady?t.dbReady=t.dbReady.then((function(){return n.promise})):t.dbReady=n.promise}function N(e){var t=g[e.name].deferredOperations.pop();if(t)return t.resolve(),t.promise}function S(e,t){var n=g[e.name].deferredOperations.pop();if(n)return n.reject(t),n.promise}function T(e,t){return new u((function(n,s){if(g[e.name]=g[e.name]||M(),e.db){if(!t)return n(e.db);I(e),e.db.close()}var r=[e.name];t&&r.push(e.version);var a=i.open.apply(i,r);t&&(a.onupgradeneeded=function(t){var n=a.result;try{n.createObjectStore(e.storeName),t.oldVersion<=1&&n.createObjectStore(f)}catch(n){if("ConstraintError"!==n.name)throw n;console.warn('The database "'+e.name+'" has been upgraded from version '+t.oldVersion+" to version "+t.newVersion+', but the storage "'+e.storeName+'" already exists.')}}),a.onerror=function(e){e.preventDefault(),s(a.error)},a.onsuccess=function(){n(a.result),N(e)}}))}function C(e){return T(e,!1)}function $(e){return T(e,!0)}function E(e,t){if(!e.db)return!0;var n=!e.db.objectStoreNames.contains(e.storeName),s=e.versione.db.version;if(s&&(e.version!==t&&console.warn('The database "'+e.name+"\" can't be downgraded from version "+e.db.version+" to version "+e.version+"."),e.version=e.db.version),r||n){if(n){var a=e.db.version+1;a>e.version&&(e.version=a)}return!0}return!1}function R(e){return new u((function(t,n){var s=new FileReader;s.onerror=n,s.onloadend=function(n){var s=btoa(n.target.result||"");t({__local_forage_encoded_blob:!0,data:s,type:e.type})},s.readAsBinaryString(e)}))}function A(e){return l([w(atob(e.data))],{type:e.type})}function F(e){return e&&e.__local_forage_encoded_blob}function _(e){var t=this,n=t._initReady().then((function(){var e=g[t._dbInfo.name];if(e&&e.dbReady)return e.dbReady}));return h(n,e,e),n}function D(e){I(e);for(var t=g[e.name],n=t.forages,s=0;s0&&(!e.db||"InvalidStateError"===r.name||"NotFoundError"===r.name))return u.resolve().then((function(){if(!e.db||"NotFoundError"===r.name&&!e.db.objectStoreNames.contains(e.storeName)&&e.version<=e.db.version)return e.db&&(e.version=e.db.version+1),$(e)})).then((function(){return D(e).then((function(){O(e,t,n,s-1)}))})).catch(n);n(r)}}function M(){return{forages:[],db:null,dbReady:null,deferredOperations:[]}}function L(e){var t=this,n={db:null};if(e)for(var s in e)n[s]=e[s];var r=g[n.name];r||(r=M(),g[n.name]=r),r.forages.push(t),t._initReady||(t._initReady=t.ready,t.ready=_);var a=[];function i(){return u.resolve()}for(var o=0;o>4,c[l++]=(15&s)<<4|r>>2,c[l++]=(3&r)<<6|63&a;return u}function fe(e){var t,n=new Uint8Array(e),s="";for(t=0;t>2],s+=X[(3&n[t])<<4|n[t+1]>>4],s+=X[(15&n[t+1])<<2|n[t+2]>>6],s+=X[63&n[t+2]];return n.length%3==2?s=s.substring(0,s.length-1)+"=":n.length%3==1&&(s=s.substring(0,s.length-2)+"=="),s}function me(e,t){var n="";if(e&&(n=pe.call(e)),e&&("[object ArrayBuffer]"===n||e.buffer&&"[object ArrayBuffer]"===pe.call(e.buffer))){var s,r=J;e instanceof ArrayBuffer?(s=e,r+=ee):(s=e.buffer,"[object Int8Array]"===n?r+=ne:"[object Uint8Array]"===n?r+=se:"[object Uint8ClampedArray]"===n?r+=re:"[object Int16Array]"===n?r+=ae:"[object Uint16Array]"===n?r+=oe:"[object Int32Array]"===n?r+=ie:"[object Uint32Array]"===n?r+=le:"[object Float32Array]"===n?r+=ue:"[object Float64Array]"===n?r+=ce:t(new Error("Failed to get type for BinaryArray"))),t(r+fe(s))}else if("[object Blob]"===n){var a=new FileReader;a.onload=function(){var n=Y+e.type+"~"+fe(this.result);t(J+te+n)},a.readAsArrayBuffer(e)}else try{t(JSON.stringify(e))}catch(n){console.error("Couldn't convert value into a JSON string: ",e),t(null,n)}}function ge(e){if(e.substring(0,Q)!==J)return JSON.parse(e);var t,n=e.substring(he),s=e.substring(Q,he);if(s===te&&Z.test(n)){var r=n.match(Z);t=r[1],n=n.substring(r[0].length)}var a=de(n);switch(s){case ee:return a;case te:return l([a],{type:t});case ne:return new Int8Array(a);case se:return new Uint8Array(a);case re:return new Uint8ClampedArray(a);case ae:return new Int16Array(a);case oe:return new Uint16Array(a);case ie:return new Int32Array(a);case le:return new Uint32Array(a);case ue:return new Float32Array(a);case ce:return new Float64Array(a);default:throw new Error("Unkown type: "+s)}}var ye={serialize:me,deserialize:ge,stringToBuffer:de,bufferToString:fe};function be(e,t,n,s){e.executeSql("CREATE TABLE IF NOT EXISTS "+t.storeName+" (id INTEGER PRIMARY KEY, key unique, value)",[],n,s)}function xe(e){var t=this,n={db:null};if(e)for(var s in e)n[s]="string"!=typeof e[s]?e[s].toString():e[s];var r=new u((function(e,s){try{n.db=openDatabase(n.name,String(n.version),n.description,n.size)}catch(e){return s(e)}n.db.transaction((function(r){be(r,n,(function(){t._dbInfo=n,e()}),(function(e,t){s(t)}))}),s)}));return n.serializer=ye,r}function we(e,t,n,s,r,a){e.executeSql(n,s,r,(function(e,i){i.code===i.SYNTAX_ERR?e.executeSql("SELECT name FROM sqlite_master WHERE type='table' AND name = ?",[t.storeName],(function(e,o){o.rows.length?a(e,i):be(e,t,(function(){e.executeSql(n,s,r,a)}),a)}),a):a(e,i)}),a)}function ve(e,t){var n=this;e=p(e);var s=new u((function(t,s){n.ready().then((function(){var r=n._dbInfo;r.db.transaction((function(n){we(n,r,"SELECT * FROM "+r.storeName+" WHERE key = ? LIMIT 1",[e],(function(e,n){var s=n.rows.length?n.rows.item(0).value:null;s&&(s=r.serializer.deserialize(s)),t(s)}),(function(e,t){s(t)}))}))})).catch(s)}));return c(s,t),s}function ke(e,t){var n=this,s=new u((function(t,s){n.ready().then((function(){var r=n._dbInfo;r.db.transaction((function(n){we(n,r,"SELECT * FROM "+r.storeName,[],(function(n,s){for(var a=s.rows,i=a.length,o=0;o0)return void a(Ie.apply(r,[e,o,n,s-1]));i(t)}}))}))})).catch(i)}));return c(a,n),a}function Ne(e,t,n){return Ie.apply(this,[e,t,n,1])}function Se(e,t){var n=this;e=p(e);var s=new u((function(t,s){n.ready().then((function(){var r=n._dbInfo;r.db.transaction((function(n){we(n,r,"DELETE FROM "+r.storeName+" WHERE key = ?",[e],(function(){t()}),(function(e,t){s(t)}))}))})).catch(s)}));return c(s,t),s}function Te(e){var t=this,n=new u((function(e,n){t.ready().then((function(){var s=t._dbInfo;s.db.transaction((function(t){we(t,s,"DELETE FROM "+s.storeName,[],(function(){e()}),(function(e,t){n(t)}))}))})).catch(n)}));return c(n,e),n}function Ce(e){var t=this,n=new u((function(e,n){t.ready().then((function(){var s=t._dbInfo;s.db.transaction((function(t){we(t,s,"SELECT COUNT(key) as c FROM "+s.storeName,[],(function(t,n){var s=n.rows.item(0).c;e(s)}),(function(e,t){n(t)}))}))})).catch(n)}));return c(n,e),n}function $e(e,t){var n=this,s=new u((function(t,s){n.ready().then((function(){var r=n._dbInfo;r.db.transaction((function(n){we(n,r,"SELECT key FROM "+r.storeName+" WHERE id = ? LIMIT 1",[e+1],(function(e,n){var s=n.rows.length?n.rows.item(0).key:null;t(s)}),(function(e,t){s(t)}))}))})).catch(s)}));return c(s,t),s}function Ee(e){var t=this,n=new u((function(e,n){t.ready().then((function(){var s=t._dbInfo;s.db.transaction((function(t){we(t,s,"SELECT key FROM "+s.storeName,[],(function(t,n){for(var s=[],r=0;r '__WebKitDatabaseInfoTable__'",[],(function(n,s){for(var r=[],a=0;a0}function Le(e){var t=this,n={};if(e)for(var s in e)n[s]=e[s];return n.keyPrefix=De(e,t._defaultConfig),Me()?(t._dbInfo=n,n.serializer=ye,u.resolve()):u.reject()}function ze(e){var t=this,n=t.ready().then((function(){for(var e=t._dbInfo.keyPrefix,n=localStorage.length-1;n>=0;n--){var s=localStorage.key(n);0===s.indexOf(e)&&localStorage.removeItem(s)}}));return c(n,e),n}function Pe(e,t){var n=this;e=p(e);var s=n.ready().then((function(){var t=n._dbInfo,s=localStorage.getItem(t.keyPrefix+e);return s&&(s=t.serializer.deserialize(s)),s}));return c(s,t),s}function Be(e,t){var n=this,s=n.ready().then((function(){for(var t=n._dbInfo,s=t.keyPrefix,r=s.length,a=localStorage.length,i=1,o=0;o=0;t--){var n=localStorage.key(t);0===n.indexOf(e)&&localStorage.removeItem(n)}})):u.reject("Invalid arguments"),c(s,t),s}var qe={_driver:"localStorageWrapper",_initStorage:Le,_support:_e(),iterate:Be,getItem:Pe,setItem:He,removeItem:Ge,clear:ze,length:Ue,key:We,keys:Ve,dropInstance:je},Ke=function(e,t){return e===t||"number"==typeof e&&"number"==typeof t&&isNaN(e)&&isNaN(t)},Xe=function(e,t){for(var n=e.length,s=0;s{e.exports=n;var t=null;try{t=new WebAssembly.Instance(new WebAssembly.Module(new Uint8Array([0,97,115,109,1,0,0,0,1,13,2,96,0,1,127,96,4,127,127,127,127,1,127,3,7,6,0,1,1,1,1,1,6,6,1,127,1,65,0,11,7,50,6,3,109,117,108,0,1,5,100,105,118,95,115,0,2,5,100,105,118,95,117,0,3,5,114,101,109,95,115,0,4,5,114,101,109,95,117,0,5,8,103,101,116,95,104,105,103,104,0,0,10,191,1,6,4,0,35,0,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,126,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,127,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,128,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,129,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,130,34,4,66,32,135,167,36,0,32,4,167,11])),{}).exports}catch(e){}function n(e,t,n){this.low=0|e,this.high=0|t,this.unsigned=!!n}function s(e){return!0===(e&&e.__isLong__)}n.prototype.__isLong__,Object.defineProperty(n.prototype,"__isLong__",{value:!0}),n.isLong=s;var r={},a={};function i(e,t){var n,s,i;return t?(i=0<=(e>>>=0)&&e<256)&&(s=a[e])?s:(n=l(e,(0|e)<0?-1:0,!0),i&&(a[e]=n),n):(i=-128<=(e|=0)&&e<128)&&(s=r[e])?s:(n=l(e,e<0?-1:0,!1),i&&(r[e]=n),n)}function o(e,t){if(isNaN(e))return t?y:g;if(t){if(e<0)return y;if(e>=d)return k}else{if(e<=-f)return I;if(e+1>=f)return v}return e<0?o(-e,t).neg():l(e%p|0,e/p|0,t)}function l(e,t,s){return new n(e,t,s)}n.fromInt=i,n.fromNumber=o,n.fromBits=l;var u=Math.pow;function c(e,t,n){if(0===e.length)throw Error("empty string");if("NaN"===e||"Infinity"===e||"+Infinity"===e||"-Infinity"===e)return g;if("number"==typeof t?(n=t,t=!1):t=!!t,(n=n||10)<2||360)throw Error("interior hyphen");if(0===s)return c(e.substring(1),t,n).neg();for(var r=o(u(n,8)),a=g,i=0;i>>0:this.low},N.toNumber=function(){return this.unsigned?(this.high>>>0)*p+(this.low>>>0):this.high*p+(this.low>>>0)},N.toString=function(e){if((e=e||10)<2||36>>0).toString(e);if((a=l).isZero())return c+i;for(;c.length<6;)c="0"+c;i=""+c+i}},N.getHighBits=function(){return this.high},N.getHighBitsUnsigned=function(){return this.high>>>0},N.getLowBits=function(){return this.low},N.getLowBitsUnsigned=function(){return this.low>>>0},N.getNumBitsAbs=function(){if(this.isNegative())return this.eq(I)?64:this.neg().getNumBitsAbs();for(var e=0!=this.high?this.high:this.low,t=31;t>0&&!(e&1<=0},N.isOdd=function(){return!(1&~this.low)},N.isEven=function(){return!(1&this.low)},N.equals=function(e){return s(e)||(e=h(e)),(this.unsigned===e.unsigned||this.high>>>31!=1||e.high>>>31!=1)&&(this.high===e.high&&this.low===e.low)},N.eq=N.equals,N.notEquals=function(e){return!this.eq(e)},N.neq=N.notEquals,N.ne=N.notEquals,N.lessThan=function(e){return this.comp(e)<0},N.lt=N.lessThan,N.lessThanOrEqual=function(e){return this.comp(e)<=0},N.lte=N.lessThanOrEqual,N.le=N.lessThanOrEqual,N.greaterThan=function(e){return this.comp(e)>0},N.gt=N.greaterThan,N.greaterThanOrEqual=function(e){return this.comp(e)>=0},N.gte=N.greaterThanOrEqual,N.ge=N.greaterThanOrEqual,N.compare=function(e){if(s(e)||(e=h(e)),this.eq(e))return 0;var t=this.isNegative(),n=e.isNegative();return t&&!n?-1:!t&&n?1:this.unsigned?e.high>>>0>this.high>>>0||e.high===this.high&&e.low>>>0>this.low>>>0?-1:1:this.sub(e).isNegative()?-1:1},N.comp=N.compare,N.negate=function(){return!this.unsigned&&this.eq(I)?I:this.not().add(b)},N.neg=N.negate,N.add=function(e){s(e)||(e=h(e));var t=this.high>>>16,n=65535&this.high,r=this.low>>>16,a=65535&this.low,i=e.high>>>16,o=65535&e.high,u=e.low>>>16,c=0,p=0,d=0,f=0;return d+=(f+=a+(65535&e.low))>>>16,p+=(d+=r+u)>>>16,c+=(p+=n+o)>>>16,c+=t+i,l((d&=65535)<<16|(f&=65535),(c&=65535)<<16|(p&=65535),this.unsigned)},N.subtract=function(e){return s(e)||(e=h(e)),this.add(e.neg())},N.sub=N.subtract,N.multiply=function(e){if(this.isZero())return g;if(s(e)||(e=h(e)),t)return l(t.mul(this.low,this.high,e.low,e.high),t.get_high(),this.unsigned);if(e.isZero())return g;if(this.eq(I))return e.isOdd()?I:g;if(e.eq(I))return this.isOdd()?I:g;if(this.isNegative())return e.isNegative()?this.neg().mul(e.neg()):this.neg().mul(e).neg();if(e.isNegative())return this.mul(e.neg()).neg();if(this.lt(m)&&e.lt(m))return o(this.toNumber()*e.toNumber(),this.unsigned);var n=this.high>>>16,r=65535&this.high,a=this.low>>>16,i=65535&this.low,u=e.high>>>16,c=65535&e.high,p=e.low>>>16,d=65535&e.low,f=0,y=0,b=0,x=0;return b+=(x+=i*d)>>>16,y+=(b+=a*d)>>>16,b&=65535,y+=(b+=i*p)>>>16,f+=(y+=r*d)>>>16,y&=65535,f+=(y+=a*p)>>>16,y&=65535,f+=(y+=i*c)>>>16,f+=n*d+r*p+a*c+i*u,l((b&=65535)<<16|(x&=65535),(f&=65535)<<16|(y&=65535),this.unsigned)},N.mul=N.multiply,N.divide=function(e){if(s(e)||(e=h(e)),e.isZero())throw Error("division by zero");var n,r,a;if(t)return this.unsigned||-2147483648!==this.high||-1!==e.low||-1!==e.high?l((this.unsigned?t.div_u:t.div_s)(this.low,this.high,e.low,e.high),t.get_high(),this.unsigned):this;if(this.isZero())return this.unsigned?y:g;if(this.unsigned){if(e.unsigned||(e=e.toUnsigned()),e.gt(this))return y;if(e.gt(this.shru(1)))return x;a=y}else{if(this.eq(I))return e.eq(b)||e.eq(w)?I:e.eq(I)?b:(n=this.shr(1).div(e).shl(1)).eq(g)?e.isNegative()?b:w:(r=this.sub(e.mul(n)),a=n.add(r.div(e)));if(e.eq(I))return this.unsigned?y:g;if(this.isNegative())return e.isNegative()?this.neg().div(e.neg()):this.neg().div(e).neg();if(e.isNegative())return this.div(e.neg()).neg();a=g}for(r=this;r.gte(e);){n=Math.max(1,Math.floor(r.toNumber()/e.toNumber()));for(var i=Math.ceil(Math.log(n)/Math.LN2),c=i<=48?1:u(2,i-48),p=o(n),d=p.mul(e);d.isNegative()||d.gt(r);)d=(p=o(n-=c,this.unsigned)).mul(e);p.isZero()&&(p=b),a=a.add(p),r=r.sub(d)}return a},N.div=N.divide,N.modulo=function(e){return s(e)||(e=h(e)),t?l((this.unsigned?t.rem_u:t.rem_s)(this.low,this.high,e.low,e.high),t.get_high(),this.unsigned):this.sub(this.div(e).mul(e))},N.mod=N.modulo,N.rem=N.modulo,N.not=function(){return l(~this.low,~this.high,this.unsigned)},N.and=function(e){return s(e)||(e=h(e)),l(this.low&e.low,this.high&e.high,this.unsigned)},N.or=function(e){return s(e)||(e=h(e)),l(this.low|e.low,this.high|e.high,this.unsigned)},N.xor=function(e){return s(e)||(e=h(e)),l(this.low^e.low,this.high^e.high,this.unsigned)},N.shiftLeft=function(e){return s(e)&&(e=e.toInt()),0==(e&=63)?this:e<32?l(this.low<>>32-e,this.unsigned):l(0,this.low<>>e|this.high<<32-e,this.high>>e,this.unsigned):l(this.high>>e-32,this.high>=0?0:-1,this.unsigned)},N.shr=N.shiftRight,N.shiftRightUnsigned=function(e){if(s(e)&&(e=e.toInt()),0===(e&=63))return this;var t=this.high;return e<32?l(this.low>>>e|t<<32-e,t>>>e,this.unsigned):l(32===e?t:t>>>e-32,0,this.unsigned)},N.shru=N.shiftRightUnsigned,N.shr_u=N.shiftRightUnsigned,N.toSigned=function(){return this.unsigned?l(this.low,this.high,!1):this},N.toUnsigned=function(){return this.unsigned?this:l(this.low,this.high,!0)},N.toBytes=function(e){return e?this.toBytesLE():this.toBytesBE()},N.toBytesLE=function(){var e=this.high,t=this.low;return[255&t,t>>>8&255,t>>>16&255,t>>>24,255&e,e>>>8&255,e>>>16&255,e>>>24]},N.toBytesBE=function(){var e=this.high,t=this.low;return[e>>>24,e>>>16&255,e>>>8&255,255&e,t>>>24,t>>>16&255,t>>>8&255,255&t]},n.fromBytes=function(e,t,s){return s?n.fromBytesLE(e,t):n.fromBytesBE(e,t)},n.fromBytesLE=function(e,t){return new n(e[0]|e[1]<<8|e[2]<<16|e[3]<<24,e[4]|e[5]<<8|e[6]<<16|e[7]<<24,t)},n.fromBytesBE=function(e,t){return new n(e[4]<<24|e[5]<<16|e[6]<<8|e[7],e[0]<<24|e[1]<<16|e[2]<<8|e[3],t)}},312:function(e,t){var n,s,r;s=[e],n=function(e){"use strict";function t(e,t,n){return t in e?Object.defineProperty(e,t,{value:n,enumerable:!0,configurable:!0,writable:!0}):e[t]=n,e}var n=Object.assign||function(e){for(var t=1;tMath.abs(n[a][i])&&(i=o);for(var l=a;l=a;h--)n[h][c]-=n[h][a]*n[a][c]/n[a][a]}for(var p=s-1;p>=0;p--){for(var d=0,f=p+1;f=0;v--)w+=v>1?y[v]+"x^"+v+" + ":1===v?y[v]+"x + ":y[v];return{string:w,points:x,predict:b,equation:[].concat(s(y)).reverse(),r2:o(a(e,x),t.precision)}}};function u(){var e=function(e,s){return n({_round:o},e,t({},s,(function(e,t){return l[s](e,n({},r,t))})))};return Object.keys(l).reduce(e,{})}e.exports=u()},void 0===(r="function"==typeof n?n.apply(t,s):n)||(e.exports=r)},391:(e,t,n)=>{var s=n(180),r=n(181),a=n(31),i=n(67),o=n(833),l=n(717),u=n(801);u.alea=s,u.xor128=r,u.xorwow=a,u.xorshift7=i,u.xor4096=o,u.tychei=l,e.exports=u},180:function(e,t,n){var s;!function(e,r){function a(e){var t=this,n=function(){var e=4022871197,t=function(t){t=String(t);for(var n=0;n>>0,e=(s*=e)>>>0,e+=4294967296*(s-=e)}return 2.3283064365386963e-10*(e>>>0)};return t}();t.next=function(){var e=2091639*t.s0+2.3283064365386963e-10*t.c;return t.s0=t.s1,t.s1=t.s2,t.s2=e-(t.c=0|e)},t.c=1,t.s0=n(" "),t.s1=n(" "),t.s2=n(" "),t.s0-=n(e),t.s0<0&&(t.s0+=1),t.s1-=n(e),t.s1<0&&(t.s1+=1),t.s2-=n(e),t.s2<0&&(t.s2+=1),n=null}function i(e,t){return t.c=e.c,t.s0=e.s0,t.s1=e.s1,t.s2=e.s2,t}function o(e,t){var n=new a(e),s=t&&t.state,r=n.next;return r.int32=function(){return 4294967296*n.next()|0},r.double=function(){return r()+11102230246251565e-32*(2097152*r()|0)},r.quick=r,s&&("object"==typeof s&&i(s,n),r.state=function(){return i(n,{})}),r}r&&r.exports?r.exports=o:n.amdD&&n.amdO?void 0===(s=function(){return o}.call(t,n,t,r))||(r.exports=s):this.alea=o}(0,e=n.nmd(e),n.amdD)},717:function(e,t,n){var s;!function(e,r){function a(e){var t=this,n="";t.next=function(){var e=t.b,n=t.c,s=t.d,r=t.a;return e=e<<25^e>>>7^n,n=n-s|0,s=s<<24^s>>>8^r,r=r-e|0,t.b=e=e<<20^e>>>12^n,t.c=n=n-s|0,t.d=s<<16^n>>>16^r,t.a=r-e|0},t.a=0,t.b=0,t.c=-1640531527,t.d=1367130551,e===Math.floor(e)?(t.a=e/4294967296|0,t.b=0|e):n+=e;for(var s=0;s>>0)/4294967296};return r.double=function(){do{var e=((n.next()>>>11)+(n.next()>>>0)/4294967296)/(1<<21)}while(0===e);return e},r.int32=n.next,r.quick=r,s&&("object"==typeof s&&i(s,n),r.state=function(){return i(n,{})}),r}r&&r.exports?r.exports=o:n.amdD&&n.amdO?void 0===(s=function(){return o}.call(t,n,t,r))||(r.exports=s):this.tychei=o}(0,e=n.nmd(e),n.amdD)},181:function(e,t,n){var s;!function(e,r){function a(e){var t=this,n="";t.x=0,t.y=0,t.z=0,t.w=0,t.next=function(){var e=t.x^t.x<<11;return t.x=t.y,t.y=t.z,t.z=t.w,t.w^=t.w>>>19^e^e>>>8},e===(0|e)?t.x=e:n+=e;for(var s=0;s>>0)/4294967296};return r.double=function(){do{var e=((n.next()>>>11)+(n.next()>>>0)/4294967296)/(1<<21)}while(0===e);return e},r.int32=n.next,r.quick=r,s&&("object"==typeof s&&i(s,n),r.state=function(){return i(n,{})}),r}r&&r.exports?r.exports=o:n.amdD&&n.amdO?void 0===(s=function(){return o}.call(t,n,t,r))||(r.exports=s):this.xor128=o}(0,e=n.nmd(e),n.amdD)},833:function(e,t,n){var s;!function(e,r){function a(e){var t=this;t.next=function(){var e,n,s=t.w,r=t.X,a=t.i;return t.w=s=s+1640531527|0,n=r[a+34&127],e=r[a=a+1&127],n^=n<<13,e^=e<<17,n^=n>>>15,e^=e>>>12,n=r[a]=n^e,t.i=a,n+(s^s>>>16)|0},function(e,t){var n,s,r,a,i,o=[],l=128;for(t===(0|t)?(s=t,t=null):(t+="\0",s=0,l=Math.max(l,t.length)),r=0,a=-32;a>>15,s^=s<<4,s^=s>>>13,a>=0&&(i=i+1640531527|0,r=0==(n=o[127&a]^=s+i)?r+1:0);for(r>=128&&(o[127&(t&&t.length||0)]=-1),r=127,a=512;a>0;--a)s=o[r+34&127],n=o[r=r+1&127],s^=s<<13,n^=n<<17,s^=s>>>15,n^=n>>>12,o[r]=s^n;e.w=i,e.X=o,e.i=r}(t,e)}function i(e,t){return t.i=e.i,t.w=e.w,t.X=e.X.slice(),t}function o(e,t){null==e&&(e=+new Date);var n=new a(e),s=t&&t.state,r=function(){return(n.next()>>>0)/4294967296};return r.double=function(){do{var e=((n.next()>>>11)+(n.next()>>>0)/4294967296)/(1<<21)}while(0===e);return e},r.int32=n.next,r.quick=r,s&&(s.X&&i(s,n),r.state=function(){return i(n,{})}),r}r&&r.exports?r.exports=o:n.amdD&&n.amdO?void 0===(s=function(){return o}.call(t,n,t,r))||(r.exports=s):this.xor4096=o}(0,e=n.nmd(e),n.amdD)},67:function(e,t,n){var s;!function(e,r){function a(e){var t=this;t.next=function(){var e,n,s=t.x,r=t.i;return e=s[r],n=(e^=e>>>7)^e<<24,n^=(e=s[r+1&7])^e>>>10,n^=(e=s[r+3&7])^e>>>3,n^=(e=s[r+4&7])^e<<7,e=s[r+7&7],n^=(e^=e<<13)^e<<9,s[r]=n,t.i=r+1&7,n},function(e,t){var n,s=[];if(t===(0|t))s[0]=t;else for(t=""+t,n=0;n0;--n)e.next()}(t,e)}function i(e,t){return t.x=e.x.slice(),t.i=e.i,t}function o(e,t){null==e&&(e=+new Date);var n=new a(e),s=t&&t.state,r=function(){return(n.next()>>>0)/4294967296};return r.double=function(){do{var e=((n.next()>>>11)+(n.next()>>>0)/4294967296)/(1<<21)}while(0===e);return e},r.int32=n.next,r.quick=r,s&&(s.x&&i(s,n),r.state=function(){return i(n,{})}),r}r&&r.exports?r.exports=o:n.amdD&&n.amdO?void 0===(s=function(){return o}.call(t,n,t,r))||(r.exports=s):this.xorshift7=o}(0,e=n.nmd(e),n.amdD)},31:function(e,t,n){var s;!function(e,r){function a(e){var t=this,n="";t.next=function(){var e=t.x^t.x>>>2;return t.x=t.y,t.y=t.z,t.z=t.w,t.w=t.v,(t.d=t.d+362437|0)+(t.v=t.v^t.v<<4^e^e<<1)|0},t.x=0,t.y=0,t.z=0,t.w=0,t.v=0,e===(0|e)?t.x=e:n+=e;for(var s=0;s>>4),t.next()}function i(e,t){return t.x=e.x,t.y=e.y,t.z=e.z,t.w=e.w,t.v=e.v,t.d=e.d,t}function o(e,t){var n=new a(e),s=t&&t.state,r=function(){return(n.next()>>>0)/4294967296};return r.double=function(){do{var e=((n.next()>>>11)+(n.next()>>>0)/4294967296)/(1<<21)}while(0===e);return e},r.int32=n.next,r.quick=r,s&&("object"==typeof s&&i(s,n),r.state=function(){return i(n,{})}),r}r&&r.exports?r.exports=o:n.amdD&&n.amdO?void 0===(s=function(){return o}.call(t,n,t,r))||(r.exports=s):this.xorwow=o}(0,e=n.nmd(e),n.amdD)},801:function(e,t,n){var s;!function(r,a,i){var o,l=256,u=i.pow(l,6),c=i.pow(2,52),h=2*c,p=255;function d(e,t,n){var s=[],p=y(g((t=1==t?{entropy:!0}:t||{}).entropy?[e,b(a)]:null==e?function(){try{var e;return o&&(e=o.randomBytes)?e=e(l):(e=new Uint8Array(l),(r.crypto||r.msCrypto).getRandomValues(e)),b(e)}catch(e){var t=r.navigator,n=t&&t.plugins;return[+new Date,r,n,r.screen,b(a)]}}():e,3),s),d=new f(s),x=function(){for(var e=d.g(6),t=u,n=0;e=h;)e/=2,t/=2,n>>>=1;return(e+n)/t};return x.int32=function(){return 0|d.g(4)},x.quick=function(){return d.g(4)/4294967296},x.double=x,y(b(d.S),a),(t.pass||n||function(e,t,n,s){return s&&(s.S&&m(s,d),e.state=function(){return m(d,{})}),n?(i.random=e,t):e})(x,p,"global"in t?t.global:this==i,t.state)}function f(e){var t,n=e.length,s=this,r=0,a=s.i=s.j=0,i=s.S=[];for(n||(e=[n++]);r{window.requestAnimFrame=window.requestAnimationFrame||window.webkitRequestAnimationFrame||window.mozRequestAnimationFrame||window.oRequestAnimationFrame||window.msRequestAnimationFrame||function(e,t){return window.setTimeout(e,1e3/60)},window.cancelRequestAnimFrame=window.cancelCancelRequestAnimationFrame||window.webkitCancelRequestAnimationFrame||window.mozCancelRequestAnimationFrame||window.oCancelRequestAnimationFrame||window.msCancelRequestAnimationFrame||window.clearTimeout},817:()=>{},590:()=>{},530:()=>{},108:()=>{},551:()=>{},234:()=>{}},t={};function n(s){var r=t[s];if(void 0!==r)return r.exports;var a=t[s]={id:s,loaded:!1,exports:{}};return e[s].call(a.exports,a,a.exports,n),a.loaded=!0,a.exports}n.amdD=function(){throw new Error("define cannot be used indirect")},n.amdO={},n.n=e=>{var t=e&&e.__esModule?()=>e.default:()=>e;return n.d(t,{a:t}),t},n.d=(e,t)=>{for(var s in t)n.o(t,s)&&!n.o(e,s)&&Object.defineProperty(e,s,{enumerable:!0,get:t[s]})},n.g=function(){if("object"==typeof globalThis)return globalThis;try{return this||new Function("return this")()}catch(e){if("object"==typeof window)return window}}(),n.o=(e,t)=>Object.prototype.hasOwnProperty.call(e,t),n.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},n.nmd=e=>(e.paths=[],e.children||(e.children=[]),e);var s={};(()=>{"use strict";n.d(s,{default:()=>zB});var e={};n.r(e),n.d(e,{browserFiles:()=>si,browserHTTPRequest:()=>pi,concatenateArrayBuffers:()=>ra,copyModel:()=>Ga,decodeWeights:()=>ea,encodeWeights:()=>Qr,fromMemory:()=>gi,fromMemorySync:()=>yi,getLoadHandlers:()=>ga,getModelArtifactsForJSON:()=>la,getModelArtifactsForJSONSync:()=>oa,getModelArtifactsInfoForJSON:()=>ua,getSaveHandlers:()=>ma,getWeightSpecs:()=>ca,http:()=>hi,isHTTPScheme:()=>ui,listModels:()=>Va,loadWeights:()=>ii,moveModel:()=>Ha,registerLoadRouter:()=>fa,registerSaveRouter:()=>da,removeModel:()=>Ua,weightsLoaderFactory:()=>oi,withSaveHandler:()=>bi,withSaveHandlerSync:()=>xi});var t={};n.r(t),n.d(t,{assertParamsValid:()=>Ei,computeFlatOffset:()=>Vi,computeOutShape:()=>Ai,getNormalizedAxes:()=>Oi,isSliceContinous:()=>Wi,maskToAxes:()=>Ri,parseSliceParams:()=>Ui,sliceInfo:()=>Gi,startForAxis:()=>Pi,startIndicesWithElidedDims:()=>Mi,stopForAxis:()=>Bi,stopIndicesWithElidedDims:()=>Li,stridesForAxis:()=>zi,stridesWithElidedDims:()=>Fi});var r={};n.r(r),n.d(r,{conv2d:()=>kh,depthwiseConv2d:()=>Sh,matMul:()=>Th});var a={};n.r(a),n.d(a,{collectGatherOpShapeInfo:()=>Ud,computeOutShape:()=>Vd,segOpComputeOptimalWindowSize:()=>Wd});var i={};n.r(i),n.d(i,{ERF_A1:()=>ad,ERF_A2:()=>id,ERF_A3:()=>od,ERF_A4:()=>ld,ERF_A5:()=>ud,ERF_P:()=>rd,PARALLELIZE_THRESHOLD:()=>qp,RowPartitionType:()=>Vp,SELU_SCALE:()=>sd,SELU_SCALEALPHA:()=>nd,applyActivation:()=>wh,assertAndGetBroadcastShape:()=>ki,assertAxesAreInnerMostDims:()=>Dl,assertParamsConsistent:()=>Bp,assignToTypedArray:()=>md,axesAreInnerMostDims:()=>Rl,calculateShapes:()=>uh,checkEinsumDimSizes:()=>Nd,checkPadOnDimRoundingMode:()=>Fo,combineLocations:()=>Al,combineRaggedTensorToTensorShapes:()=>Up,complexWithEvenIndex:()=>pd,complexWithOddIndex:()=>dd,computeConv2DInfo:()=>ko,computeConv3DInfo:()=>Io,computeDefaultPad:()=>No,computeDilation2DInfo:()=>xo,computeOptimalWindowSize:()=>Kp,computeOutAndReduceShapes:()=>Fl,computeOutShape:()=>Wp,computePool2DInfo:()=>wo,computePool3DInfo:()=>vo,convertConv2DDataFormat:()=>Ao,decodeEinsumEquation:()=>kd,eitherStridesOrDilationsAreOne:()=>Ro,expandShapeToKeepDim:()=>_l,exponent:()=>yd,exponents:()=>gd,fromStringArrayToUint8:()=>Hd,fromUint8ToStringArray:()=>Gd,getAxesPermutation:()=>Ol,getBroadcastDims:()=>wi,getComplexWithIndex:()=>fd,getEinsumComputePath:()=>Sd,getEinsumPermutation:()=>Id,getFusedBiasGradient:()=>xh,getFusedDyActivation:()=>bh,getImageCenter:()=>Xp,getInnerMostAxes:()=>Ll,getPermuted:()=>Zp,getRaggedRank:()=>Hp,getReductionAxes:()=>vi,getReshaped:()=>Yp,getReshapedPermuted:()=>Jp,getRowPartitionTypesHelper:()=>Gp,getSliceBeginCoords:()=>Qp,getSliceSize:()=>ed,getSparseFillEmptyRowsIndicesDenseShapeMismatch:()=>Ed,getSparseFillEmptyRowsNegativeIndexErrorMessage:()=>Rd,getSparseFillEmptyRowsOutOfRangeIndexErrorMessage:()=>Ad,getSparseReshapeEmptyTensorZeroOutputDimErrorMessage:()=>Dd,getSparseReshapeInputOutputMismatchErrorMessage:()=>Md,getSparseReshapeInputOutputMultipleErrorMessage:()=>Od,getSparseReshapeMultipleNegativeOneOutputDimErrorMessage:()=>Fd,getSparseReshapeNegativeOutputDimErrorMessage:()=>_d,getSparseSegmentReductionIndicesOutOfRangeErrorMessage:()=>Bd,getSparseSegmentReductionNegativeSegmentIdsErrorMessage:()=>Ld,getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage:()=>zd,getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage:()=>Pd,getUndoAxesPermutation:()=>Ml,isIdentityPermutation:()=>Td,log:()=>Rs,mergeRealAndImagArrays:()=>cd,prepareAndValidate:()=>td,prepareSplitSize:()=>$d,segment_util:()=>a,shouldFuse:()=>vh,slice_util:()=>t,splitRealAndImagArrays:()=>hd,tupleValuesAreOne:()=>Eo,upcastType:()=>Sr,validateDefaultValueShape:()=>jp,validateInput:()=>lh,validateUpdateShape:()=>oh,warn:()=>Es});var o={};n.r(o),n.d(o,{json:()=>kv});var l={};n.r(l),n.d(l,{json:()=>Iv});var u={};n.r(u),n.d(u,{json:()=>Nv});var c={};n.r(c),n.d(c,{json:()=>Sv});var h={};n.r(h),n.d(h,{json:()=>Tv});var p={};n.r(p),n.d(p,{json:()=>Cv});var d={};n.r(d),n.d(d,{json:()=>$v});var f={};n.r(f),n.d(f,{json:()=>Ev});var m={};n.r(m),n.d(m,{json:()=>Rv});var g={};n.r(g),n.d(g,{json:()=>Av});var y={};n.r(y),n.d(y,{json:()=>Fv});var b={};n.r(b),n.d(b,{json:()=>_v});var x={};n.r(x),n.d(x,{json:()=>Dv});var w={};n.r(w),n.d(w,{json:()=>Ov});var v={};n.r(v),n.d(v,{json:()=>Mv});var k={};n.r(k),n.d(k,{json:()=>Lv});var I={};n.r(I),n.d(I,{json:()=>zv});var N={};n.r(N),n.d(N,{json:()=>Pv});var S={};n.r(S),n.d(S,{json:()=>Bv});var T={};n.r(T),n.d(T,{OP_SCOPE_SUFFIX:()=>jr,abs:()=>ro,acos:()=>ao,acosh:()=>io,add:()=>oo,addN:()=>lo,all:()=>uo,any:()=>co,argMax:()=>ho,argMin:()=>po,asin:()=>fo,asinh:()=>mo,atan:()=>go,atan2:()=>yo,atanh:()=>bo,avgPool:()=>Do,avgPool3d:()=>Oo,basicLSTMCell:()=>Vo,batchNorm:()=>Go,batchNorm2d:()=>Ho,batchNorm3d:()=>jo,batchNorm4d:()=>qo,batchToSpaceND:()=>Uo,bincount:()=>Ko,booleanMaskAsync:()=>rh,broadcastArgs:()=>Xo,broadcastTo:()=>Yo,buffer:()=>Ya,cast:()=>Za,ceil:()=>Zo,clipByValue:()=>Qo,clone:()=>Ja,complex:()=>Kr,concat:()=>Mo,concat1d:()=>el,concat2d:()=>tl,concat3d:()=>nl,concat4d:()=>sl,conv1d:()=>al,conv2d:()=>rl,conv2dTranspose:()=>ol,conv3d:()=>ll,conv3dTranspose:()=>cl,cos:()=>hl,cosh:()=>pl,cosineWindow:()=>mh,cumprod:()=>dl,cumsum:()=>fl,denseBincount:()=>ml,depthToSpace:()=>gl,depthwiseConv2d:()=>yl,diag:()=>bl,dilation2d:()=>xl,div:()=>vl,divNoNan:()=>Sl,dot:()=>Tl,dropout:()=>dh,einsum:()=>Cl,elu:()=>$l,enclosingPowerOfTwo:()=>fh,equal:()=>kl,erf:()=>El,euclideanNorm:()=>jl,exp:()=>ql,expandDims:()=>Kl,expm1:()=>Xl,eye:()=>Zl,fft:()=>_c,fill:()=>Jo,floor:()=>Jl,floorDiv:()=>wl,fused:()=>r,gather:()=>Ql,gatherND:()=>ph,greater:()=>eu,greaterEqual:()=>tu,ifft:()=>Dc,imag:()=>nu,image:()=>Np,inTopKAsync:()=>gh,irfft:()=>Oc,isFinite:()=>su,isInf:()=>ru,isNaN:()=>au,leakyRelu:()=>iu,less:()=>ou,lessEqual:()=>lu,linalg:()=>Sp,linspace:()=>uu,localResponseNormalization:()=>cu,log:()=>hu,log1p:()=>pu,logSigmoid:()=>mu,logSoftmax:()=>yu,logSumExp:()=>bu,logicalAnd:()=>xu,logicalNot:()=>wu,logicalOr:()=>vu,logicalXor:()=>ku,losses:()=>Tp,lowerBound:()=>Su,matMul:()=>Lo,max:()=>zl,maxPool:()=>Tu,maxPool3d:()=>Cu,maxPoolWithArgmax:()=>$u,maximum:()=>Eu,mean:()=>Ru,meshgrid:()=>_u,min:()=>Pl,minimum:()=>Du,mirrorPad:()=>Ou,mod:()=>Mu,moments:()=>Lu,movingAverage:()=>ih,mul:()=>zo,multiRNNCell:()=>zu,multinomial:()=>Pu,neg:()=>du,norm:()=>Hl,notEqual:()=>Bu,oneHot:()=>Wu,ones:()=>Fu,onesLike:()=>Vu,op:()=>qr,outerProduct:()=>Uu,pad:()=>Gu,pad1d:()=>Hu,pad2d:()=>ju,pad3d:()=>qu,pad4d:()=>Ku,pool:()=>Yu,pow:()=>Bl,prelu:()=>Zu,print:()=>Qa,prod:()=>Ju,raggedGather:()=>Qu,raggedTensorToTensor:()=>ec,rand:()=>tc,randomGamma:()=>ic,randomNormal:()=>oc,randomStandardNormal:()=>lc,randomUniform:()=>uc,range:()=>cc,real:()=>hc,reciprocal:()=>pc,relu:()=>dc,relu6:()=>fc,reshape:()=>_o,reverse:()=>mc,reverse1d:()=>gc,reverse2d:()=>yc,reverse3d:()=>bc,reverse4d:()=>xc,rfft:()=>Lc,round:()=>wc,rsqrt:()=>vc,scalar:()=>no,scatterND:()=>ch,searchSorted:()=>Nu,selu:()=>kc,separableConv2d:()=>Ic,setdiff1dAsync:()=>Nc,sigmoid:()=>Po,sign:()=>Sc,signal:()=>Ip,sin:()=>Tc,sinh:()=>Cc,slice:()=>Bo,slice1d:()=>$c,slice2d:()=>Ec,slice3d:()=>Rc,slice4d:()=>Ac,softmax:()=>Fc,softplus:()=>fu,spaceToBatchND:()=>Xu,sparse:()=>Cp,sparseToDense:()=>hh,spectral:()=>kp,split:()=>Mc,sqrt:()=>Wl,square:()=>Vl,squaredDifference:()=>zc,squeeze:()=>Pc,stack:()=>Bc,step:()=>Wc,stridedSlice:()=>Vc,string:()=>$p,sub:()=>gu,sum:()=>Ul,tan:()=>Uc,tanh:()=>Wo,tensor:()=>Yr,tensor1d:()=>Gc,tensor2d:()=>Hc,tensor3d:()=>Ii,tensor4d:()=>jc,tensor5d:()=>qc,tensor6d:()=>Kc,tile:()=>Yl,topk:()=>Xc,transpose:()=>ah,truncatedNormal:()=>Yc,unique:()=>Zc,unsortedSegmentSum:()=>Jc,unstack:()=>Qc,upperBound:()=>eh,variable:()=>th,where:()=>Il,whereAsync:()=>sh,zeros:()=>Au,zerosLike:()=>Nl});var C={};n.r(C),n.d(C,{mx:()=>PI,XI:()=>AN,Nk:()=>FN,ct:()=>DI,YG:()=>ON,hH:()=>WN,z3:()=>NS,sG:()=>OS,uM:()=>BS,vS:()=>sT,qB:()=>hT,GG:()=>dT,lg:()=>bT,rq:()=>mT,cu:()=>AT,WR:()=>$T,GE:()=>DT,px:()=>MT,jC:()=>ZT,He:()=>eC,hE:()=>cC,BF:()=>gS,Dk:()=>wC,cl:()=>$C,_B:()=>WC,ub:()=>jC,Ku:()=>JC,qy:()=>e$,Zy:()=>p$,bu:()=>m$,zv:()=>SI,dH:()=>KI,HS:()=>CN,yH:()=>O$,l3:()=>L$,z9:()=>P$,x6:()=>G$,eW:()=>Q$,GK:()=>nE,SP:()=>aE,f6:()=>oE,dl:()=>jS,Dw:()=>pE,xT:()=>gE,_X:()=>tN,wz:()=>IE});class ${constructor(e,t){this.backend=e,this.dataMover=t,this.data=new WeakMap,this.dataIdsCount=0}get(e){return this.data.has(e)||this.dataMover.moveData(this.backend,e),this.data.get(e)}set(e,t){this.dataIdsCount++,this.data.set(e,t)}has(e){return this.data.has(e)}delete(e){return this.dataIdsCount--,this.data.delete(e)}numDataIds(){return this.dataIdsCount}}class E{refCount(e){return R("refCount")}incRef(e){return R("incRef")}timerAvailable(){return!0}time(e){return R("time")}read(e){return R("read")}readSync(e){return R("readSync")}readToGPU(e,t){return R("readToGPU")}numDataIds(){return R("numDataIds")}disposeData(e,t){return R("disposeData")}write(e,t,n){return R("write")}move(e,t,n,s,r){return R("move")}memory(){return R("memory")}floatPrecision(){return R("floatPrecision")}epsilon(){return 32===this.floatPrecision()?1e-7:1e-4}dispose(){return R("dispose")}}function R(e){throw new Error(`'${e}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`)}
+/**
+ * @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 A(e){let t=e.length,n=0;for(;t>0;)n=Math.random()*t|0,t--,D(e,t,n)}function F(e,t,n){return Math.max(e,Math.min(t,n))}function _(e){return e%2==0?e:e+1}function D(e,t,n){const s=e[t];e[t]=e[n],e[n]=s}function O(e,t){if(!e)throw new Error("string"==typeof t?t:t())}function M(e,t,n=""){O(B(e,t),(()=>n+` Shapes ${e} and ${t} must match`))}function L(e){O(null!=e,(()=>"The input to the tensor constructor must be a non-null value."))}function z(e,t=[],n=!1){if(null==t&&(t=[]),Array.isArray(e)||Z(e)&&!n)for(let s=0;s0,n,s=setTimeout){return new Promise(((r,a)=>{let i=0;const o=()=>{if(e())return void r();i++;const l=t(i);null!=n&&i>=n?a():s(o,l)};o()}))}function H(e,t){let n=1,s=-1;for(let t=0;t=0)n*=e[t];else if(-1===e[t]){if(-1!==s)throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${s} and dim ${t}`);s=t}else if(e[t]<0)throw Error(`Shapes can not be < 0. Found ${e[t]} at dim ${t}`);if(-1===s){if(t>0&&t!==n)throw Error(`Size(${t}) must match the product of shape ${e}`);return e}if(0===n)throw Error(`Cannot infer the missing size in [${e}] when there are 0 elements`);if(t%n!=0)throw Error(`The implicit shape can't be a fractional number. Got ${t} / ${n}`);const r=e.slice();return r[s]=t/n,r}function j(e,t){const n=t.length;return O((e=null==e?t.map(((e,t)=>t)):[].concat(e)).every((e=>e>=-n&&e`All values in axis param must be in range [-${n}, ${n}) but got axis ${e}`)),O(e.every((e=>W(e))),(()=>`All values in axis param must be integers but got axis ${e}`)),e.map((e=>e<0?n+e:e))}function q(e,t){const n=[],s=[],r=null!=t&&Array.isArray(t)&&0===t.length,a=null==t||r?null:j(t,e).sort();let i=0;for(let t=0;tt)&&1===e[t]&&(n.push(e[t]),s.push(t)),a[i]<=t&&i++}1!==e[t]&&(n.push(e[t]),s.push(t))}return{newShape:n,keptDims:s}}function K(e,t){let n=null;if(null==e||"float32"===e)n=new Float32Array(t);else if("int32"===e)n=new Int32Array(t);else{if("bool"!==e)throw new Error(`Unknown data type ${e}`);n=new Uint8Array(t)}return n}function X(e,t){let n=null;if(null==e||"float32"===e)n=new Float32Array(t);else if("int32"===e)n=new Int32Array(t);else if("bool"===e)n=new Uint8Array(t);else{if("string"!==e)throw new Error(`Unknown data type ${e}`);n=new Array(t)}return n}function Y(e,t){return"complex64"!==t&&(("float32"!==t||"complex64"===e)&&(("int32"!==t||"float32"===e||"complex64"===e)&&("bool"!==t||"bool"!==e)))}function Z(e){return e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray}function J(e){if("float32"===e||"int32"===e)return 4;if("complex64"===e)return 8;if("bool"===e)return 1;throw new Error(`Unknown dtype ${e}`)}function Q(e){return"string"==typeof e||e instanceof String}function ee(e){return"number"==typeof e}function te(e){return Array.isArray(e)?te(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray?"int32":ee(e)?"float32":Q(e)?"string":"boolean"==typeof e?"bool":"float32"}function ne(e){return!!(e&&e.constructor&&e.call&&e.apply)}function se(e,t){for(let n=t;n=0;--s)n[s]=n[s+1]*e[s+1];return n}function ae(e,t,n,s=!1){const r=new Array;if(1===t.length){const a=t[0]*(s?2:1);for(let t=0;te*t))*(s?2:1);for(let t=0;te*t))*(n?2:1);if(0===s)return[];if(s!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}${n?" for a complex tensor":""}.`);return ae(0,e,t,n)}function oe(e,t){const n=le(e,t);for(let e=0;ee*t),1);if(null==t||"float32"===t)return ie(e,new Float32Array(n));if("int32"===t)return ie(e,new Int32Array(n));if("bool"===t)return ie(e,new Uint8Array(n));throw new Error(`Unknown data type ${t}`)}function ce(e){e.forEach((t=>{O(Number.isInteger(t)&&t>=0,(()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`))}))}function he(e,t,n){if(0===t)return 0;if(1===t)return e[0];let s=e[e.length-1];for(let t=0;t{const[t,n]=e.split(":");this.urlFlags[t]=function(e,t){if("true"===(t=t.toLowerCase())||"false"===t)return"true"===t;if(""+ +t===t)return+t;throw new Error(`Could not parse value flag value ${t} for flag ${e}.`)}(t,n)}))}}}function ge(e){const t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,((e,...n)=>(function(e,t,n){e[decodeURIComponent(t)]=decodeURIComponent(n||"")}(t,n[0],n[1]),n.join("=")))),t}function ye(){return xe}let be,xe=null;function we(){if(null==be){let e;if("undefined"!=typeof window)e=window;else if(void 0!==n.g)e=n.g;else if("undefined"!=typeof process)e=process;else{if("undefined"==typeof self)throw new Error("Could not find a global object");e=self}be=e}return be}function ve(e,t){const n=function(){const e=we();return null==e._tfGlobals&&(e._tfGlobals=new Map),e._tfGlobals}();if(n.has(e))return n.get(e);{const s=t();return n.set(e,s),n.get(e)}}const ke="Abs",Ie="Acos",Ne="Acosh",Se="Add",Te="AddN",Ce="All",$e="Any",Ee="ArgMax",Re="ArgMin",Ae="Asin",Fe="Asinh",_e="Atan",De="Atanh",Oe="Atan2",Me="AvgPool",Le="AvgPoolGrad",ze="AvgPool3D",Pe="AvgPool3DGrad",Be="BatchMatMul",We="BatchToSpaceND",Ve="Bincount",Ue="BroadcastArgs",Ge="Cast",He="Ceil",je="ClipByValue",qe="Complex",Ke="ComplexAbs",Xe="Concat",Ye="Conv2D",Ze="Conv2DBackpropFilter",Je="Conv2DBackpropInput",Qe="Conv3D",et="Conv3DBackpropFilterV2",tt="Conv3DBackpropInputV2",nt="Cos",st="Cosh",rt="Cumprod",at="Cumsum",it="CropAndResize",ot="DenseBincount",lt="DepthToSpace",ut="DepthwiseConv2dNative",ct="DepthwiseConv2dNativeBackpropFilter",ht="DepthwiseConv2dNativeBackpropInput",pt="Diag",dt="Dilation2D",ft="Dilation2DBackpropInput",mt="Dilation2DBackpropFilter",gt="RealDiv",yt="Einsum",bt="Elu",xt="EluGrad",wt="Erf",vt="Equal",kt="Exp",It="ExpandDims",Nt="Expm1",St="FFT",Tt="Fill",Ct="FlipLeftRight",$t="Floor",Et="FloorDiv",Rt="FusedBatchNorm",At="GatherV2",Ft="GatherNd",_t="Greater",Dt="GreaterEqual",Ot="Identity",Mt="IFFT",Lt="Imag",zt="IsFinite",Pt="IsInf",Bt="IsNan",Wt="LeakyRelu",Vt="Less",Ut="LessEqual",Gt="LinSpace",Ht="Log",jt="Log1p",qt="LogicalAnd",Kt="LogicalNot",Xt="LogicalOr",Yt="LRN",Zt="LRNGrad",Jt="Max",Qt="Maximum",en="MaxPool",tn="MaxPoolGrad",nn="MaxPool3D",sn="MaxPool3DGrad",rn="MaxPoolWithArgmax",an="Mean",on="Min",ln="Minimum",un="MirrorPad",cn="Mod",hn="Multinomial",pn="Multiply",dn="Neg",fn="NotEqual",mn="NonMaxSuppressionV3",gn="NonMaxSuppressionV4",yn="NonMaxSuppressionV5",bn="OnesLike",xn="OneHot",wn="Pack",vn="PadV2",kn="Pow",In="Prelu",Nn="Prod",Sn="RaggedGather",Tn="RaggedTensorToTensor",Cn="Range",$n="Real",En="Reciprocal",Rn="Relu",An="Reshape",Fn="ResizeNearestNeighbor",_n="ResizeNearestNeighborGrad",Dn="ResizeBilinear",On="ResizeBilinearGrad",Mn="Relu6",Ln="Reverse",zn="Round",Pn="Rsqrt",Bn="ScatterNd",Wn="SearchSorted",Vn="Select",Un="Selu",Gn="Slice",Hn="Sin",jn="Sinh",qn="Sign",Kn="Sigmoid",Xn="Softplus",Yn="Sqrt",Zn="Sum",Jn="SpaceToBatchND",Qn="SplitV",es="Softmax",ts="SparseFillEmptyRows",ns="SparseReshape",ss="SparseSegmentMean",rs="SparseSegmentSum",as="SparseToDense",is="SquaredDifference",os="Square",ls="StridedSlice",us="StringNGrams",cs="StringSplit",hs="StringToHashBucketFast",ps="Sub",ds="Tan",fs="Tanh",ms="Tile",gs="TopK",ys="Transform",bs="Transpose",xs="Unique",ws="Unpack",vs="UnsortedSegmentSum",ks="ZerosLike",Is="Step",Ns="FromPixels",Ss="RotateWithOffset",Ts="_FusedMatMul",Cs="FusedConv2D",$s="FusedDepthwiseConv2D";
+/**
+ * @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 Es(...e){ye().getBool("IS_TEST")||ye().getBool("PROD")||console.warn(...e)}function Rs(...e){ye().getBool("IS_TEST")||ye().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 As=ve("kernelRegistry",(()=>new Map)),Fs=ve("gradRegistry",(()=>new Map));function _s(e,t){const n=zs(e,t);return As.get(n)}function Ds(e){return Fs.get(e)}function Os(e){const t=As.entries(),n=[];for(;;){const{done:s,value:r}=t.next();if(s)break;const[a,i]=r,[o]=a.split("_");o===e&&n.push(i)}return n}function Ms(e){const{kernelName:t,backendName:n}=e,s=zs(t,n);As.has(s)&&Es(`The kernel '${t}' for backend '${n}' is already registered`),As.set(s,e)}function Ls(e){const{kernelName:t}=e;Fs.has(t)&&ye().getBool("DEBUG")&&Es(`Overriding the gradient for '${t}'`),Fs.set(t,e)}function zs(e,t){return`${t}_${e}`}var Ps=n(570);
+/**
+ * @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 Bs=n.n(Ps)()||Ps;function Ws(e){return Bs.fromString(e,!0,16)}const Vs=Ws("c3a5c85c97cb3127"),Us=Ws("b492b66fbe98f273"),Gs=Ws("9ae16a3b2f90404f");function Hs(e){return e.xor(e.shru(47))}function js(e,t,n){const s=e.slice(t,t+n);return Bs.fromBytes(Array.from(s),!0,!0)}function qs(e,t){return js(e,t,8)}function Ks(e,t){return js(e,t,4)}function Xs(e,t){return 0===t?e:e.shru(t).or(e.shl(64-t))}function Ys(e,t,n=Ws("9ddfea08eb382d69")){let s=e.xor(t).mul(n);s=s.xor(s.shru(47));let r=t.xor(s).mul(n);return r=r.xor(r.shru(47)),r=r.mul(n),r}function Zs(e,t,n,s){return function(e,t,n,s,r,a){r=r.add(e),a=Xs(a.add(r).add(s),21);const i=r;return r=(r=r.add(t)).add(n),a=a.add(Xs(r,44)),[r.add(s),a.add(i)]}(qs(e,t),qs(e,t+8),qs(e,t+16),qs(e,t+24),n,s)}function Js(e,t=e.length){const n=Bs.fromNumber(81,!0);if(t<=32)return t<=16?function(e,t=e.length){if(t>=8){const n=Gs.add(2*t),s=qs(e,0).add(Gs),r=qs(e,t-8);return Ys(Xs(r,37).mul(n).add(s),Xs(s,25).add(r).mul(n),n)}if(t>=4){const n=Gs.add(2*t);return Ys(Ks(e,0).shl(3).add(t),Ks(e,t-4),n)}if(t>0){const n=e[0]+(e[t>>1]<<8),s=t+(e[t-1]<<2);return Hs(Gs.mul(n).xor(Vs.mul(s))).mul(Gs)}return Gs}(e,t):function(e,t=e.length){const n=Gs.add(2*t),s=qs(e,0).mul(Us),r=qs(e,8),a=qs(e,t-8).mul(n),i=qs(e,t-16).mul(Gs);return Ys(Xs(s.add(r),43).add(Xs(a,30)).add(i),s.add(Xs(r.add(Gs),18)).add(a),n)}(e,t);if(t<=64)return function(e,t=e.length){const n=Gs.add(2*t),s=qs(e,0).mul(Gs),r=qs(e,8),a=qs(e,t-8).mul(n),i=qs(e,t-16).mul(Gs),o=Xs(s.add(r),43).add(Xs(a,30)).add(i),l=Ys(o,s.add(Xs(r.add(Gs),18)).add(a),n),u=qs(e,16).mul(n),c=qs(e,24),h=o.add(qs(e,t-32)).mul(n),p=l.add(qs(e,t-24)).mul(n);return Ys(Xs(u.add(c),43).add(Xs(h,30)).add(p),u.add(Xs(c.add(s),18)).add(h),n)}(e,t);let s=n,r=n.mul(Us).add(113),a=Hs(r.mul(Gs).add(113)).mul(Gs),i=[Bs.UZERO,Bs.UZERO],o=[Bs.UZERO,Bs.UZERO];s=s.mul(Gs).add(qs(e,0));let l=0;const u=64*(t-1>>6),c=u+(t-1&63)-63;do{s=Xs(s.add(r).add(i[0]).add(qs(e,l+8)),37).mul(Us),r=Xs(r.add(i[1]).add(qs(e,l+48)),42).mul(Us),s=s.xor(o[1]),r=r.add(i[0]).add(qs(e,l+40)),a=Xs(a.add(o[0]),33).mul(Us),i=Zs(e,l,i[1].mul(Us),s.add(o[0])),o=Zs(e,l+32,a.add(o[1]),r.add(qs(e,l+16))),[a,s]=[s,a],l+=64}while(l!==u);const h=Us.add(a.and(255).shl(1));return l=c,o[0]=o[0].add(t-1&63),i[0]=i[0].add(o[0]),o[0]=o[0].add(i[0]),s=Xs(s.add(r).add(i[0]).add(qs(e,l+8)),37).mul(h),r=Xs(r.add(i[1]).add(qs(e,l+48)),42).mul(h),s=s.xor(o[1].mul(9)),r=r.add(i[0].mul(9).add(qs(e,l+40))),a=Xs(a.add(o[0]),33).mul(h),i=Zs(e,l,i[1].mul(h),s.add(o[0])),o=Zs(e,l+32,a.add(o[1]),r.add(qs(e,l+16))),[a,s]=[s,a],Ys(Ys(i[0],o[0],h).add(Hs(r).mul(Vs)).add(a),Ys(i[1],o[1],h).add(s),h)}
+/**
+ * @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 Qs(e,t){return"string"===t?nr(e):er([e],t)}function er(e,t){if("string"===t)throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=z(e)),ye().getBool("DEBUG")&&function(e,t){for(let n=0;n{s=n()};let a;const i=tr();if(this.backendTimer.timerAvailable())a=this.backendTimer.time(r);else{r();for(const e of s)e.dataSync();a=Promise.resolve({kernelMs:tr()-i})}if(ye().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let t=0;t{ar(t,n.dtype,e)}))}return{kernelName:e,outputs:s,inputs:t,timeMs:a.then((e=>e.kernelMs)),extraInfo:a.then((e=>null!=e.getExtraProfileInfo?e.getExtraProfileInfo():""))}}logKernelProfile(e){const{kernelName:t,outputs:n,timeMs:s,inputs:r,extraInfo:a}=e;n.forEach((e=>{Promise.all([e.data(),s,a]).then((n=>{this.logger.logKernelProfile(t,e,n[0],n[1],r,n[2])}))}))}}function ar(e,t,n){if("float32"!==t)return!1;for(let t=0;t0?s:""} `}}console.log(`%c${o}\t%c${i}\t%c${l}D ${c}\t%c${u}\t%c${h}\t%c${a}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}}function or(e,t,n,s){const r=re(t),a=function(e,t,n,s){const r=P(t),a=s[s.length-1],i=new Array(a).fill(0),o=t.length,l="complex64"===n?hr(e):e;if(o>1)for(let e=0;e" "+e)).join("\n")),l.join("\n")}function lr(e,t,n){let s;return s=Array.isArray(e)?`${parseFloat(e[0].toFixed(7))} + ${parseFloat(e[1].toFixed(7))}j`:Q(e)?`'${e}'`:"bool"===n?ur(e):parseFloat(e.toFixed(7)).toString(),U(s,t)}function ur(e){return 0===e?"false":"true"}function cr(e,t,n,s,r,a=!0){const i="complex64"===n?2:1,o=t[0],l=t.length;if(0===l){if("complex64"===n){return[lr(hr(e)[0],0,n)]}return"bool"===n?[ur(e[0])]:[e[0].toString()]}if(1===l){if(o>20){const t=3*i;let s=Array.from(e.slice(0,t)),a=Array.from(e.slice((o-3)*i,o*i));return"complex64"===n&&(s=hr(s),a=hr(a)),["["+s.map(((e,t)=>lr(e,r[t],n))).join(", ")+", ..., "+a.map(((e,t)=>lr(e,r[o-3+t],n))).join(", ")+"]"]}return["["+("complex64"===n?hr(e):Array.from(e)).map(((e,t)=>lr(e,r[t],n))).join(", ")+"]"]}const u=t.slice(1),c=s.slice(1),h=s[0]*i,p=[];if(o>20){for(let t=0;t<3;t++){const s=t*h,a=s+h;p.push(...cr(e.slice(s,a),u,n,c,r,!1))}p.push("...");for(let t=o-3;t`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||X(t,this.size),this.strides=re(e)}set(e,...t){0===t.length&&(t=[0]),O(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;tsr(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(),dr().readToGPU(this.dataId,e)}dataSync(){this.throwIfDisposed();const e=dr().readSync(this.dataId);if("string"===this.dtype)try{return e.map((e=>sr(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 dr().read(this.dataId);return"string"===this.dtype?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(dr().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return fr.print(this,e)}clone(){return this.throwIfDisposed(),fr.clone(this)}toString(e=!1){return or(this.dataSync(),this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),fr.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),dr().makeVariable(this,e,t,n)}}function yr(){return ve("Tensor",(()=>gr))}Object.defineProperty(gr,Symbol.hasInstance,{value:e=>!!e&&null!=e.data&&null!=e.dataSync&&null!=e.throwIfDisposed}),yr();class br extends gr{constructor(e,t,n,s){super(e.shape,e.dtype,e.dataId,s),this.trainable=t,this.name=n}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!B(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);dr().disposeTensor(this),this.dataId=e.dataId,dr().incRef(this,null)}dispose(){dr().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 xr,wr,vr,kr,Ir;Object.defineProperty(br,Symbol.hasInstance,{value:e=>e instanceof gr&&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"}(xr||(xr={})),function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"}(wr||(wr={})),function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"}(vr||(vr={})),function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"}(kr||(kr={})),function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"}(Ir||(Ir={}));const Nr={float32:kr,int32:wr,bool:vr,complex64:Ir};function Sr(e,t){if("string"===e||"string"===t){if("string"===e&&"string"===t)return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return Nr[e][t]}function Tr(e){return Sr(e,"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 Cr(e,t){if(e.dtype===t.dtype)return[e,t];const n=Sr(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function $r(e,t){return t.some((t=>t.id===e.id))}function Er(e){const t=[];return Rr(e,t,new Set),t}function Rr(e,t,n){if(null==e)return;if(e instanceof gr)return void t.push(e);if(s=e,!Array.isArray(s)&&"object"!=typeof s)return;var s;const r=e;for(const e in r){const s=r[e];n.has(s)||(n.add(s),Rr(s,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 Ar(e){return null!=e.kernelName}class Fr{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 _r{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Fr}async ready(){if(null!=this.pendingBackendInit)return this.pendingBackendInit.then((()=>{}));if(null!=this.backendInstance)return;const e=this.getSortedBackends();for(let t=0;t{null!=e.setupFunc&&e.setupFunc(this.backendInstance)}))}disposeRegisteredKernels(e){Os(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 ${e}, no registration found.`);try{const n=t.factory();if(!n||n instanceof E||"function"!=typeof n.then)return this.registry[e]=n,{success:!0,asyncInit:!1};{const t=++this.pendingBackendInitId,s=n.then((n=>!(t(tthis.registryFactory[t].priority-this.registryFactory[e].priority))}initializeBackendsAndReturnBest(){const e=this.getSortedBackends();for(let t=0;tthis.startScope(s)),(()=>this.endScope(n)),(()=>(n=t(),n instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n)))}scopedRun(e,t,n){e();try{const e=n();return t(),e}catch(e){throw t(),e}}nextTensorId(){return _r.nextTensorId++}nextVariableId(){return _r.nextVariableId++}clone(e){const t=Or.runKernel(Ot,{x:e}),n={x:e};return this.addTapeNode(this.state.activeScope.name,n,[t],(e=>({x:()=>{const t={x:e},n={dtype:"float32"};return Or.runKernel(Ge,t,n)}})),[],{}),t}runKernel(e,t,n){null==this.backendName&&this.backend;if(!(null!=_s(e,this.backendName)))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){const s=this.backend.numDataIds();let r=0;n.forEach((e=>{r+="complex64"===e.dtype?3:1}));const a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=s-t-r-a;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[];const s=this.isTapeOn(),r=this.state.numBytes,a=this.state.numTensors;let i,o;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0),null==this.backendName&&this.backend;const l=Ar(e)?e.kernelName:null!=this.state.activeScope?this.state.activeScope.name:"";if(Ar(e)){const{kernelName:t,inputs:r,attrs:a}=e;null==this.backendName&&this.backend;const l=_s(t,this.backendName);O(null!=l,(()=>`Cannot find registered kernel '${t}' for backend '${this.backendName}'`)),i=()=>{const e=this.backend.numDataIds();o=l.kernelFunc({inputs:r,attrs:a,backend:this.backend});const i=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(t,e,i);const u=i.map((e=>null!=e.rank?e:this.makeTensorFromTensorInfo(e)));if(s){const e=this.getTensorsForGradient(t,r,u);n=this.saveTensorsForBackwardMode(e)}return u}}else{const{forwardFunc:t}=e,r=e=>{s&&(n=e.map((e=>this.keep(this.clone(e)))))};i=()=>{const e=this.backend.numDataIds();o=this.tidy((()=>t(this.backend,r)));const n=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,e,n),n}}const{inputs:u,attrs:c}=e,h=Ar(e)?null:e.backwardsFunc;let p;return this.scopedRun((()=>this.state.kernelDepth++),(()=>this.state.kernelDepth--),(()=>{this.ENV.getBool("DEBUG")||this.state.profiling?(p=this.profiler.profileKernel(l,u,(()=>i())),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(p),t=p.outputs):t=i()})),s&&this.addTapeNode(l,u,t,h,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map((e=>null!=u[e]?u[e].shape:null)),outputShapes:t.map((e=>e.shape)),kernelTimeMs:p.timeMs,extraInfo:p.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){const t=e.map((e=>this.keep(this.clone(e))));return t}getTensorsForGradient(e,t,n){const s=Ds(e);if(null!=s){const e=s.inputsToSave||[],r=s.outputsToSave||[];let a;s.saveAllInputs?(O(Array.isArray(t),(()=>"saveAllInputs is true, expected inputs to be an array.")),a=Object.keys(t).map((e=>t[e]))):a=e.map((e=>t[e]));const i=n.filter(((e,t)=>r[t]));return a.concat(i)}return[]}makeTensor(e,t,n,s){if(null==e)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",s=s||this.backend;let r=e;"string"===n&&Q(e[0])&&(r=e.map((e=>nr(e))));const a=s.write(r,t,n),i=new gr(t,n,a,this.nextTensorId());if(this.trackTensor(i,s),"string"===n){const e=this.state.tensorInfo.get(a),t=function(e){if(null==e)return 0;let t=0;return e.forEach((e=>t+=e.length)),t}(r);this.state.numBytes+=t-e.bytes,e.bytes=t}return i}makeTensorFromDataId(e,t,n,s){const r={dataId:e,shape:t,dtype:n=n||"float32"};return this.makeTensorFromTensorInfo(r,s)}makeTensorFromTensorInfo(e,t){const{dataId:n,shape:s,dtype:r}=e,a=new gr(s,r,n,this.nextTensorId());return this.trackTensor(a,t),a}makeVariable(e,t=!0,n,s){n=n||this.nextVariableId().toString(),null!=s&&s!==e.dtype&&(e=e.cast(s));const r=new br(e,t,n,this.nextTensorId());if(null!=this.state.registeredVariables[r.name])throw new Error(`Variable with name ${r.name} was already registered`);return this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,"string"===e.dtype&&this.state.numStringTensors++;let n=0;"complex64"!==e.dtype&&"string"!==e.dtype&&(n=e.size*J(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 br||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*J(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,s,r,a){const i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:r},o=Ds(e);null!=o&&(s=o.gradFunc),null!=s&&(i.gradient=e=>(e=e.map(((e,t)=>{if(null==e){const e=n[t],s=le(e.size,e.dtype);return this.makeTensor(s,e.shape,e.dtype)}return e})),s(e.length>1?e:e[0],r,a))),this.state.activeTape.push(i)}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=Er(e),n=new Set(t.map((e=>e.id)));for(let e=0;e{e.kept||e.scopeId!==s.id||this.track(e)}))}gradients(e,t,n,s=!1){if(O(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 r=this.scopedRun((()=>this.startTape()),(()=>this.endTape()),(()=>this.tidy("forward",e)));O(r instanceof gr,(()=>"The result y returned by f() must be a tensor."));const a=
+/**
+ * @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 s={},r={};for(let e=0;es[e.id]=!0)),o=!0,r[a.id]=!0;break}if(o)break}}const a={};a[n.id]=!0;const i={};for(let t=e.length-1;t>=0;t--){const n=e[t],s=n.inputs;for(let e=0;e0)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[r.id]=null==n?function(e){const t=oe(P(e),"float32");return Or.makeTensor(t,e,"float32")}(r.shape):n,function(e,t,n,s){for(let r=t.length-1;r>=0;r--){const a=t[r],i=[];if(a.outputs.forEach((t=>{const n=e[t.id];null!=n?i.push(n):i.push(null)})),null==a.gradient)throw new Error(`Cannot compute gradient: gradient function not found for ${a.kernelName}.`);const o=a.gradient(i);for(const t in a.inputs){if(!(t in o))throw new Error(`Cannot backprop through input ${t}. Available gradients found: ${Object.keys(o)}.`);const r=n((()=>o[t]()));if("float32"!==r.dtype)throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input ${t} must have 'float32' dtype, but has '${r.dtype}'`);const i=a.inputs[t];if(!B(r.shape,i.shape))throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input '${t}' has shape '${r.shape}', which does not match the shape of the input '${i.shape}'`);if(null==e[i.id])e[i.id]=r;else{const t=e[i.id];e[i.id]=s(t,r),t.dispose()}}}}(e,a,(e=>this.tidy(e)),Mr);const s=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:r,grads:s}}))}customGrad(e){return O(ne(e),(()=>"The f passed in customGrad(f) must be a function.")),(...t)=>{let n;O(t.every((e=>e instanceof gr)),(()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors"));const s={};t.forEach(((e,t)=>{s[t]=e}));return this.runKernelFunc({forwardFunc:(s,r)=>(n=e(...t,r),O(n.value instanceof gr,(()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor")),O(ne(n.gradFunc),(()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function.")),n.value),backwardsFunc:(e,s)=>{const r=n.gradFunc(e,s),a=Array.isArray(r)?r:[r];O(a.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(...).")),O(a.every((e=>e instanceof gr)),(()=>"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 i={};return a.forEach(((e,t)=>{i[t]=()=>e})),i},inputs:s})}}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=tr(),n=await this.backend.time(e);return n.wallMs=tr()-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 Fr;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 Dr(){const e=we();if(null==e._tfengine){const t=new me(e);e._tfengine=new _r(t)}var t;return t=e._tfengine.ENV,xe=t,dr=()=>e._tfengine,e._tfengine}_r.nextTensorId=0,_r.nextVariableId=0;const Or=Dr();function Mr(e,t){const n={a:e,b:t};return Or.runKernel(Se,n)}let Lr;function zr(e){if(void 0!==Lr)return Lr;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 Pr(){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 Br=ye();
+/**
+ * @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 Wr(e,t){let n=e;if(Z(e))return"string"===t?[]:[e.length];if(!Array.isArray(e))return[];const s=[];for(;Array.isArray(n)||Z(n)&&"string"!==t;)s.push(n.length),n=n[0];return Array.isArray(e)&&ye().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&Vr(e,s,[]),s}function Vr(e,t,n){if(n=n||[],!Array.isArray(e)&&!Z(e))return void O(0===t.length,(()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`));O(t.length>0,(()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`)),O(e.length===t[0],(()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`));const s=t.slice(1);for(let t=0;t=0&&(r=s),Ur(s,r,t,n),null==e||!Z(e)&&!Array.isArray(e)&&"number"!=typeof e&&"boolean"!=typeof e&&"string"!=typeof e){const s=null==e?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${s}'`)}const a=Wr(e,r);Z(e)||Array.isArray(e)||(e=[e]);const i="string"!==r?er(e,r):z(e,[],!0);return Or.makeTensor(i,a,r)}function Hr(e,t,n,s="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map(((e,r)=>Gr(e,`${t}[${r}]`,n,s)))}Br.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.")})),Br.registerFlag("IS_BROWSER",(()=>Pr())),Br.registerFlag("IS_NODE",(()=>"undefined"!=typeof process&&void 0!==process.versions&&void 0!==process.versions.node)),Br.registerFlag("IS_CHROME",(()=>"undefined"!=typeof navigator&&null!=navigator&&null!=navigator.userAgent&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor))),Br.registerFlag("PROD",(()=>!1)),Br.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",(()=>Br.getBool("DEBUG"))),Br.registerFlag("DEPRECATION_WARNINGS_ENABLED",(()=>!0)),Br.registerFlag("IS_TEST",(()=>!1)),Br.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",(()=>!0)),Br.registerFlag("WRAP_TO_IMAGEBITMAP",(()=>!1)),Br.registerFlag("ENGINE_COMPILE_ONLY",(()=>!1)),Br.registerFlag("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU",(()=>!1)),Br.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 jr="__op";function qr(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 s=e[n];n.endsWith("_")&&(n=n.substring(0,n.length-1)),n+=jr;const r=(...e)=>{Or.startScope(n);try{const t=s(...e);return de(t)&&console.error("Cannot return a Promise inside of tidy."),Or.endScope(t),t}catch(e){throw Or.endScope(null),e}};return Object.defineProperty(r,"name",{value:n,configurable:!0}),r}const Kr=qr({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=Gr(e,"real","complex"),s=Gr(t,"imag","complex");M(n.shape,s.shape,`real and imag shapes, ${n.shape} and ${s.shape}, must match in call to tf.complex().`);const r={real:n,imag:s};return Or.runKernel(qe,r)}});
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function Xr(e,t,n,s){if(null==s&&(s=te(e)),"complex64"===s)throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(!Z(e)&&!Array.isArray(e)&&"number"!=typeof e&&"boolean"!=typeof e&&"string"!=typeof e)throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(null!=t){ce(t);const e=P(t),s=P(n);O(e===s,(()=>`Based on the provided shape, [${t}], the tensor should have ${e} values but has ${s}`));for(let e=0;e`Error creating a new Tensor. Inferred shape (${n}) does not match the provided shape (${t}). `))}}return Z(e)||Array.isArray(e)||(e=[e]),t=t||n,e="string"!==s?er(e,s):z(e,[],!0),Or.makeTensor(e,t,s)}
+/**
+ * @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 Yr(e,t,n){return Xr(e,t,Wr(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 Zr={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},Jr=4;async function Qr(e,t){const n=[],s=[],r=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);for(let a=0;a{const t=await o.bytes(),n=t.reduce(((e,t)=>e+t.length),0)+Jr*t.length,s=new Uint8Array(n);let r=0;for(let e=0;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 s=new Uint8Array(t);let r=0;return n.forEach((e=>{s.set(new Uint8Array(e.buffer),r),r+=e.byteLength})),s.buffer}const na="undefined"!=typeof Buffer&&("undefined"==typeof Blob||"undefined"==typeof atob||"undefined"==typeof btoa);function sa(e){return na?Buffer.byteLength(e):new Blob([e]).size}function ra(e){if(1===e.length)return e[0];let t=0;e.forEach((e=>{t+=e.byteLength}));const n=new Uint8Array(t);let s=0;return e.forEach((e=>{n.set(new Uint8Array(e),s),s+=e.byteLength})),n.buffer}function aa(e){for(e=e.trim();e.endsWith("/");)e=e.slice(0,e.length-1);const t=e.split("/");return t[t.length-1]}function ia(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.trainingConfig&&(n.trainingConfig=e.trainingConfig),n}function oa(e,t,n){const s={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy};if(null!=e.trainingConfig&&(s.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");s.weightSpecs=t,s.weightData=n}return null!=e.signature&&(s.signature=e.signature),null!=e.userDefinedMetadata&&(s.userDefinedMetadata=e.userDefinedMetadata),null!=e.modelInitializer&&(s.modelInitializer=e.modelInitializer),s}async function la(e,t){let n,s;return null!=e.weightsManifest&&([n,s]=await t(e.weightsManifest)),oa(e,n,s)}function ua(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:sa(JSON.stringify(e.modelTopology)),weightSpecsBytes:null==e.weightSpecs?0:sa(JSON.stringify(e.weightSpecs)),weightDataBytes:null==e.weightData?0:e.weightData.byteLength}}function ca(e){const t=[];for(const n of e)t.push(...n.weights);return t}function ha(){const e=function(){const e=e=>{let t=e<<13,n=0;for(;!(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 s=>{const r=new ArrayBuffer(4*s.length),a=new Uint32Array(r);for(let r=0;r>10]+(1023&i)]+t[i>>10];a[r]=o}return new Float32Array(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 pa{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return null==pa.instance&&(pa.instance=new pa),pa.instance}static registerSaveRouter(e){pa.getInstance().saveRouters.push(e)}static registerLoadRouter(e){pa.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return pa.getHandlers(e,"save")}static getLoadHandlers(e,t){return pa.getHandlers(e,"load",t)}static getHandlers(e,t,n){const s=[];return("load"===t?pa.getInstance().loadRouters:pa.getInstance().saveRouters).forEach((t=>{const r=t(e,n);null!==r&&s.push(r)})),s}}const da=e=>pa.registerSaveRouter(e),fa=e=>pa.registerLoadRouter(e),ma=e=>pa.getSaveHandlers(e),ga=(e,t)=>pa.getLoadHandlers(e,t),ya="tensorflowjs",ba="models_store",xa="model_info_store";function wa(){if(!ye().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 va(e){const t=e.result;t.createObjectStore(ba,{keyPath:"modelPath"}),t.createObjectStore(xa,{keyPath:"modelPath"})}class ka{constructor(e){if(this.indexedDB=wa(),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 s=this.indexedDB.open(ya,1);s.onupgradeneeded=()=>va(s),s.onsuccess=()=>{const r=s.result;if(null==t){const t=r.transaction(ba,"readonly"),s=t.objectStore(ba).get(this.modelPath);s.onsuccess=()=>{if(null==s.result)return r.close(),n(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));e(s.result.modelArtifacts)},s.onerror=e=>(r.close(),n(s.error)),t.oncomplete=()=>r.close()}else{const s=ua(t),a=r.transaction(xa,"readwrite");let i=a.objectStore(xa);const o=i.put({modelPath:this.modelPath,modelArtifactsInfo:s});let l;o.onsuccess=()=>{l=r.transaction(ba,"readwrite");const o=l.objectStore(ba).put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:s});o.onsuccess=()=>e({modelArtifactsInfo:s}),o.onerror=e=>{i=a.objectStore(xa);const t=i.delete(this.modelPath);t.onsuccess=()=>(r.close(),n(o.error)),t.onerror=e=>(r.close(),n(o.error))}},o.onerror=e=>(r.close(),n(o.error)),a.oncomplete=()=>{null==l?r.close():l.oncomplete=()=>r.close()}}},s.onerror=e=>n(s.error)}))}}ka.URL_SCHEME="indexeddb://";const Ia=e=>{return ye().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(ka.URL_SCHEME)?(t=e.slice(ka.URL_SCHEME.length),new ka(t)):null;var t};pa.registerSaveRouter(Ia),pa.registerLoadRouter(Ia);class Na{constructor(){this.indexedDB=wa()}async listModels(){return new Promise(((e,t)=>{const n=this.indexedDB.open(ya,1);n.onupgradeneeded=()=>va(n),n.onsuccess=()=>{const s=n.result,r=s.transaction(xa,"readonly"),a=r.objectStore(xa).getAll();a.onsuccess=()=>{const t={};for(const e of a.result)t[e.modelPath]=e.modelArtifactsInfo;e(t)},a.onerror=e=>(s.close(),t(a.error)),r.oncomplete=()=>s.close()},n.onerror=e=>t(n.error)}))}async removeModel(e){var t;return e=(t=e).startsWith(ka.URL_SCHEME)?t.slice(ka.URL_SCHEME.length):t,new Promise(((t,n)=>{const s=this.indexedDB.open(ya,1);s.onupgradeneeded=()=>va(s),s.onsuccess=()=>{const r=s.result,a=r.transaction(xa,"readwrite"),i=a.objectStore(xa),o=i.get(e);let l;o.onsuccess=()=>{if(null==o.result)return r.close(),n(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{const s=i.delete(e),a=()=>{l=r.transaction(ba,"readwrite");const s=l.objectStore(ba).delete(e);s.onsuccess=()=>t(o.result.modelArtifactsInfo),s.onerror=e=>n(o.error)};s.onsuccess=a,s.onerror=e=>(a(),r.close(),n(o.error))}},o.onerror=e=>(r.close(),n(o.error)),a.oncomplete=()=>{null==l?r.close():l.oncomplete=()=>r.close()}},s.onerror=e=>n(s.error)}))}}
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+const Sa="/",Ta="tensorflowjs_models",Ca="info",$a="model_topology",Ea="weight_specs",Ra="weight_data",Aa="model_metadata";function Fa(e){return{info:[Ta,e,Ca].join(Sa),topology:[Ta,e,$a].join(Sa),weightSpecs:[Ta,e,Ea].join(Sa),weightData:[Ta,e,Ra].join(Sa),modelMetadata:[Ta,e,Aa].join(Sa)}}function _a(e){for(const t of Object.values(e))window.localStorage.removeItem(t)}function Da(e){const t=e.split(Sa);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(Sa)}class Oa{constructor(e){if(!ye().getBool("IS_BROWSER")||"undefined"==typeof window||void 0===window.localStorage)throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,null==e||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=Fa(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{const t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),s=ua(e);try{this.LS.setItem(this.keys.info,JSON.stringify(s)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,function(e){if(na)return Buffer.from(e).toString("base64");const t=new Uint8Array(e);let n="";for(let e=0,s=t.length;e{return ye().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Oa.URL_SCHEME)?(t=e.slice(Oa.URL_SCHEME.length),new Oa(t)):null;var t};pa.registerSaveRouter(Ma),pa.registerLoadRouter(Ma);class La{constructor(){O(ye().getBool("IS_BROWSER"),(()=>"Current environment is not a web browser")),O("undefined"==typeof window||void 0!==window.localStorage,(()=>"Current browser does not appear to support localStorage")),this.LS=window.localStorage}async listModels(){const e={},t=Ta+Sa,n=Sa+Ca;for(let s=0;s"scheme must not be undefined or null.")),e.endsWith(za)&&(e=e.slice(0,e.indexOf(za))),O(e.length>0,(()=>"scheme must not be an empty string."));const n=Pa.getInstance();O(null==n.managers[e],(()=>`A model store manager is already registered for scheme '${e}'.`)),n.managers[e]=t}static getManager(e){const t=Pa.getInstance().managers[e];if(null==t)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return Object.keys(Pa.getInstance().managers)}}function Ba(e){if(-1===e.indexOf(za))throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${Pa.getSchemes().join(",")}`);return{scheme:e.split(za)[0],path:e.split(za)[1]}}async function Wa(e,t,n=!1){O(e!==t,(()=>`Old path and new path are the same: '${e}'`));const s=pa.getLoadHandlers(e);O(s.length>0,(()=>`Copying failed because no load handler is found for source URL ${e}.`)),O(s.length<2,(()=>`Copying failed because more than one (${s.length}) load handlers for source URL ${e}.`));const r=s[0],a=pa.getSaveHandlers(t);O(a.length>0,(()=>`Copying failed because no save handler is found for destination URL ${t}.`)),O(a.length<2,(()=>`Copying failed because more than one (${s.length}) save handlers for destination URL ${t}.`));const i=a[0],o=Ba(e).scheme,l=Ba(e).path,u=o===Ba(e).scheme,c=await r.load();n&&u&&await Pa.getManager(o).removeModel(l);const h=await i.save(c);return n&&!u&&await Pa.getManager(o).removeModel(l),h.modelArtifactsInfo}async function Va(){const e=Pa.getSchemes(),t={};for(const n of e){const e=await Pa.getManager(n).listModels();for(const s in e){t[n+za+s]=e[s]}}return t}async function Ua(e){const t=Ba(e);return Pa.getManager(t.scheme).removeModel(t.path)}async function Ga(e,t){return Wa(e,t,!1)}async function Ha(e,t){return Wa(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 ja{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){window&&ye().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)}}if(ye().get("IS_BROWSER")){ye().setPlatform("browser",new ja);try{Pa.registerManager(Oa.URL_SCHEME,new La)}catch(e){}try{Pa.registerManager(ka.URL_SCHEME,new Na)}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 qa=()=>n(817);let Ka;class Xa{constructor(){this.util=n(590),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return null!=ye().global.fetch?ye().global.fetch(e,t):(null==Ka&&(Ka=qa()),Ka(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)}}
+/**
+ * @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 Ya(e,t="float32",n){return t=t||"float32",ce(e),new pr(e,t,n)}ye().get("IS_NODE")&&!ye().get("IS_BROWSER")&&ye().setPlatform("node",new Xa);const Za=qr({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=Gr(e,"x","cast");if(!function(e){return"bool"===e||"complex64"===e||"float32"===e||"int32"===e||"string"===e}(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 s={x:n},r={dtype:t};return Or.runKernel(Ge,s,r)}});const Ja=qr({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:Gr(e,"x","clone","string_or_numeric")};return Or.runKernel(Ot,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 Qa(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.
+ * =============================================================================
+ */
+Dr();fr={buffer:Ya,cast:Za,clone:Ja,print:Qa};function ei(e){return new Promise((e=>setTimeout(e))).then(e)}class ti{constructor(e){if(!ye().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(ti.URL_SCHEME)&&(e=e.slice(ti.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=window.URL.createObjectURL(new Blob([e.weightData],{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 n=ia(e,[{paths:["./"+this.weightDataFileName],weights:e.weightSpecs}]),s=window.URL.createObjectURL(new Blob([JSON.stringify(n)],{type:"application/json"})),r=null==this.modelJsonAnchor?document.createElement("a"):this.modelJsonAnchor;if(r.download=this.modelJsonFileName,r.href=s,await ei((()=>r.dispatchEvent(new MouseEvent("click")))),null!=e.weightData){const e=null==this.weightDataAnchor?document.createElement("a"):this.weightDataAnchor;e.download=this.weightDataFileName,e.href=t,await ei((()=>e.dispatchEvent(new MouseEvent("click"))))}return{modelArtifactsInfo:ua(e)}}}}ti.URL_SCHEME="downloads://";class ni{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 s=JSON.parse(n.target.result),r=s.modelTopology;if(null==r)return void t(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));if(null==s.weightsManifest)return void t(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));if(0===this.weightsFiles.length)return void e({modelTopology:r});const a=la(s,(e=>this.loadWeights(e)));e(a)},n.onerror=e=>t(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),n.readAsText(this.jsonFile)}))}loadWeights(e){const t=[],n=[];for(const s of e)t.push(...s.weights),n.push(...s.paths);const s=this.checkManifestAndWeightFiles(e),r=n.map((e=>this.loadWeightsFile(e,s[e])));return Promise.all(r).then((e=>[t,ra(e)]))}loadWeightsFile(e,t){return new Promise(((n,s)=>{const r=new FileReader;r.onload=e=>{const t=e.target.result;n(t)},r.onerror=t=>s(`Failed to weights data from file of path '${e}'.`),r.readAsArrayBuffer(t)}))}checkManifestAndWeightFiles(e){const t=[],n=this.weightsFiles.map((e=>aa(e.name))),s={};for(const r of e)r.paths.forEach((e=>{const r=aa(e);if(-1!==t.indexOf(r))throw new Error(`Duplicate file basename found in weights manifest: '${r}'`);if(t.push(r),-1===n.indexOf(r))throw new Error(`Weight file with basename '${r}' is not provided.`);s[e]=this.weightsFiles[n.indexOf(r)]}));if(t.length!==this.weightsFiles.length)throw new Error(`Mismatch in the number of files in weights manifest (${t.length}) and the number of weight files provided (${this.weightsFiles.length}).`);return s}}function si(e){return new ni(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 ri(e,t,n,s){!function(e){O(null!=e&&Array.isArray(e)&&e.length>0,(()=>"promises must be a none empty array"))}(e),function(e,t){O(e>=0&&e<=1,(()=>`Progress fraction must be in range [0, 1], but got startFraction ${e}`)),O(t>=0&&t<=1,(()=>`Progress fraction must be in range [0, 1], but got endFraction ${t}`)),O(t>=e,(()=>`startFraction must be no more than endFraction, but got startFraction ${e} and endFraction ${t}`))}(n=null==n?0:n,s=null==s?1:s);let r=0;return Promise.all(e.map((a=>(a.then((a=>{const i=n+ ++r/e.length*(s-n);return t(i),a})),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.
+ * =============================================================================
+ */
+async function ai(e,t){null==t&&(t={});const n=null==t.fetchFunc?ye().platform.fetch:t.fetchFunc,s=e.map((e=>n(e,t.requestInit,{isBinary:!0}))),r=(null==t.onProgress?await Promise.all(s):await ri(s,t.onProgress,0,.5)).map((e=>e.arrayBuffer()));return null==t.onProgress?await Promise.all(r):await ri(r,t.onProgress,.5,1)}async function ii(e,t="",n,s){return oi((e=>ai(e,{requestInit:s})))(e,t,n)}function oi(e){return async(t,n="",s)=>{const r=t.map((()=>!1)),a={},i=null!=s?s.map((()=>!1)):[],o=[];if(t.forEach(((e,t)=>{let n=0;e.weights.forEach((e=>{const l="quantization"in e?e.quantization.dtype:e.dtype,u=Zr[l]*P(e.shape),c=()=>{r[t]=!0,null==a[t]&&(a[t]=[]),a[t].push({manifestEntry:e,groupOffset:n,sizeBytes:u})};null!=s?s.forEach(((t,n)=>{t===e.name&&(c(),i[n]=!0)})):c(),o.push(e.name),n+=u}))})),!i.every((e=>e))){const e=s.filter(((e,t)=>!i[t]));throw new Error(`Could not find weights in manifest with names: ${e.join(", ")}. \nManifest JSON has weights with names: ${o.join(", ")}.`)}const l=r.reduce(((e,t,n)=>(t&&e.push(n),e)),[]),u=[];l.forEach((e=>{t[e].paths.forEach((e=>{const t=n+(n.endsWith("/")?"":"/")+e;u.push(t)}))}));const c=await e(u),h={};let p=0;return l.forEach((e=>{const n=t[e].paths.length;let s=0;for(let e=0;e{const t=ea(r.slice(e.groupOffset,e.groupOffset+e.sizeBytes),[e.manifestEntry]);for(const e in t)h[e]=t[e]})),p+=n})),h}}pa.registerSaveRouter((e=>ye().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(ti.URL_SCHEME)?function(e="model"){return new ti(e)}(e.slice(ti.URL_SCHEME.length)):null));class li{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?(O("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=ye().platform.fetch,O(null!=e&&e.length>0,(()=>"URL path for http must not be null, undefined or empty.")),Array.isArray(e)&&O(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=ia(e,[{paths:["./model.weights.bin"],weights:e.weightSpecs}]);t.body.append("model.json",new Blob([JSON.stringify(n)],{type:"application/json"}),"model.json"),null!=e.weightData&&t.body.append("model.weights.bin",new Blob([e.weightData],{type:"application/octet-stream"}),"model.weights.bin");const s=await this.fetch(this.path,t);if(s.ok)return{modelArtifactsInfo:ua(e),responses:[s]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${s.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,s=t.weightsManifest;if(null==n&&null==s)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);return la(t,(e=>this.loadWeights(e)))}async loadWeights(e){const t=Array.isArray(this.path)?this.path[1]:this.path,[n,s]=function(e){const t=e.lastIndexOf("/"),n=e.lastIndexOf("?"),s=e.substring(0,t),r=n>t?e.substring(n):"";return[s+"/",r]}(t),r=this.weightPathPrefix||n,a=ca(e),i=[],o=[];for(const t of e)for(const e of t.paths)null!=this.weightUrlConverter?o.push(this.weightUrlConverter(e)):i.push(r+e+s);this.weightUrlConverter&&i.push(...await Promise.all(o));return[a,ra(await ai(i,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress}))]}}function ui(e){return null!=e.match(li.URL_SCHEME_REGEX)}li.URL_SCHEME_REGEX=/^https?:\/\//;const ci=(e,t)=>{if("undefined"==typeof fetch&&(null==t||null==t.fetchFunc))return null;{let n=!0;if(n=Array.isArray(e)?e.every((e=>ui(e))):ui(e),n)return hi(e,t)}return null};function hi(e,t){return new li(e,t)}function pi(e,t){return hi(e,t)}pa.registerSaveRouter(ci),pa.registerLoadRouter(ci);
+/**
+ * @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 di{constructor(e){this.modelArtifacts=e}load(){return this.modelArtifacts}}class fi{constructor(e){this.saveHandler=e}save(e){return this.saveHandler(e)}}class mi{constructor(e){e.load&&(this.load=()=>Promise.resolve(e.load())),e.save&&(this.save=t=>Promise.resolve(e.save(t)))}}function gi(e,t,n,s){return new mi(yi(...arguments))}function yi(e,t,n,s){if(1===arguments.length){return null!=e.modelTopology||null!=e.weightSpecs?new di(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 di({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 di({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:s})}function bi(e){return new fi(e)}function xi(e){return new fi(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 wi(e,t){const n=e.length,s=[];for(let r=0;r1&&1===i&&s.unshift(a)}return s}function vi(e,t){const n=[];for(let s=0;s1)&&n.unshift(a)}return n}function ki(e,t){const n=[],s=Math.max(e.length,t.length);for(let r=0;r4)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,s=!1,r=!1,a=!1,i=!1,o=!1;if(e.data instanceof Uint8Array)n=!0;else if("undefined"!=typeof ImageData&&e instanceof ImageData)s=!0;else if("undefined"!=typeof HTMLVideoElement&&e instanceof HTMLVideoElement)r=!0;else if("undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement)a=!0;else if(null!=e.getContext)i=!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 ${e.constructor.name}`);o=!0}if(null!=_s(Ns,Or.backendName)){const n={pixels:e},s={numChannels:t};return Or.runKernel(Ns,n,s)}const[l,u]=r?[e.videoWidth,e.videoHeight]:[e.width,e.height];let c,h;if(i)c=e.getContext("2d").getImageData(0,0,l,u).data;else if(s||n)c=e.data;else if(a||r||o){if(null==Ni)if("undefined"==typeof document){if("undefined"==typeof OffscreenCanvas||"undefined"==typeof OffscreenCanvasRenderingContext2D)throw new Error("Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.");Ni=new OffscreenCanvas(1,1).getContext("2d")}else Ni=document.createElement("canvas").getContext("2d",{willReadFrequently:!0});Ni.canvas.width=l,Ni.canvas.height=u,Ni.drawImage(e,0,0,l,u),c=Ni.getImageData(0,0,l,u).data}if(4===t)h=new Int32Array(c);else{const e=l*u;h=new Int32Array(e*t);for(let n=0;n`Error in slice${s}D: Length of begin ${t} must match the rank of the array (${s}).`)),O(s===n.length,(()=>`Error in slice${s}D: Length of size ${n} must match the rank of the array (${s}).`));for(let r=0;r`Error in slice${s}D: begin[${r}] + size[${r}] (${t[r]+n[r]}) would overflow input.shape[${r}] (${e.shape[r]})`))}function Ri(e){const t=[];let n=0;for(;e>0;)1&e&&t.push(n),e/=2,n++;return t}function Ai(e,t,n){const s=[];for(let r=0;r0){const l=t[0],u=n+1;c=Mi(i,l,u,s,e),h=Li(o,l,u,r,e),p=Fi(a,l,u,e)}else for(let t=0;t-1)a[r]=0;else{const i=_i(t,n,r);let o=s[i];e&1<-1)a[r]=Number.MAX_SAFE_INTEGER;else{const i=_i(t,n,r);let o=s[i];e&1<0?Number.MIN_SAFE_INTEGER:Number.MAX_SAFE_INTEGER);const l=s[r];return i<0&&(i+=l),i=F(0,i,l-1),i}function Bi(e,t,n,s,r,a){let i=t[r];const o=n[r]||1;(e&1<0?Number.MAX_SAFE_INTEGER:Number.MIN_SAFE_INTEGER);const l=s[r];return i<0&&(i+=l),i=o>0?F(0,i,l):F(-1,i,l-1),i}function Wi(e,t,n){let s=n.length;for(let e=0;e1){s=e;break}for(let r=s+1;r0||n[r]!==e[r])return!1;return!0}function Vi(e,t){let n=e.length>0?e[e.length-1]:1;for(let s=0;s{O(-1!==e,(()=>"slice() does not support negative begin indexing."))})),a=null==n?new Array(r).fill(-1):"number"==typeof n?[n,...new Array(r-1).fill(-1)]:n.lengtht>=0?t:(O(-1===t,(()=>`Negative size values should be exactly -1 but got ${t} for the slice() size at index ${n}.`)),e.shape[n]-s[n]))),[s,a]}function Gi(e,t,n,s,r,a,i,o,l){let u;if(null==s?(u=new Array(t.length),u.fill(1)):u=s,null!=i&&i&i-1)throw new Error("Multiple ellipses in slice is not allowed.");let c=!1;const h={dims:u.length,numAddAxisAfterEllipsis:0,begin:t.slice(),end:n.slice(),strides:u.slice(),beginMask:r,endMask:a,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};for(let e=0;e0?0:-1,p.strides[t]>0?s:s-1];if(n&&p.strides[t]<=0)throw Error("only stride 1 allowed on non-range indexing.");m=m&&1===p.strides[t];const i=!!(p.beginMask&1<=s)throw Error(`slice index ${p.begin[t]} of dimension ${t} out of bounds.`)}else p.begin[t]=Hi(p.begin[t],0,p.strides[t],s,r,a),p.end[t]=Hi(p.end[t],1,p.strides[t],s,r,a);const e=1===p.strides[t]&&0===p.begin[t]&&p.end[t]===s;d=d&&e,f=f&&(0===t&&1===p.strides[t]||e)}else d=d&&1===p.strides[t]&&i,f=f&&(0===t&&1===p.strides[t]||i);let o,l=!1;if(p.beginValid&&p.endValid?(o=p.end[t]-p.begin[t],l=!0):n?(o=1,l=!0):i&&s>=0&&(o=p.strides[t]<0?-s:s,l=!0),l){let e;e=0===o||o<0!=p.strides[t]<0?0:Math.trunc(o/p.strides[t])+(o%p.strides[t]!=0?1:0),g.push(e)}else g.push(-1)}for(let e=0;e=0?y.push(g[t]):t===Ci&&y.push(1)}return{finalShapeSparse:y.filter(((e,t)=>p.finalShapeGatherIndices[t]!==Ci)),finalShape:y,isIdentity:d,sliceDim0:f,isSimpleSlice:m,begin:p.begin,end:p.end,strides:p.strides}}function Hi(e,t,n,s,r,a){if(r[t])return n>0?a[t]:a[t+1&1];{const t=e<0?s+e:e;return ta[1]?a[1]: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 ji{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}}class qi{constructor(){this.classNameMap={}}static getMap(){return null==qi.instance&&(qi.instance=new qi),qi.instance}static register(e){qi.getMap().classNameMap[e.className]=[e,e.fromConfig]}}function Ki(e){O(null!=e.className,(()=>"Class being registered does not have the static className property defined.")),O("string"==typeof e.className,(()=>"className is required to be a string, but got type "+typeof e.className)),O(e.className.length>0,(()=>"Class being registered has an empty-string as its className, which is disallowed.")),qi.register(e)}function Xi(){return Or}function Yi(){return Or.memory()}function Zi(e,t){return Or.tidy(e,t)}function Ji(e){Er(e).forEach((e=>e.dispose()))}function Qi(e){return Or.keep(e)}function eo(e,t,n=1){return Or.registerBackend(e,t,n)}function to(e){return Or.customGrad(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 no(e,t){if((Z(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&&Z(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return Xr(e,[],[],t)}mr=function(e){ye().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")};
+/**
+ * @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 so extends ji{minimize(e,t=!1,n){const{value:s,grads:r}=this.computeGradients(e,n);if(null!=n){const e=n.map((e=>({name:e.name,tensor:r[e.name]})));this.applyGradients(e)}else this.applyGradients(r);return Ji(r),t?s:(s.dispose(),null)}get iterations(){return null==this.iterations_&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return function(e,t){O(ne(e),(()=>"The f passed in variableGrads(f) must be a function")),O(null==t||Array.isArray(t)&&t.every((e=>e instanceof br)),(()=>"The varList passed in variableGrads(f, varList) must be an array of variables"));const n=null!=t;if(!n){t=[];for(const e in Or.registeredVariables)t.push(Or.registeredVariables[e])}const s=n?t.filter((e=>!e.trainable)):null,r=t.length;t=t.filter((e=>e.trainable)),O(t.length>0,(()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${r} variables is trainable.`));const{value:a,grads:i}=Or.gradients(e,t,null,!0);O(i.some((e=>null!=e)),(()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize().")),O(0===a.rank,(()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${a.rank} tensor`));const o={};return t.forEach(((e,t)=>{null!=i[t]&&(o[e.name]=i[t])})),null!=s&&s.forEach((e=>o[e.name]=null)),{value:a,grads:o}}(e,t)}dispose(){null!=this.iterations_&&Ji(this.iterations_)}async saveIterations(){return null==this.iterations_&&(this.iterations_=0),{name:"iter",tensor:no(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(so,Symbol.hasInstance,{value:e=>null!=e.minimize&&null!=e.computeGradients&&null!=e.applyGradients});const ro=qr({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=Gr(e,"x","abs");if("complex64"===t.dtype){const e={x:t};return Or.runKernel(Ke,e)}{const e={x:t};return Or.runKernel(ke,e)}}});const ao=qr({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:Gr(e,"x","acos")};return Or.runKernel(Ie,t)}});const io=qr({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:Gr(e,"x","acosh")};return Or.runKernel(Ne,t)}});const oo=qr({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=Gr(e,"a","add"),s=Gr(t,"b","add");[n,s]=Cr(n,s);const r={a:n,b:s};return Or.runKernel(Se,r)}});const lo=qr({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){O(Array.isArray(e),(()=>"The argument passed to tf.addN() must be a list of tensors")),O(e.length>=1,(()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`));const t=e.map(((e,t)=>Gr(e,`tensors${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(!B(e.shape,n.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")}));const s=t;return Or.runKernel(Te,s)}});const uo=qr({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 s={x:Gr(e,"x","all","bool")},r={axis:t,keepDims:n};return Or.runKernel(Ce,s,r)}});const co=qr({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 s={x:Gr(e,"x","any","bool")},r={axis:t,keepDims:n};return Or.runKernel($e,s,r)}});const ho=qr({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:Gr(e,"x","argMax")},s={axis:t};return Or.runKernel(Ee,n,s)}});const po=qr({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:Gr(e,"x","argMin")},s={axis:t};return Or.runKernel(Re,n,s)}});const fo=qr({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:Gr(e,"x","asin")};return Or.runKernel(Ae,t)}});const mo=qr({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:Gr(e,"x","asinh")};return Or.runKernel(Fe,t)}});const go=qr({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:Gr(e,"x","atan")};return Or.runKernel(_e,t)}});const yo=qr({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=Gr(e,"a","atan2"),s=Gr(t,"b","atan2");[n,s]=Cr(n,s);const r={a:n,b:s};return Or.runKernel(Oe,r)}});const bo=qr({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:Gr(e,"x","atanh")};return Or.runKernel(De,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 xo(e,t,n,s,r="NHWC",a){return ko(e,[...t,e[3]],n,a,s,null,null,Ao(r))}function wo(e,t,n,s,r,a,i="channelsLast"){const[o,l]=So(t);let u;if("channelsLast"===i)u=[o,l,e[3],e[3]];else{if("channelsFirst"!==i)throw new Error(`Unknown dataFormat ${i}`);u=[o,l,e[1],e[1]]}return ko(e,u,n,s,r,a,!1,i)}function vo(e,t,n,s,r,a,i="NDHWC"){const[o,l,u]=To(t);let c,h;if("NDHWC"===i)h="channelsLast",c=[o,l,u,e[4],e[4]];else{if("NCDHW"!==i)throw new Error(`Unknown dataFormat ${i}`);h="channelsFirst",c=[o,l,u,e[1],e[1]]}return Io(e,c,n,s,r,!1,h,a)}function ko(e,t,n,s,r,a,i=!1,o="channelsLast"){let[l,u,c,h]=[-1,-1,-1,-1];if("channelsLast"===o)[l,u,c,h]=e;else{if("channelsFirst"!==o)throw new Error(`Unknown dataFormat ${o}`);[l,h,u,c]=e}const[p,d,,f]=t,[m,g]=So(n),[y,b]=So(s),x=Co(p,y),w=Co(d,b),{padInfo:v,outHeight:k,outWidth:I}=function(e,t,n,s,r,a,i,o,l){let u,c,h;if("number"==typeof e){u={top:e,bottom:e,left:e,right:e,type:0===e?"VALID":"NUMBER"};const r=function(e,t,n,s,r){null==s&&(s=No(e,t,n));const a=e[0],i=e[1],o=$o((a-t+2*s)/n+1,r),l=$o((i-t+2*s)/n+1,r);return[o,l]}([t,n],a,s,e,o);c=r[0],h=r[1]}else if("same"===e){c=Math.ceil(t/s),h=Math.ceil(n/r);const e=Math.max(0,(c-1)*s+a-t),o=Math.max(0,(h-1)*r+i-n),l=Math.floor(e/2),p=e-l,d=Math.floor(o/2);u={top:l,bottom:p,left:d,right:o-d,type:"SAME"}}else if("valid"===e)u={top:0,bottom:0,left:0,right:0,type:"VALID"},c=Math.ceil((t-a+1)/s),h=Math.ceil((n-i+1)/r);else{if("object"!=typeof e)throw Error(`Unknown padding parameter: ${e}`);{const p="channelsLast"===l?e[1][0]:e[2][0],d="channelsLast"===l?e[1][1]:e[2][1],f="channelsLast"===l?e[2][0]:e[3][0],m="channelsLast"===l?e[2][1]:e[3][1];u={top:p,bottom:d,left:f,right:m,type:0===p&&0===d&&0===f&&0===m?"VALID":"EXPLICIT"},c=$o((t-a+p+d)/s+1,o),h=$o((n-i+f+m)/r+1,o)}}return{padInfo:u,outHeight:c,outWidth:h}}(r,u,c,m,g,x,w,a,o),N=i?f*h:f;let S;return"channelsFirst"===o?S=[l,N,k,I]:"channelsLast"===o&&(S=[l,k,I,N]),{batchSize:l,dataFormat:o,inHeight:u,inWidth:c,inChannels:h,outHeight:k,outWidth:I,outChannels:N,padInfo:v,strideHeight:m,strideWidth:g,filterHeight:p,filterWidth:d,effectiveFilterHeight:x,effectiveFilterWidth:w,dilationHeight:y,dilationWidth:b,inShape:e,outShape:S,filterShape:t}}function Io(e,t,n,s,r,a=!1,i="channelsLast",o){let[l,u,c,h,p]=[-1,-1,-1,-1,-1];if("channelsLast"===i)[l,u,c,h,p]=e;else{if("channelsFirst"!==i)throw new Error(`Unknown dataFormat ${i}`);[l,p,u,c,h]=e}const[d,f,m,,g]=t,[y,b,x]=To(n),[w,v,k]=To(s),I=Co(d,w),N=Co(f,v),S=Co(m,k),{padInfo:T,outDepth:C,outHeight:$,outWidth:E}=function(e,t,n,s,r,a,i,o,l,u,c){let h,p,d,f;if("number"==typeof e){h={top:e,bottom:e,left:e,right:e,front:e,back:e,type:0===e?"VALID":"NUMBER"};const a=function(e,t,n,s,r,a){null==r&&(r=No(e,t,s));const i=e[0],o=e[1],l=e[2],u=$o((i-t+2*r)/s+1,a),c=$o((o-t+2*r)/s+1,a),h=$o((l-t+2*r)/s+1,a);return[u,c,h,n]}([t,n,s,1],o,1,r,e,c);p=a[0],d=a[1],f=a[2]}else if("same"===e){p=Math.ceil(t/r),d=Math.ceil(n/a),f=Math.ceil(s/i);const e=(p-1)*r+o-t,c=(d-1)*a+l-n,m=(f-1)*i+u-s,g=Math.floor(e/2),y=e-g,b=Math.floor(c/2),x=c-b,w=Math.floor(m/2);h={top:b,bottom:x,left:w,right:m-w,front:g,back:y,type:"SAME"}}else{if("valid"!==e)throw Error(`Unknown padding parameter: ${e}`);h={top:0,bottom:0,left:0,right:0,front:0,back:0,type:"VALID"},p=Math.ceil((t-o+1)/r),d=Math.ceil((n-l+1)/a),f=Math.ceil((s-u+1)/i)}return{padInfo:h,outDepth:p,outHeight:d,outWidth:f}}(r,u,c,h,y,b,x,I,N,S,o),R=a?g*p:g;let A;return"channelsFirst"===i?A=[l,R,C,$,E]:"channelsLast"===i&&(A=[l,C,$,E,R]),{batchSize:l,dataFormat:i,inDepth:u,inHeight:c,inWidth:h,inChannels:p,outDepth:C,outHeight:$,outWidth:E,outChannels:R,padInfo:T,strideDepth:y,strideHeight:b,strideWidth:x,filterDepth:d,filterHeight:f,filterWidth:m,effectiveFilterDepth:I,effectiveFilterHeight:N,effectiveFilterWidth:S,dilationDepth:w,dilationHeight:v,dilationWidth:k,inShape:e,outShape:A,filterShape:t}}function No(e,t,n,s=1){const r=Co(t,s);return Math.floor((e[0]*(n-1)-n+r)/2)}function So(e){return"number"==typeof e?[e,e,e]:2===e.length?[e[0],e[1],1]:e}function To(e){return"number"==typeof e?[e,e,e]:e}function Co(e,t){return t<=1?e:e+(e-1)*(t-1)}function $o(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 Eo(e){const[t,n,s]=So(e);return 1===t&&1===n&&1===s}function Ro(e,t){return Eo(e)||Eo(t)}function Ao(e){if("NHWC"===e)return"channelsLast";if("NCHW"===e)return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function Fo(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)O(W(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=>{O(W(t),(()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`))}))}))}}}const _o=qr({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:Gr(e,"x","reshape","string_or_numeric")},s={shape:t};return Or.runKernel(An,n,s)}});const Do=qr({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,s,r){const a=Gr(e,"x","avgPool","float32");O(Ro(n,1),(()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${n} and dilations '1'`));let i=a,o=!1;3===a.rank&&(o=!0,i=_o(a,[1,a.shape[0],a.shape[1],a.shape[2]])),O(4===i.rank,(()=>`Error in avgPool: x must be rank 4 but got rank ${i.rank}.`)),Fo("avgPool",s,r);const l={x:i},u={filterSize:t,strides:n,pad:s,dimRoundingMode:r};let c=Or.runKernel(Me,l,u);return c=Za(c,a.dtype),o?_o(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});const Oo=qr({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,s,r,a="NDHWC"){const i=Gr(e,"x","avgPool3d","float32");let o=i,l=!1;4===i.rank&&(l=!0,o=_o(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),O(5===o.rank,(()=>`Error in avgPool3d: x must be rank 5 but got rank ${o.rank}.`)),O("NDHWC"===a,(()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`)),Fo("avgPool3d",s,r);const u={x:o},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a};let h=Or.runKernel(ze,u,c);return h=Za(h,o.dtype),l?_o(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}});const Mo=qr({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){O(e.length>=1,(()=>"Pass at least one tensor to concat"));const n=Hr(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 Ja(n[0]);const s=n,r={axis:t};return Or.runKernel(Xe,s,r)}});const Lo=qr({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,s=!1){let r=Gr(e,"a","matMul"),a=Gr(t,"b","matMul");[r,a]=Cr(r,a);const i={a:r,b:a},o={transposeA:n,transposeB:s};return Or.runKernel(Be,i,o)}});const zo=qr({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=Gr(e,"a","mul"),s=Gr(t,"b","mul");[n,s]=Cr(n,s);const r={a:n,b:s};return Or.runKernel(pn,r)}});const Po=qr({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:Gr(e,"x","sigmoid","float32")};return Or.runKernel(Kn,t)}});const Bo=qr({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 s=Gr(e,"x","slice","string_or_numeric");if(0===s.rank)throw new Error("Slicing scalar is not possible");const r={x:s},a={begin:t,size:n};return Or.runKernel(Gn,r,a)}});const Wo=qr({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:Gr(e,"x","tanh","float32")};return Or.runKernel(fs,t)}});const Vo=qr({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,s,r,a){const i=Gr(e,"forgetBias","basicLSTMCell"),o=Gr(t,"lstmKernel","basicLSTMCell"),l=Gr(n,"lstmBias","basicLSTMCell"),u=Gr(s,"data","basicLSTMCell"),c=Gr(r,"c","basicLSTMCell"),h=Gr(a,"h","basicLSTMCell"),p=Mo([u,h],1),d=Lo(p,o),f=oo(d,l),m=f.shape[0],g=f.shape[1]/4,y=[m,g],b=Bo(f,[0,0],y),x=Bo(f,[0,g],y),w=Bo(f,[0,2*g],y),v=Bo(f,[0,3*g],y),k=oo(zo(Po(b),Wo(x)),zo(c,Po(oo(i,w))));return[k,zo(Wo(k),Po(v))]}});const Uo=qr({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 s=Gr(e,"x","batchToSpaceND"),r=t.reduce(((e,t)=>e*t));O(s.rank>=1+t.length,(()=>`input rank is ${s.rank} but should be > than blockShape.length ${t.length}`)),O(n.length===t.length,(()=>`crops.length is ${n.length} but should be equal to blockShape.length ${t.length}`)),O(s.shape[0]%r==0,(()=>`input tensor batch is ${s.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${r}`));const a={x:s},i={blockShape:t,crops:n};return Or.runKernel(We,a,i)}});const Go=qr({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,s,r,a){null==a&&(a=.001);const i=Gr(e,"x","batchNorm"),o=Gr(t,"mean","batchNorm"),l=Gr(n,"variance","batchNorm");let u,c;null!=r&&(u=Gr(r,"scale","batchNorm")),null!=s&&(c=Gr(s,"offset","batchNorm")),O(o.rank===l.rank,(()=>"Batch normalization gradient requires mean and variance to have equal ranks.")),O(null==c||o.rank===c.rank,(()=>"Batch normalization gradient requires mean and offset to have equal ranks.")),O(null==u||o.rank===u.rank,(()=>"Batch normalization gradient requires mean and scale to have equal ranks."));const h=function(e){let t;return t=0===e.rank||1===e.rank?_o(e,[1,1,1,e.size]):2===e.rank?_o(e,[1,1,e.shape[0],e.shape[1]]):3===e.rank?_o(e,[1,e.shape[0],e.shape[1],e.shape[2]]):e,t}(i),p={x:h,scale:u,offset:c,mean:o,variance:l},d={varianceEpsilon:a},f=Or.runKernel(Rt,p,d);return _o(f,i.shape)}});const Ho=qr({batchNorm2d_:function(e,t,n,s,r,a){const i=Gr(e,"x","batchNorm"),o=Gr(t,"mean","batchNorm"),l=Gr(n,"variance","batchNorm");let u,c;return null!=r&&(u=Gr(r,"scale","batchNorm")),null!=s&&(c=Gr(s,"offset","batchNorm")),O(2===i.rank,(()=>`Error in batchNorm2D: x must be rank 2 but got rank ${i.rank}.`)),O(2===o.rank||1===o.rank,(()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${o.rank}.`)),O(2===l.rank||1===l.rank,(()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`)),null!=u&&O(2===u.rank||1===u.rank,(()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`)),null!=c&&O(2===c.rank||1===c.rank,(()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`)),Go(i,o,l,c,u,a)}});const jo=qr({batchNorm3d_:function(e,t,n,s,r,a){const i=Gr(e,"x","batchNorm"),o=Gr(t,"mean","batchNorm"),l=Gr(n,"variance","batchNorm");let u,c;return null!=r&&(u=Gr(r,"scale","batchNorm")),null!=s&&(c=Gr(s,"offset","batchNorm")),O(3===i.rank,(()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`)),O(3===o.rank||1===o.rank,(()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${o.rank}.`)),O(3===l.rank||1===l.rank,(()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`)),null!=u&&O(3===u.rank||1===u.rank,(()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`)),null!=c&&O(3===c.rank||1===c.rank,(()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`)),Go(i,o,l,c,u,a)}});const qo=qr({batchNorm4d_:function(e,t,n,s,r,a){const i=Gr(e,"x","batchNorm"),o=Gr(t,"mean","batchNorm"),l=Gr(n,"variance","batchNorm");let u,c;return null!=r&&(u=Gr(r,"scale","batchNorm")),null!=s&&(c=Gr(s,"offset","batchNorm")),O(4===i.rank,(()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`)),O(4===o.rank||1===o.rank,(()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`)),O(4===l.rank||1===l.rank,(()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`)),null!=u&&O(4===u.rank||1===u.rank,(()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`)),null!=c&&O(4===c.rank||1===c.rank,(()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`)),Go(i,o,l,c,u,a)}});const Ko=qr({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 s=Gr(e,"x","bincount"),r=Gr(t,"weights","bincount");O("int32"===s.dtype,(()=>`Error in bincount: input dtype must be int32, but got ${s.dtype}`)),O(n>=0,(()=>`size must be non-negative, but got ${n}.`)),O(r.size===s.size||0===r.size,(()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${s.shape}, weights shape: ${r.shape}.`));const a={x:s,weights:r},i={size:n};return Or.runKernel(Ve,a,i)}});const Xo=qr({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=Gr(e,"s0","broadcastArgs","int32"),s=Gr(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!==s.rank)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${s.rank}`);const r={s0:n,s1:s};return Or.runKernel(Ue,r)}});const Yo=qr({broadcastTo_:
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t){let n=Gr(e,"broadcastTo","x");const s=n.shape;if(t.some((e=>!(e>0)||e%1!=0)))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.lengthn.rank){const e=n.shape.slice();for(;e.length=0;e--)if(r[e]===t[e])a[e]=1;else if(1!==n.shape[e])throw new Error(`broadcastTo(): [${s}] cannot be broadcast to [${t}].`);if(0===a.map(((e,t)=>e>1?t:-1)).filter((e=>e>=0)).length)return Ja(n);const i={x:n},o={reps:a};return Or.runKernel(ms,i,o)}});const Zo=qr({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:Gr(e,"x","ceil","float32")};return Or.runKernel(He,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 Jo(e,t,n){const s={shape:e,value:t,dtype:n};return Or.runKernel(Tt,{},s)}const Qo=qr({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 s=Gr(e,"x","clipByValue");if(O(t<=n,(()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`)),t===n)return Jo(s.shape,t,s.dtype);const r={x:s},a={clipValueMin:t,clipValueMax:n};return Or.runKernel(je,r,a)}});const el=qr({concat1d_:function(e){return Mo(e,0)}});const tl=qr({concat2d_:function(e,t){return Mo(e,t)}});const nl=qr({concat3d_:function(e,t){return Mo(e,t)}});const sl=qr({concat4d_:function(e,t){return Mo(e,t)}});const rl=qr({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,s,r="NHWC",a=[1,1],i){const o=Gr(e,"x","conv2d","float32"),l=Gr(t,"filter","conv2d","float32");let u=o,c=!1;3===o.rank&&(c=!0,u=_o(o,[1,o.shape[0],o.shape[1],o.shape[2]])),O(4===u.rank,(()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`)),O(4===l.rank,(()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`)),Fo("conv2d",s,i);const h="NHWC"===r?u.shape[3]:u.shape[1];O(h===l.shape[2],(()=>`Error in conv2d: depth of input (${h}) must match input depth for filter ${l.shape[2]}.`)),O(Ro(n,a),(()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`));const p={x:u,filter:l},d={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:i},f=Or.runKernel(Ye,p,d);return c?_o(f,[f.shape[1],f.shape[2],f.shape[3]]):f}});const al=qr({conv1d_:function(e,t,n,s,r="NWC",a=1,i){const o=Gr(e,"x","conv1d"),l=Gr(t,"filter","conv1d");let u=o,c=!1;2===o.rank&&(c=!0,u=_o(o,[1,o.shape[0],o.shape[1]])),O(3===u.rank,(()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`)),O(3===l.rank,(()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`)),Fo("conv1d",s,i),O(u.shape[2]===l.shape[1],(()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`)),O(Ro(n,a),(()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${a}'`)),O("NWC"===r,(()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`));const h=_o(l,[1,l.shape[0],l.shape[1],l.shape[2]]),p=_o(u,[u.shape[0],1,u.shape[1],u.shape[2]]),d=rl(p,h,[1,n],s,"NHWC",[1,a],i);return _o(d,c?[d.shape[2],d.shape[3]]:[d.shape[0],d.shape[2],d.shape[3]])}});const il=qr({conv2DBackpropInput_:
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t,n,s,r,a="NHWC",i){O(e.length===t.rank,(()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`));let o=e,l=t,u=!1;3===t.rank&&(u=!0,l=_o(t,[1,t.shape[0],t.shape[1],t.shape[2]]),o=[1,e[0],e[1],e[2]]),O(4===o.length,(()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${o.length}.`)),O(4===l.rank,(()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`)),O(4===n.rank,(()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`));const c="NHWC"===a?o[3]:o[1],h="NHWC"===a?l.shape[3]:l.shape[1];O(c===n.shape[2],(()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`)),O(h===n.shape[3],(()=>`Error in conv2dDerInput: depth of output (${h}) must match output depth for filter ${n.shape[3]}.`)),Fo("conv2dDerInput",r,i);const p={dy:l,filter:n},d={strides:s,pad:r,dataFormat:a,dimRoundingMode:i,inputShape:o},f=Or.runKernel(Je,p,d);return u?_o(f,[f.shape[1],f.shape[2],f.shape[3]]):f}});const ol=qr({conv2dTranspose_:function(e,t,n,s,r,a){const i=Gr(e,"x","conv2dTranspose"),o=Gr(t,"filter","conv2dTranspose");return il(n,i,o,s,r,"NHWC",a)}});const ll=qr({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,s,r="NDHWC",a=[1,1,1]){const i=Gr(e,"x","conv3d"),o=Gr(t,"filter","conv3d");let l=i,u=!1;4===i.rank&&(u=!0,l=_o(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),O(5===l.rank,(()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`)),O(5===o.rank,(()=>`Error in conv3d: filter must be rank 5, but got rank ${o.rank}.`)),O(l.shape[4]===o.shape[3],(()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${o.shape[3]}.`)),O(Ro(n,a),(()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`)),O("NDHWC"===r,(()=>`Error in conv3d: got dataFormat of ${r} but only NDHWC is currently supported.`));const c={x:l,filter:o},h={strides:n,pad:s,dataFormat:r,dilations:a},p=Or.runKernel(Qe,c,h);return u?_o(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}});const ul=qr({conv3DBackpropInput_:
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t,n,s,r){O(e.length===t.rank,(()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`));let a=e,i=t,o=!1;4===t.rank&&(o=!0,i=_o(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),a=[1,e[0],e[1],e[2],e[3]]);const l=a[4],u=i.shape[4];O(5===a.length,(()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${a.length}.`)),O(5===i.rank,(()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${i.rank}`)),O(5===n.rank,(()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`)),O(l===n.shape[3],(()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`)),O(u===n.shape[4],(()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`));const c={dy:i,filter:n},h={pad:r,strides:s,inputShape:a},p=Or.runKernel(tt,c,h);return o?_o(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}});const cl=qr({conv3dTranspose_:function(e,t,n,s,r){const a=Gr(e,"x","conv3dTranspose"),i=Gr(t,"filter","conv3dTranspose");return ul(n,a,i,s,r)}});const hl=qr({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:Gr(e,"x","cos","float32")};return Or.runKernel(nt,t)}});const pl=qr({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:Gr(e,"x","cosh","float32")};return Or.runKernel(st,t)}});const dl=qr({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,s=!1){const r={x:Gr(e,"x","cumprod")},a={axis:t,exclusive:n,reverse:s};return Or.runKernel(rt,r,a)}});const fl=qr({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,s=!1){const r={x:Gr(e,"x","cumsum")},a={axis:t,exclusive:n,reverse:s};return Or.runKernel(at,r,a)}});const ml=qr({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,s=!1){const r=Gr(e,"x","denseBincount"),a=Gr(t,"weights","denseBincount");O("int32"===r.dtype,(()=>`Error in denseBincount: input dtype must be int32, but got ${r.dtype}`)),O(r.rank<=2,(()=>`Error in denseBincount: input must be at most rank 2, but got rank ${r.rank}.`)),O(n>=0,(()=>`size must be non-negative, but got ${n}.`)),O(a.size===r.size||0===a.size,(()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${r.shape}, weights shape: ${a.shape}.`));const i={x:r,weights:a},o={size:n,binaryOutput:s};return Or.runKernel(ot,i,o)}});const gl=qr({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 s=Gr(e,"x","depthToSpace","float32"),r="NHWC"===n?s.shape[1]:s.shape[2],a="NHWC"===n?s.shape[2]:s.shape[3],i="NHWC"===n?s.shape[3]:s.shape[1];O(t>1,(()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`)),O(r*t>=0,(()=>`Negative dimension size caused by overflow when multiplying\n ${r} and ${t} for depthToSpace with input shape\n ${s.shape}`)),O(a*t>=0,(()=>`Negative dimension size caused by overflow when multiplying\n ${a} and ${t} for depthToSpace with input shape\n ${s.shape}`)),O(i%(t*t)==0,(()=>`Dimension size must be evenly divisible by ${t*t} but is ${i} for depthToSpace with input shape ${s.shape}`));const o={x:s},l={blockSize:t,dataFormat:n};return Or.runKernel(lt,o,l)}});const yl=qr({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,s,r="NHWC",a=[1,1],i){const o=Gr(e,"x","depthwiseConv2d","float32"),l=Gr(t,"filter","depthwiseConv2d","float32");let u=o,c=!1;3===o.rank&&(c=!0,u=_o(o,[1,o.shape[0],o.shape[1],o.shape[2]])),O(4===u.rank,(()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${u.rank}.`)),O(4===l.rank,(()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`));const h="NHWC"===r?u.shape[3]:u.shape[1];O(h===l.shape[2],(()=>`Error in depthwiseConv2d: number of input channels (${h}) must match the inChannels dimension in filter ${l.shape[2]}.`)),Fo("depthwiseConv2d",s,i);const p={x:u,filter:l},d={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:i},f=Or.runKernel(ut,p,d);return c?_o(f,[f.shape[1],f.shape[2],f.shape[3]]):f}});const bl=qr({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:Gr(e,"x","diag")};return Or.runKernel(pt,t)}});const xl=qr({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,s,r=[1,1],a="NHWC"){const i=Gr(e,"x","dilation2d"),o=Gr(t,"filter","dilation2d");O(3===i.rank||4===i.rank,(()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${i.rank}.`)),O(3===o.rank,(()=>`Error in dilation2d: filter must be rank 3, but got rank ${o.rank}.`)),O("NHWC"===a,(()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${a}`));let l=i,u=!1;3===i.rank&&(l=_o(i,[1,i.shape[0],i.shape[1],i.shape[2]]),u=!0);const c={x:l,filter:o},h={strides:n,pad:s,dilations:r},p=Or.runKernel(dt,c,h);return u?_o(p,[p.shape[1],p.shape[2],p.shape[3]]):p}});const wl=qr({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=Gr(e,"a","floorDiv"),s=Gr(t,"b","floorDiv");[n,s]=Cr(n,s);const r={a:n,b:s};return Or.runKernel(Et,r)}});const vl=qr({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=Gr(e,"a","div"),s=Gr(t,"b","div");if([n,s]=Cr(n,s),"int32"===n.dtype&&"int32"===s.dtype)return wl(n,s);const r={a:n,b:s};return Or.runKernel(gt,r,{})}});const kl=qr({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=Gr(e,"a","equal","string_or_numeric"),s=Gr(t,"b","equal","string_or_numeric");[n,s]=Cr(n,s),ki(n.shape,s.shape);const r={a:n,b:s};return Or.runKernel(vt,r)}});const Il=qr({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 s=Gr(t,"a","where"),r=Gr(n,"b","where"),a=Gr(e,"condition","where","bool"),i=ki(ki(a.shape,s.shape),r.shape),o={condition:Yo(a,i),t:Yo(s,i),e:Yo(r,i)};return Or.runKernel(Vn,o)}});const Nl=qr({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:Gr(e,"x","zerosLike")};return Or.runKernel(ks,t)}});const Sl=qr({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=Gr(e,"a","div"),s=Gr(t,"b","div");[n,s]=Cr(n,s);const r=vl(n,s),a=Nl(r),i=kl(s,a);return Il(i,a,r)}});const Tl=qr({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=Gr(e,"t1","dot"),s=Gr(t,"t2","dot");O(!(1!==n.rank&&2!==n.rank||1!==s.rank&&2!==s.rank),(()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${n.rank} and ${s.rank}.`));const r=1===n.rank?n.size:n.shape[1],a=1===s.rank?s.size:s.shape[0];if(O(r===a,(()=>`Error in dot: inner dimensions of inputs must match, but got ${r} and ${a}.`)),1===n.rank&&1===s.rank){const e=_o(n,[1,-1]),t=_o(s,[-1,1]),r=Lo(e,t);return _o(r,[])}if(1===n.rank&&2===s.rank){const e=_o(n,[1,-1]),t=_o(s,[s.shape[0],s.shape[1]]),r=Lo(e,t);return _o(r,[r.size])}if(2===n.rank&&1===s.rank){const e=_o(s,[-1,1]),t=Lo(n,e);return _o(t,[t.size])}{const e=_o(s,[s.shape[0],s.shape[1]]);return Lo(n,e)}}});const Cl=qr({einsum_:
+/**
+ * @license
+ * Copyright 2021 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,...t){const n=t.map(((e,t)=>Gr(e,`tensors${t}`,"einsum"))),s={equation:e};return Or.runKernel(yt,n,s)}});const $l=qr({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:Gr(e,"x","elu","float32")};return Or.runKernel(bt,t)}});const El=qr({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=Gr(e,"x","erf");O("int32"===t.dtype||"float32"===t.dtype,(()=>"Input dtype must be `int32` or `float32`.")),"int32"===t.dtype&&(t=Za(t,"float32"));const n={x:t};return Or.runKernel(wt,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 Rl(e,t){for(let n=0;ne[t]))]}function _l(e,t){return Al(e,t.map((e=>1)),t)}function Dl(e,t,n){O(Rl(t,n),(()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${n} input.`))}function Ol(e,t){if(Rl(e,t))return null;const n=[];for(let s=0;sn.push(e))),n}function Ml(e){return e.map(((e,t)=>[t,e])).sort(((e,t)=>e[1]-t[1])).map((e=>e[0]))}function Ll(e,t){const n=[];for(let s=t-e;s"Axis must be <= rank of the tensor"));const s={input:n},r={dim:t};return Or.runKernel(It,s,r)}});const Xl=qr({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:Gr(e,"x","expm1")};return Or.runKernel(Nt,t)}});const Yl=qr({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=Gr(e,"x","tile","string_or_numeric");O(n.rank===t.length,(()=>`Error in transpose: rank of input ${n.rank} must match length of reps ${t}.`));const s={x:n},r={reps:t};return Or.runKernel(ms,s,r)}});const Zl=qr({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,s="float32"){null==t&&(t=e);const r=Ya([e,t],s),a=e<=t?e:t;for(let e=0;e`Error in localResponseNormalization: x must be rank 3 or 4 but got\n rank ${a.rank}.`)),O(W(t),(()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`));let i=a,o=!1;3===a.rank&&(o=!0,i=_o(a,[1,a.shape[0],a.shape[1],a.shape[2]]));const l={x:i},u={depthRadius:t,bias:n,alpha:s,beta:r},c=Or.runKernel(Yt,l,u);return o?_o(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});const hu=qr({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:Gr(e,"x","log","float32")};return Or.runKernel(Ht,t)}});const pu=qr({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:Gr(e,"x","log1p")};return Or.runKernel(jt,t)}});const du=qr({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:Gr(e,"x","neg")};return Or.runKernel(dn,t)}});const fu=qr({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:Gr(e,"x","softplus")};return Or.runKernel(Xn,t)}});const mu=qr({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=Gr(e,"x","logSigmoid"),n=to((e=>({value:du(fu(du(e))),gradFunc:t=>zo(t,Po(du(e)))})));return n(t)}});const gu=qr({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=Gr(e,"a","sub"),s=Gr(t,"b","sub");[n,s]=Cr(n,s);const r={a:n,b:s};return Or.runKernel(ps,r)}});const yu=qr({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=Gr(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 s=to(((e,n)=>{const s=zl(e,t,!0),r=gu(e,s),a=gu(Za(r,"float32"),hu(Ul(ql(r),t,!0)));n([a]);return{value:a,gradFunc:(e,n)=>{const[s]=n,r=ql(s);return gu(e,zo(Ul(e,t,!0),r))}}}));return s(n)}});const bu=qr({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 s=Gr(e,"x","logSumExp"),r=j(t,s.shape),a=zl(s,r,!0),i=gu(s,a),o=ql(i),l=Ul(o,r),u=hu(l),c=oo(_o(a,u.shape),u);if(n){const e=_l(c.shape,r);return _o(c,e)}return c}});const xu=qr({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=Gr(e,"a","logicalAnd","bool"),s=Gr(t,"b","logicalAnd","bool");ki(n.shape,s.shape);const r={a:n,b:s};return Or.runKernel(qt,r)}});const wu=qr({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:Gr(e,"x","logicalNot","bool")};return Or.runKernel(Kt,t)}});const vu=qr({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=Gr(e,"a","logicalOr","bool"),s=Gr(t,"b","logicalOr","bool");ki(n.shape,s.shape);const r={a:n,b:s};return Or.runKernel(Xt,r)}});const ku=qr({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=Gr(e,"a","logicalXor","bool"),s=Gr(t,"b","logicalXor","bool");return ki(n.shape,s.shape),xu(vu(e,t),wu(xu(e,t)))}}),Iu=2147483648;const Nu=qr({searchSorted_:function(e,t,n="left"){const s=Gr(e,"sortedSequence","searchSorted"),r=Gr(t,"values","searchSorted"),a=s.shape[s.shape.length-1],i=r.shape[r.shape.length-1],o=_o(s,[-1,a]),l=_o(r,[-1,i]);if(o.rank<2)throw new Error("Sorted input argument must be at least 2-dimensional");if(o.shape[0]!==l.shape[0])throw new Error("Leading dimension of 'sortedSequence' and 'values' must match.");if(P(l.shape)>=Iu)throw new Error("values tensor size must less than 2147483648");if(o.shape[1]>=Iu)throw new Error(`trailing dim_size must less than 2147483648 for int32 output type, was ${o.shape[1]}`);const u={sortedSequence:o,values:l},c={side:n};return Or.runKernel(Wn,u,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 Su(e,t){return Nu(e,t,"left")}const Tu=qr({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,s,r){const a=Gr(e,"x","maxPool");let i=a,o=!1;3===a.rank&&(o=!0,i=_o(a,[1,a.shape[0],a.shape[1],a.shape[2]])),O(4===i.rank,(()=>`Error in maxPool: input must be rank 4 but got rank ${i.rank}.`)),O(Ro(n,1),(()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${n} and dilations '1'`)),Fo("maxPool",s,r);const l={x:i},u={filterSize:t,strides:n,pad:s,dimRoundingMode:r},c=Or.runKernel(en,l,u);return o?_o(c,[c.shape[1],c.shape[2],c.shape[3]]):c}});const Cu=qr({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,s,r,a="NDHWC"){const i=Gr(e,"x","maxPool3d");let o=i,l=!1;4===i.rank&&(l=!0,o=_o(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),O(5===o.rank,(()=>`Error in maxPool3d: x must be rank 5 but got rank ${o.rank}.`)),O("NDHWC"===a,(()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`)),Fo("maxPool3d",s,r);const u={x:o},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a},h=Or.runKernel(nn,u,c);return l?_o(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}});const $u=qr({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,s,r=!1){const a={x:Gr(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:n,pad:s,includeBatchInIndex:r},o=Or.runKernel(rn,a,i);return{result:o[0],indexes:o[1]}}});const Eu=qr({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=Gr(e,"a","maximum"),s=Gr(t,"b","maximum");[n,s]=Cr(n,s),"bool"===n.dtype&&(n=Za(n,"int32"),s=Za(s,"int32")),ki(n.shape,s.shape);const r={a:n,b:s};return Or.runKernel(Qt,r)}});const Ru=qr({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 s={x:Gr(e,"x","mean")},r={axis:t,keepDims:n};return Or.runKernel(an,s,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 Au(e,t="float32"){if("complex64"===t){const t=Au(e,"float32"),n=Au(e,"float32");return Kr(t,n)}const n=le(P(e),t);return Or.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 Fu(e,t="float32"){if("complex64"===t){const t=Fu(e,"float32"),n=Au(e,"float32");return Kr(t,n)}const n=oe(P(e),t);return Or.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 _u(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 s=Gr(e,"x","meshgrid",e instanceof gr?e.dtype:"float32");if(void 0===t)return[s];let r=Gr(t,"y","meshgrid",t instanceof gr?t.dtype:"float32");const a=P(s.shape),i=P(r.shape);return"xy"===n?(s=_o(s,[1,-1]),r=_o(r,[-1,1]),[Lo(Fu([i,1],s.dtype),s),Lo(r,Fu([1,a],r.dtype))]):(s=_o(s,[-1,1]),r=_o(r,[1,-1]),[Lo(s,Fu([1,i],s.dtype)),Lo(Fu([a,1],r.dtype),r)])}const Du=qr({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=Gr(e,"a","minimum"),s=Gr(t,"b","minimum");[n,s]=Cr(n,s),"bool"===n.dtype&&(n=Za(n,"int32"),s=Za(s,"int32")),ki(n.shape,s.shape);const r={a:n,b:s};return Or.runKernel(ln,r)}});const Ou=qr({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){O("reflect"===n||"symmetric"===n,(()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${n}.`));const s=Gr(e,"x","mirrorPad");if(0===s.rank)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");O(t.length===s.rank,(()=>`Padding doesn't match input. Must be ${s.rank}. Got ${t.length}.`));const r="reflect"===n?1:0;for(let e=0;e"Invalid number of paddings. Must be length of 2 each.")),O(t[e][0]>=0&&t[e][0]<=s.shape[e]-r&&t[e][1]>=0&&t[e][1]<=s.shape[e]-r,(()=>`Padding in dimension ${e} cannot be greater than or equal to ${s.shape[e]-r} or less than 0 for input of shape ${s.shape}`));const a={paddings:t,mode:n},i={x:s};return Or.runKernel(un,i,a)}});const Mu=qr({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=Gr(e,"a","mod"),s=Gr(t,"b","mod");[n,s]=Cr(n,s);const r={a:n,b:s};return Or.runKernel(cn,r)}});const Lu=qr({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 s=j(t,(e=Gr(e,"x","moments")).shape),r=Ru(e,s,n);let a=r.shape;n||(a=_l(r.shape,s));const i=Vl(gu(Za(e,"float32"),_o(r,a)));return{mean:r,variance:Ru(i,s,n)}}});const zu=qr({multiRNNCell_:function(e,t,n,s){const r=Gr(t,"data","multiRNNCell"),a=Hr(n,"c","multiRNNCell"),i=Hr(s,"h","multiRNNCell");let o=r;const l=[];for(let t=0;t2)throw new Error(`Rank of probabilities must be 1 or 2, but is ${i}`);n=n||Math.random();const o={logits:1===i?_o(r,[1,-1]):r},l={numSamples:t,seed:n,normalized:s},u=Or.runKernel(hn,o,l);return 1===i?_o(u,[u.size]):u}});const Bu=qr({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=Gr(e,"a","notEqual","string_or_numeric"),s=Gr(t,"b","notEqual","string_or_numeric");[n,s]=Cr(n,s),ki(n.shape,s.shape);const r={a:n,b:s};return Or.runKernel(fn,r)}});const Wu=qr({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,s=0,r="int32"){if(t<2)throw new Error(`Error in oneHot: depth must be >=2, but it is ${t}`);const a={indices:Gr(e,"indices","oneHot","int32")},i={dtype:r,depth:t,onValue:n,offValue:s};return Or.runKernel(xn,a,i)}});const Vu=qr({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:Gr(e,"x","onesLike")};return Or.runKernel(bn,t)}});const Uu=qr({outerProduct_:function(e,t){const n=Gr(e,"v1","outerProduct"),s=Gr(t,"v2","outerProduct");O(1===n.rank&&1===s.rank,(()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${n.rank} and ${s.rank}.`));const r=_o(n,[-1,1]),a=_o(s,[1,-1]);return Lo(r,a)}});const Gu=qr({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 s=Gr(e,"x","pad");if(0===s.rank)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");const r={paddings:t,constantValue:n},a={x:s};return Or.runKernel(vn,a,r)}});const Hu=qr({pad1d_:function(e,t,n=0){return O(2===t.length,(()=>"Invalid number of paddings. Must be length of 2.")),Gu(e,[t],n)}});const ju=qr({pad2d_:function(e,t,n=0){return O(2===t.length&&2===t[0].length&&2===t[1].length,(()=>"Invalid number of paddings. Must be length of 2 each.")),Gu(e,t,n)}});const qu=qr({pad3d_:function(e,t,n=0){return O(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.")),Gu(e,t,n)}});const Ku=qr({pad4d_:function(e,t,n=0){return O(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.")),Gu(e,t,n)}});const Xu=qr({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 s=Gr(e,"x","spaceToBatchND");O(s.rank>=1+t.length,(()=>`input rank ${s.rank} should be > than [blockShape] ${t.length}`)),O(n.length===t.length,(()=>`paddings.shape[0] ${n.length} must be equal to [blockShape] ${t.length}`)),O(s.shape.reduce(((e,s,r)=>r>0&&r<=t.length?e&&(s+n[r-1][0]+n[r-1][1])%t[r-1]==0:e),!0),(()=>`input spatial dimensions ${s.shape.slice(1)} with paddings ${n.toString()} must be divisible by blockShapes ${t.toString()}`));const r={x:s},a={blockShape:t,paddings:n};return Or.runKernel(Jn,r,a)}});const Yu=qr({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,s,r,a,i){null==r&&(r=[1,1]),null==a&&(a=1),0===s&&(s="valid");const o=Gr(e,"x","maxPool");let l=o,u=!1;3===o.rank&&(u=!0,l=_o(o,[1,o.shape[0],o.shape[1],o.shape[2]])),O(Ro(a,r),(()=>`Error in pool: Either strides or dilations must be 1. Got strides ${a} and dilations '${r}'`));const c=wo(l.shape,t,a,r,s),h=[c.dilationHeight,c.dilationWidth];let p;p="same"===s?function(e,t){const n=e.map(((e,n)=>e+(e-1)*(t[n]-1))),s=n.map((e=>e-1)),r=s.map((e=>Math.floor(e/2))),a=s.map(((e,t)=>e-r[t]));return s.map(((e,t)=>[r[t],a[t]]))}([c.filterHeight,c.filterWidth],h):[[0,0],[0,0]];const d=1===h[0]&&1===h[1],[f,m]=function(e,t,n){const s=n.map((e=>e[0])),r=n.map((e=>e[1])),a=e.concat(s,r),i=t.map(((e,t)=>(e-a[t]%e)%e)),o=r.map(((e,t)=>e+i[t])),l=t.map(((e,t)=>[s[t],o[t]])),u=t.map(((e,t)=>[0,i[t]]));return[l,u]}([c.inHeight,c.inWidth],h,p),g=d?s:"valid",y=d?l:Xu(l,h,f),b=("avg"===n?()=>Do(y,t,a,g,i):()=>Tu(y,t,a,g,i))(),x=d?b:Uo(b,h,m);return u?_o(x,[x.shape[1],x.shape[2],x.shape[3]]):x}});const Zu=qr({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:Gr(e,"x","prelu"),alpha:Gr(t,"alpha","prelu")};return Or.runKernel(In,n)}});const Ju=qr({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 s=Gr(e,"x","prod");"bool"===s.dtype&&(s=Za(s,"int32"));const r={x:s},a={axis:t,keepDims:n};return Or.runKernel(Nn,r,a)}});const Qu=qr({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,s){const r={paramsNestedSplits:e.map(((e,t)=>Gr(e,`tensors${t}`,"raggedGather","int32"))),paramsDenseValues:Gr(t,"paramsDenseValues","raggedGather"),indices:Gr(n,"indices","raggedGather","int32")},a={outputRaggedRank:s},i=Or.runKernel(Sn,r,a);return{outputNestedSplits:i.slice(0,i.length-1),outputDenseValues:i[i.length-1]}}});const ec=qr({raggedTensorToTensor_:
+/**
+ * @license
+ * Copyright 2022 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t,n,s,r){const a=Gr(e,"shape","raggedTensorToTensor","int32"),i=Gr(t,"values","raggedTensorToTensor"),o={shape:a,values:i,defaultValue:Gr(n,"defaultValue","raggedTensorToTensor",i.dtype),rowPartitionTensors:s.map(((e,t)=>Gr(e,`tensors${t}`,"raggedTensorToTensor","int32")))},l={rowPartitionTypes:r};return Or.runKernel(Tn,o,l)}});const tc=qr({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){const s=P(e);let r=null;if(null==n||"float32"===n)r=new Float32Array(s);else if("int32"===n)r=new Int32Array(s);else{if("bool"!==n)throw new Error(`Unknown data type ${n}`);r=new Uint8Array(s)}for(let e=0;e=1||0===a);const i=Math.sqrt(-2*Math.log(a)/a);e=this.mean+this.stdDev*s*i,t=this.mean+this.stdDev*r*i,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 rc{constructor(e,t,n,s){this.alpha=e,this.beta=1/t,this.dtype=n;const r=s||Math.random();this.randu=nc.alea(r.toString()),this.randn=new sc(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,s,r,a;for(;;){do{s=this.randn.nextValue(),a=1+this.c*s}while(a<=0);if(a*=a*a,e=s*s,t=1-.331*e*e,n=.5*e+this.d*(1-a+Math.log(a)),r=this.randu(),rnull==this.dtype||"float32"===this.dtype,this.min=e,this.range=t-e,this.dtype=n,null==s&&(s=Math.random()),"number"==typeof s&&(s=s.toString()),!this.canReturnFloat()&&this.range<=1)throw new Error(`The difference between ${e} - ${t} <= 1 and dtype is not float`);this.random=nc.alea(s)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}}const ic=qr({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,s="float32",r){if(null==n&&(n=1),null==s&&(s="float32"),"float32"!==s&&"int32"!==s)throw new Error(`Unsupported data type ${s}`);const a=new rc(t,n,s,r),i=Ya(e,s);for(let e=0;e`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`)),mc(t,0)}});const yc=qr({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=Gr(e,"x","reverse");return O(2===n.rank,(()=>`Error in reverse2D: x must be rank 2 but got rank ${n.rank}.`)),mc(n,t)}});const bc=qr({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=Gr(e,"x","reverse");return O(3===n.rank,(()=>`Error in reverse3D: x must be rank 3 but got rank ${n.rank}.`)),mc(n,t)}});const xc=qr({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=Gr(e,"x","reverse");return O(4===n.rank,(()=>`Error in reverse4D: x must be rank 4 but got rank ${n.rank}.`)),mc(n,t)}});const wc=qr({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:Gr(e,"x","round")};return Or.runKernel(zn,t)}});const vc=qr({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:Gr(e,"x","rsqrt","float32")};return Or.runKernel(Pn,t)}});const kc=qr({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:Gr(e,"x","selu")};return Or.runKernel(Un,t)}});const Ic=qr({separableConv2d_:function(e,t,n,s,r,a=[1,1],i="NHWC"){const o=Gr(e,"x","separableConv2d"),l=Gr(t,"depthwiseFilter","separableConv2d"),u=Gr(n,"pointwiseFilter","separableConv2d");let c=o,h=!1;if(3===o.rank&&(h=!0,c=_o(o,[1,o.shape[0],o.shape[1],o.shape[2]])),"NCHW"===i)throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");O(4===c.rank,(()=>`Error in separableConv2d: input must be rank 4, but got rank ${c.rank}.`)),O(4===l.rank,(()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${l.rank}.`)),O(4===u.rank,(()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${l.rank}.`)),O(1===u.shape[0],(()=>`Error in separableConv2d: the first dimension of pointwise filter must be 1, but got ${u.shape[0]}.`)),O(1===u.shape[1],(()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${u.shape[1]}.`));const p=l.shape[2],d=l.shape[3];O(u.shape[2]===p*d,(()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${p*d}, but got ${u.shape[2]}.`));const f=yl(c,l,s,r,i,a),m=rl(f,u,1,"valid",i);return h?_o(m,[m.shape[1],m.shape[2],m.shape[3]]):m}});const Nc=
+/**
+ * @license
+ * Copyright 2020 Google Inc. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+async function(e,t){const n=Gr(e,"x","setdiff1d"),s=Gr(t,"y","setdiff1d");O(n.dtype===s.dtype,(()=>`x and y should have the same dtype, but got x (${n.dtype}) and y (${s.dtype}).`)),O(1===n.rank,(()=>`x should be 1D tensor, but got x (${n.shape}).`)),O(1===s.rank,(()=>`y should be 1D tensor, but got y (${s.shape}).`));const r=await n.data(),a=await s.data(),i=new Set(a);let o=0;for(let e=0;e`slice1d expects a rank-1 tensor, but got a rank-${s.rank} tensor`)),Bo(s,[t],[n])}});const Ec=qr({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 s=Gr(e,"x","slice2d");return O(2===s.rank,(()=>`slice2d expects a rank-2 tensor, but got a rank-${s.rank} tensor`)),Bo(s,t,n)}});const Rc=qr({slice3d_:
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t,n){const s=Gr(e,"x","slice3d");return O(3===s.rank,(()=>`slice3d expects a rank-3 tensor, but got a rank-${s.rank} tensor`)),Bo(s,t,n)}});const Ac=qr({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 s=Gr(e,"x","slice4d");return O(4===s.rank,(()=>`slice4d expects a rank-4 tensor, but got a rank-${s.rank} tensor`)),Bo(s,t,n)}});const Fc=qr({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=Gr(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 s={logits:n},r={dim:t};return Or.runKernel(es,s,r)}});const _c=qr({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){O("complex64"===e.dtype,(()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`));const t={input:e};return Or.runKernel(St,t)}});const Dc=qr({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){O("complex64"===e.dtype,(()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`));const t={input:e};return Or.runKernel(Mt,t)}});const Oc=qr({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 s;if(t<=2){const r=_o(e,[n,t]);s=Dc(r)}else{const r=[n,2*(t-1)],a=_o(hc(e),[n,t]),i=_o(nu(e),[n,t]),o=mc(Bo(a,[0,1],[n,t-2]),1),l=zo(mc(Bo(i,[0,1],[n,t-2]),1),no(-1)),u=Mo([a,o],1),c=Mo([i,l],1),h=_o(Kr(u,c),[r[0],r[1]]);s=Dc(h)}if(s=hc(s),3===e.rank&&0!==e.shape[0]){const t=s,n=e.shape[0];s=_o(s,[n,s.shape[0]/n,s.shape[1]]),t.dispose()}return s}});const Mc=qr({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 s={x:Gr(e,"x","split")},r={numOrSizeSplits:t,axis:n};return Or.runKernel(Qn,s,r)}});const Lc=qr({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){O("float32"===e.dtype,(()=>`The dtype for rfft() must be real value but got ${e.dtype}`));let n=e.shape[e.shape.length-1];const s=e.size/n;let r;if(null!=t&&t0)),a=e.shape.map((e=>e));a[e.shape.length-1]=t,r=Bo(e,s,a),n=t}else if(null!=t&&t>n){const s=e.shape.map((e=>e));s[e.shape.length-1]=t-n,r=Mo([e,Au(s)],e.shape.length-1),n=t}else r=e;const a=Nl(r),i=_o(Kr(r,a),[s,n]),o=_c(i),l=Math.floor(n/2)+1,u=hc(o),c=nu(o),h=Mc(u,[l,n-l],u.shape.length-1),p=Mc(c,[l,n-l],c.shape.length-1),d=r.shape.slice();return d[r.shape.length-1]=l,_o(Kr(h[0],p[0]),d)}});const zc=qr({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=Gr(e,"a","squaredDifference"),s=Gr(t,"b","squaredDifference");[n,s]=Cr(n,s),ki(n.shape,s.shape);const r={a:n,b:s};return Or.runKernel(is,r,{})}});const Pc=qr({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=Gr(e,"x","squeeze","string_or_numeric");return _o(n,q(n.shape,t).newShape)}});const Bc=qr({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=Hr(e,"tensors","stack","string_or_numeric");O(n.length>=1,(()=>"Pass at least one tensor to tf.stack")),n.length>0&&O(t<=n[0].rank,(()=>"Axis must be <= rank of the tensor"));const s=n,r={axis:t};return Or.runKernel(wn,s,r)}});const Wc=qr({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:Gr(e,"x","step")},s={alpha:t};return Or.runKernel(Is,n,s)}});const Vc=qr({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,s,r=0,a=0,i=0,o=0,l=0){const u={x:Gr(e,"x","stridedSlice","string_or_numeric")},c={begin:t,end:n,strides:s,beginMask:r,endMask:a,ellipsisMask:i,newAxisMask:o,shrinkAxisMask:l};return Or.runKernel(ls,u,c)}});const Uc=qr({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:Gr(e,"x","tan","float32")};return Or.runKernel(ds,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 Gc(e,t){L(e);const n=Wr(e,t);if(1!==n.length)throw new Error("tensor1d() requires values to be a flat/TypedArray");return Xr(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 Hc(e,t,n){if(L(e),null!=t&&2!==t.length)throw new Error("tensor2d() requires shape to have two numbers");const s=Wr(e,n);if(2!==s.length&&1!==s.length)throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");if(1===s.length&&null==t)throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");return Xr(e,t,s,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 jc(e,t,n){if(L(e),null!=t&&4!==t.length)throw new Error("tensor4d() requires shape to have four numbers");const s=Wr(e,n);if(4!==s.length&&1!==s.length)throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");if(1===s.length&&null==t)throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");return Xr(e,t,s,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 qc(e,t,n){if(L(e),null!=t&&5!==t.length)throw new Error("tensor5d() requires shape to have five numbers");const s=Wr(e,n);if(5!==s.length&&1!==s.length)throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");if(1===s.length&&null==t)throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");return Xr(e,t,s,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 Kc(e,t,n){if(L(e),null!=t&&6!==t.length)throw new Error("tensor6d() requires shape to have six numbers");const s=Wr(e,n);if(6!==s.length&&1!==s.length)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(1===s.length&&null==t)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return Xr(e,t=t||s,s,n)}const Xc=qr({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 s=Gr(e,"x","topk");if(0===s.rank)throw new Error("topk() expects the input to be of rank 1 or higher");const r=s.shape[s.shape.length-1];if(t<0)throw new Error(`'k' passed to topk() must be >= 0 but got ${t}`);if(t>r)throw new Error(`'k' passed to topk() must be <= the last dimension (${r}) but got ${t}`);const a={x:s},i={k:t,sorted:n},[o,l]=Or.runKernel(gs,a,i);return{values:o,indices:l}}});const Yc=qr({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,s,r){if(null!=s&&"bool"===s)throw new Error("Unsupported data type $ { dtype }");const a=new sc(t,n,s,!0,r),i=Ya(e,s);for(let e=0;e0,(()=>"The input tensor must be at least 1D"));const s={x:n},r={axis:t},[a,i]=Or.runKernel(xs,s,r);return{values:a,indices:i}}});const Jc=qr({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 s=Gr(e,"x","unsortedSegmentSum"),r=Gr(t,"segmentIds","unsortedSegmentSum","int32");O(W(n),(()=>"numSegments must be of dtype int"));const a={x:s,segmentIds:r},i={numSegments:n};return Or.runKernel(vs,a,i)}});const Qc=qr({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=Gr(e,"x","unstack","string_or_numeric");O(t>=-n.shape.length&&t`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`));const s={value:n},r={axis:t};return Or.runKernel(ws,s,r)}});
+/**
+ * @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 eh(e,t){return Nu(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 th(e,t=!0,n,s){return Or.makeVariable(e,t,n,s)}
+/**
+ * @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 nh(e,t){const n=[];for(let e=0;e0,(()=>"mask cannot be scalar")),M(o.slice(a,a+i),r.shape,"mask's shape must match the first K dimensions of tensor's shape,");let l=1;for(let e=a;et)).reverse()),O(s.rank===t.length,(()=>`Error in transpose: rank of input ${s.rank} must match length of perm ${t}.`)),t.forEach((e=>{O(e>=0&&e"All entries in 'perm' must be between 0 and "+(s.rank-1)+` but got ${t}`))})),s.rank<=1)return s.clone();const r={x:s},a={perm:t};return"complex64"===s.dtype?Zi((()=>{let e=hc(s),t=nu(s);return e=Or.runKernel(bs,{x:e},a),t=Or.runKernel(bs,{x:t},a),n&&(t=du(t)),Kr(e,t)})):Or.runKernel(bs,r,a)}});const ih=qr({movingAverage_:
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t,n,s,r=!0){const a=Gr(e,"v","movingAverage"),i=Gr(t,"x","movingAverage"),o=Gr(n,"decay","movingAverage");var l,u;u=i,O((l=a).dtype===u.dtype,(()=>`The dtypes of the first(${l.dtype}) and second(${u.dtype}) input must match`)),O(B(a.shape,i.shape),(()=>"Shape mismatch in v and x"));const c=no(1),h=gu(c,o);let p=zo(gu(i,a),h);if(r){O(null!=s,(()=>"When using zeroDebias: true, step is required."));const e=Gr(s,"step","movingAverage");p=vl(p,gu(c,Bl(o,e)))}return oo(a,p)}});function oh(e,t,n){const s=t.rank>1?t.shape[t.rank-1]:1,r=t.rank>1?t.rank-1:1,a=`Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${n.shape}, indices.shape: ${t.shape}, shape: ${e}, sliceDim: ${s}, and batchDim: ${r}.`;if(n.rank1?t.shape[s-1]:1,a=n.length;let i=1;for(let e=r;e2)throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${e.shape}.`);const r=e.rank>0?e.shape[0]:1,a=e.rank>1?e.shape[1]:1;if(n.length!==a)throw new Error(`outputShape has incorrect number of elements:, ${n.length}, should be: ${a}.`);const i=t.size;if(0!==t.rank&&(1!==t.rank||i!==r))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${r}]`);if(t.dtype!==s.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}(r,a,n,i);const o={sparseIndices:r,sparseValues:a,defaultValue:i},l={outputShape:n};return Or.runKernel(as,o,l)}});const ph=qr({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=Gr(t,"indices","gatherND","int32"),s={params:Gr(e,"x","gatherND","string_or_numeric"),indices:n};return Or.runKernel(Ft,s)}});const dh=qr({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,s){const r=Gr(e,"x","dropout");if(O("float32"===r.dtype,(()=>`x has to be a floating point tensor since it's going to be scaled, but got a ${r.dtype} tensor instead.`)),O(t>=0&&t<1,(()=>`rate must be a float in the range [0, 1), but got ${t}.`)),0===t)return e instanceof gr?r.clone():r;const a=
+/**
+ * @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(B(e.shape,t))return t;if(e.shape.length===t.length){const n=[];for(let s=0;s1,(()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${s.rank}`)),O(s.rank-1===r.rank,(()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${s.rank} and targets rank ${r.rank}`)),M(s.shape.slice(0,s.shape.length-1),r.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");const a=s.shape[s.shape.length-1];O(n>0&&n<=a,(()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${a}), but got ${n}`));const i=await s.data(),o=await r.data(),[l,u]=[i.length/a,a],c=K("bool",l);for(let e=0;et.value-e.value)),c[e]=0;for(let t=0;t`Error in conv2dDerFilter: input must be rank 4, but got shape ${o.shape}.`)),O(4===l.rank,(()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`)),O(4===n.length,(()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`));const u="NHWC"===a?o.shape[3]:o.shape[1],c="NHWC"===a?l.shape[3]:l.shape[1];O(u===n[2],(()=>`Error in conv2dDerFilter: depth of input ${u}) must match input depth in filter (${n[2]}.`)),O(c===n[3],(()=>`Error in conv2dDerFilter: depth of dy (${c}) must match output depth for filter (${n[3]}).`)),Fo("conv2dDerFilter",r,i);const h={x:o,dy:l},p={strides:s,pad:r,dataFormat:a,dimRoundingMode:i,filterShape:n};return Or.runKernel(Ze,h,p)}});
+/**
+ * @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 bh(e,t,n){if(null==n||"linear"===n)return e;if("relu"===n)return zo(e,Wc(t));throw new Error(`Cannot compute gradient for fused activation ${n}.`)}function xh(e,t){let n=t;const s=vi(e.shape,t.shape);return s.length>0&&(n=Ul(n,s)),_o(n,e.shape)}function wh(e,t,n,s){if("linear"===t)return e;if("relu"===t)return dc(e);if("elu"===t)return $l(e);if("relu6"===t)return fc(e);if("prelu"===t)return Zu(e,n);if("leakyrelu"===t)return iu(e,s);if("sigmoid"===t)return Po(e);throw new Error(`Unknown fused activation ${t}.`)}const vh=(e,t)=>!(e>0)||"linear"===t;const kh=qr({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:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(l=l||"linear",!1===vh(Or.state.gradientDepth,l)){O("NHWC"===r,(()=>`Error in fused conv2d: got dataFormat of ${r} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`));let h=rl(e,t,n,s,r,a,i);return null!=o&&(h=oo(h,o)),wh(h,l,u,c)}const h=Gr(e,"x","conv2d","float32"),p=Gr(t,"filter","conv2d","float32");let d=h,f=!1;3===h.rank&&(f=!0,d=_o(h,[1,h.shape[0],h.shape[1],h.shape[2]])),O(4===d.rank,(()=>`Error in fused conv2d: input must be rank 4, but got rank ${d.rank}.`)),O(4===p.rank,(()=>`Error in fused conv2d: filter must be rank 4, but got rank ${p.rank}.`)),Fo("fused conv2d",s,i);const m="NHWC"===r?d.shape[3]:d.shape[1];O(p.shape[2]===m,(()=>`Error in conv2d: depth of input (${m}) must match input depth for filter ${p.shape[2]}.`)),O(Ro(n,a),(()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`));const g=ko(d.shape,p.shape,n,a,s,i);let y,b;if(null!=o&&(y=Gr(o,"bias","fused conv2d"),[y]=Cr(y,h),"NHWC"===r?ki(g.outShape,y.shape):(O(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-${y.shape.length}.`)),O(0===y.shape.length||y.shape[0]===g.outChannels||1===y.shape[0],(()=>`Error in fused conv2d: bias shape (${y.shape}) is not compatible with the number of output channels (${g.outChannels})`)))),null!=u){const e=u.shape;if(O(e.length<=1||3===e.length,(()=>`Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${e.length}.`)),1===e.length)O(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{ki(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=Gr(u,"prelu weights","fused conv2d")}const x=(e,t)=>{O("NHWC"===r,(()=>`Error in gradient of fused conv2D: got dataFormat of ${r} but only NHWC is currently supported.`));const[i,o,u,c]=t,h=bh(e,u,l);O(Eo(a),(()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`));const p=[il(o.shape,h,i,n,s),yh(o,h,i.shape,n,s)];if(null!=c){const e=xh(c,h);p.push(e)}return p},w={x:d,filter:p,bias:y,preluActivationWeights:b},v={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:i,activation:l,leakyreluAlpha:c};if(null==o){const e=to(((e,t,n)=>{let s=Or.runKernel(Cs,w,v);return n([t,e,s]),f&&(s=_o(s,[s.shape[1],s.shape[2],s.shape[3]])),{value:s,gradFunc:x}}));return e(d,p)}{const e=to(((e,t,n,s)=>{let r=Or.runKernel(Cs,w,v);return s([t,e,r,n]),f&&(r=_o(r,[r.shape[1],r.shape[2],r.shape[3]])),{value:r,gradFunc:x}}));return e(d,p,y)}}});const Ih=qr({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,s,r,a=[1,1],i){let o=e;3===e.rank&&(o=_o(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;3===l.rank&&(l=_o(t,[1,t.shape[0],t.shape[1],t.shape[2]]));const u={x:o,dy:l},c={strides:s,pad:r,dimRoundingMode:i,dilations:a,filterShape:n};return Or.runKernel(ct,u,c)}});const Nh=qr({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,s,r,a=[1,1],i){let o=t,l=!1;3===t.rank&&(l=!0,o=_o(t,[1,t.shape[0],t.shape[1],t.shape[2]]));const u={dy:o,filter:n},c={strides:s,pad:r,dimRoundingMode:i,dilations:a,inputShape:e},h=Or.runKernel(ht,u,c);return l?_o(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});const Sh=qr({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:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:i,bias:o,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(!1===vh(Or.state.gradientDepth,l)){let h=yl(e,t,n,s,r,a,i);return null!=o&&(h=oo(h,o)),wh(h,l,u,c)}const h=Gr(e,"x","depthwiseConv2d","float32"),p=Gr(t,"filter","depthwiseConv2d","float32");let d=h,f=!1;3===h.rank&&(f=!0,d=_o(h,[1,h.shape[0],h.shape[1],h.shape[2]])),O(4===d.rank,(()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${d.rank}.`)),O(4===p.rank,(()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${p.rank}.`)),O(d.shape[3]===p.shape[2],(()=>`Error in fused depthwiseConv2d: number of input channels (${d.shape[3]}) must match the inChannels dimension in filter ${p.shape[2]}.`)),null==a&&(a=[1,1]),O(Ro(n,a),(()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`)),Fo("fused depthwiseConv2d",s,i);const m=ko(d.shape,p.shape,n,a,s,i,!0);let g,y;null!=o&&(g=Gr(o,"bias","fused conv2d"),[g]=Cr(g,h),ki(m.outShape,g.shape)),null!=u&&(y=Gr(u,"prelu weights","fused depthwiseConv2d"));const b=(e,t)=>{O(Eo(a),(()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${a}'`));const[r,o,u,c]=t,h=bh(e,u,l),p=Nh(o.shape,h,r,n,s,a,i),d=Ih(o,h,r.shape,n,s,a,i);if(null!=c){return[p,d,xh(g,h)]}return[p,d]},x={x:d,filter:p,bias:g,preluActivationWeights:y},w={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:i,activation:l,leakyreluAlpha:c};if(null==o){const e=to(((e,t,n)=>{let s=Or.runKernel($s,x,w);return n([t,e,s]),f&&(s=_o(s,[s.shape[1],s.shape[2],s.shape[3]])),{value:s,gradFunc:b}}));return e(d,p)}{const e=to(((e,t,n,s)=>{let r=Or.runKernel($s,x,w);return s([t,e,r,n]),f&&(r=_o(r,[r.shape[1],r.shape[2],r.shape[3]])),{value:r,gradFunc:b}}));return e(d,p,g)}}});const Th=qr({fusedMatMul_:
+/**
+ * @license
+ * Copyright 2019 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function({a:e,b:t,transposeA:n=!1,transposeB:s=!1,bias:r,activation:a="linear",preluActivationWeights:i,leakyreluAlpha:o=.2}){if(!1===vh(Or.state.gradientDepth,a)){let l=Lo(e,t,n,s);return null!=r&&(l=oo(l,r)),wh(l,a,i,o)}let l=Gr(e,"a","fused matMul"),u=Gr(t,"b","fused matMul");[l,u]=Cr(l,u);const c=n?l.shape[l.rank-2]:l.shape[l.rank-1],h=s?u.shape[u.rank-1]:u.shape[u.rank-2],p=n?l.shape[l.rank-1]:l.shape[l.rank-2],d=s?u.shape[u.rank-2]:u.shape[u.rank-1],f=l.shape.slice(0,-2),m=u.shape.slice(0,-2),g=P(f),y=P(m);O(c===h,(()=>`Error in fused matMul: inner shapes (${c}) and (${h}) of Tensors with shapes ${l.shape} and ${u.shape} and transposeA=${n} and transposeB=${s} must match.`));const b=ki(l.shape.slice(0,-2),u.shape.slice(0,-2)).concat([p,d]),x=_o(l,n?[g,c,p]:[g,p,c]),w=_o(u,s?[y,d,h]:[y,h,d]);let v,k;null!=r&&(v=Gr(r,"bias","fused matMul"),[v]=Cr(v,l),ki(b,v.shape)),null!=i&&(k=Gr(i,"prelu weights","fused matMul"));const I=(e,t)=>{const[i,o,l,u]=t,c=bh(_o(e,l.shape),l,a);let h,p;if(n||s?!n&&s?(h=Lo(c,o,!1,!1),p=Lo(c,i,!0,!1)):n&&!s?(h=Lo(o,c,!1,!0),p=Lo(i,c,!1,!1)):(h=Lo(o,c,!0,!0),p=Lo(c,i,!0,!0)):(h=Lo(c,o,!1,!0),p=Lo(i,c,!0,!1)),null!=r){return[h,p,xh(u,c)]}return[h,p]},N={a:x,b:w,bias:v,preluActivationWeights:k},S={transposeA:n,transposeB:s,activation:a,leakyreluAlpha:o};if(null==r){const e=to(((e,t,n)=>{const s=Or.runKernel(Ts,N,S);return n([e,t,s]),{value:_o(s,b),gradFunc:I}}));return e(x,w)}{const e=to(((e,t,n,s)=>{const r=Or.runKernel(Ts,N,S);return s([e,t,r,n]),{value:_o(r,b),gradFunc:I}}));return e(x,w,v)}}});const Ch=qr({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 mh(e,.54,.46)}});const $h=qr({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 mh(e,.5,.5)}});const Eh=qr({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,s=!1,r=0){let a=0;const i=[];for(;a+t<=e.size;)i.push(Bo(e,a,t)),a+=n;if(s)for(;a`Error in cropAndResize: image must be rank 4,but got rank ${i.rank}.`)),O(2===o.rank&&4===o.shape[1],(()=>`Error in cropAndResize: boxes must be have size [${u},4] but had shape ${o.shape}.`)),O(1===l.rank&&l.shape[0]===u,(()=>`Error in cropAndResize: boxInd must be have size [${u}] but had shape ${o.shape}.`)),O(2===s.length,(()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${s.length}.`)),O(s[0]>=1&&s[1]>=1,(()=>`cropSize must be atleast [1,1], but was ${s}`)),O("bilinear"===r||"nearest"===r,(()=>`method must be bilinear or nearest, but was ${r}`));const c={image:i,boxes:o,boxInd:l},h={method:r,extrapolationValue:a,cropSize:s};return Or.runKernel(it,c,h)}});const Fh=qr({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=Gr(e,"image","flipLeftRight","float32");O(4===t.rank,(()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`));const n={image:t};return Or.runKernel(Ct,n,{})}});const _h=qr({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=Gr(e,"image","grayscaleToRGB"),n=t.rank-1,s=t.shape[n];O(t.rank>=2,(()=>`Error in grayscaleToRGB: images must be at least rank 2, but got rank ${t.rank}.`)),O(1===s,(()=>`Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${s}.`));const r=new Array(t.rank);return r.fill(1,0,n),r[n]=3,Yl(t,r)}});const Dh=qr({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,s=.5){const r=Gr(e,"image","rotateWithOffset","float32");O(4===r.rank,(()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${r.rank}.`));const a={image:r},i={radians:t,fillValue:n,center:s};return Or.runKernel(Ss,a,i)}});
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function Oh(e,t,n,s,r,a){null==s&&(s=.5),null==r&&(r=Number.NEGATIVE_INFINITY),null==a&&(a=0);const i=e.shape[0];return n=Math.min(n,i),O(0<=s&&s<=1,(()=>`iouThreshold must be in [0, 1], but was '${s}'`)),O(2===e.rank,(()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`)),O(4===e.shape[1],(()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`)),O(1===t.rank,(()=>"scores must be a 1D tensor")),O(t.shape[0]===i,(()=>`scores has incompatible shape with boxes. Expected ${i}, but was ${t.shape[0]}`)),O(0<=a&&a<=1,(()=>`softNmsSigma must be in [0, 1], but was '${a}'`)),{maxOutputSize:n,iouThreshold:s,scoreThreshold:r,softNmsSigma:a}}const Mh=qr({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,s=.5,r=Number.NEGATIVE_INFINITY){const a=Gr(e,"boxes","nonMaxSuppression","float32"),i=Gr(t,"scores","nonMaxSuppression","float32"),o=Oh(a,i,n,s,r),l={maxOutputSize:n=o.maxOutputSize,iouThreshold:s=o.iouThreshold,scoreThreshold:r=o.scoreThreshold};return Or.runKernel(mn,{boxes:a,scores:i},l)}});
+/**
+ * @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 Lh(e,t,n){const s=function(e,t,n){return function(e,t,n){let s=0,r=e.length,a=0,i=!1;for(;s>>1);const o=n(t,e[a]);o>0?s=a+1:(r=a,i=!o)}return i?s:-s-1}(e,t,n||zh)}(e,t,n),r=s<0?-(s+1):s;e.splice(r,0,t)}function zh(e,t){return e>t?1:er&&u.push({score:t[e],boxIndex:e,suppressBeginIndex:0});u.sort(Hh);const c=a>0?-.5/a:0,h=[],p=[];for(;h.length0;){const t=u.pop(),{score:n,boxIndex:a,suppressBeginIndex:i}=t;if(n=i;--n){const i=Uh(e,a,h[n]);if(i>=s){o=!0;break}if(t.score=t.score*Gh(s,c,i),t.score<=r)break}t.suppressBeginIndex=h.length,o||(t.score===n?(h.push(a),p.push(t.score)):t.score>r&&Lh(u,t,Hh))}const d=h.length,f=n-d;o&&f>0&&(h.push(...new Array(f).fill(0)),p.push(...new Array(f).fill(0)));const m={selectedIndices:h};return i&&(m.selectedScores=p),l&&(m.validOutputs=d),m}function Uh(e,t,n){const s=e.subarray(4*t,4*t+4),r=e.subarray(4*n,4*n+4),a=Math.min(s[0],s[2]),i=Math.min(s[1],s[3]),o=Math.max(s[0],s[2]),l=Math.max(s[1],s[3]),u=Math.min(r[0],r[2]),c=Math.min(r[1],r[3]),h=Math.max(r[0],r[2]),p=Math.max(r[1],r[3]),d=(o-a)*(l-i),f=(h-u)*(p-c);if(d<=0||f<=0)return 0;const m=Math.max(a,u),g=Math.max(i,c),y=Math.min(o,h),b=Math.min(l,p),x=Math.max(y-m,0)*Math.max(b-g,0);return x/(d+f-x)}function Gh(e,t,n){const s=Math.exp(t*n*n);return n<=e?s:0}function Hh(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}const jh=
+/**
+ * @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,s=.5,r=Number.NEGATIVE_INFINITY){const a=Gr(e,"boxes","nonMaxSuppressionAsync"),i=Gr(t,"scores","nonMaxSuppressionAsync"),o=Oh(a,i,n,s,r);n=o.maxOutputSize,s=o.iouThreshold,r=o.scoreThreshold;const l=await Promise.all([a.data(),i.data()]),u=l[0],c=l[1],{selectedIndices:h}=Ph(u,c,n,s,r);return a!==e&&a.dispose(),i!==t&&i.dispose(),Gc(h,"int32")};const qh=qr({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,s=.5,r=Number.NEGATIVE_INFINITY,a=0){const i=Gr(e,"boxes","nonMaxSuppression"),o=Gr(t,"scores","nonMaxSuppression"),l=Oh(i,o,n,s,r,a),u={boxes:i,scores:o},c={maxOutputSize:n=l.maxOutputSize,iouThreshold:s=l.iouThreshold,scoreThreshold:r=l.scoreThreshold,softNmsSigma:a=l.softNmsSigma},h=Or.runKernel(yn,u,c);return{selectedIndices:h[0],selectedScores:h[1]}}});const Kh=
+/**
+ * @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,s=.5,r=Number.NEGATIVE_INFINITY,a=0){const i=Gr(e,"boxes","nonMaxSuppressionAsync"),o=Gr(t,"scores","nonMaxSuppressionAsync"),l=Oh(i,o,n,s,r,a);n=l.maxOutputSize,s=l.iouThreshold,r=l.scoreThreshold,a=l.softNmsSigma;const u=await Promise.all([i.data(),o.data()]),c=u[0],h=u[1],{selectedIndices:p,selectedScores:d}=Wh(c,h,n,s,r,a);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Gc(p,"int32"),selectedScores:Gc(d)}};const Xh=qr({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,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){const i=Gr(e,"boxes","nonMaxSuppression"),o=Gr(t,"scores","nonMaxSuppression"),l=Oh(i,o,n,s,r,null),u={boxes:i,scores:o},c={maxOutputSize:l.maxOutputSize,iouThreshold:l.iouThreshold,scoreThreshold:l.scoreThreshold,padToMaxOutputSize:a},h=Or.runKernel(gn,u,c);return{selectedIndices:h[0],validOutputs:h[1]}}});const Yh=
+/**
+ * @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,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){const i=Gr(e,"boxes","nonMaxSuppressionAsync"),o=Gr(t,"scores","nonMaxSuppressionAsync"),l=Oh(i,o,n,s,r,null),u=l.maxOutputSize,c=l.iouThreshold,h=l.scoreThreshold,[p,d]=await Promise.all([i.data(),o.data()]),{selectedIndices:f,validOutputs:m}=Bh(p,d,u,c,h,a);return i!==e&&i.dispose(),o!==t&&o.dispose(),{selectedIndices:Gc(f,"int32"),validOutputs:no(m,"int32")}};const Zh=qr({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,s=!1){const r=Gr(e,"images","resizeBilinear");O(3===r.rank||4===r.rank,(()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${r.rank}.`)),O(2===t.length,(()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`)),O(!1===s||!1===n,(()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false."));let a=r,i=!1;3===r.rank&&(i=!0,a=_o(r,[1,r.shape[0],r.shape[1],r.shape[2]]));const[]=t,o={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=Or.runKernel(Dn,o,l);return i?_o(u,[u.shape[1],u.shape[2],u.shape[3]]):u}});const Jh=qr({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,s=!1){const r=Gr(e,"images","resizeNearestNeighbor");O(3===r.rank||4===r.rank,(()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${r.rank}.`)),O(2===t.length,(()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`)),O("float32"===r.dtype||"int32"===r.dtype,(()=>"`images` must have `int32` or `float32` as dtype")),O(!1===s||!1===n,(()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false."));let a=r,i=!1;3===r.rank&&(i=!0,a=_o(r,[1,r.shape[0],r.shape[1],r.shape[2]]));const[]=t,o={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=Or.runKernel(Fn,o,l);return i?_o(u,[u.shape[1],u.shape[2],u.shape[3]]):u}});const Qh=qr({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,s=.5){const r=Gr(e,"image","threshold"),a=r.shape[0]*r.shape[1];let i,o,l,u,c=zo(Gc([s]),255);if(O(3===r.rank,(()=>`Error in threshold: image must be rank 3,but got rank ${r.rank}.`)),O(3===r.shape[2]||1===r.shape[2],(()=>`Error in threshold: image color channel must be equal to 3 or 1but got ${r.shape[2]}.`)),O("int32"===r.dtype||"float32"===r.dtype,(()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${r.dtype}.`)),O("otsu"===t||"binary"===t,(()=>`Method must be binary or otsu, but was ${t}`)),3===r.shape[2]){[i,o,l]=Mc(r,[1,1,1],-1);const e=zo(i,.2989),t=zo(o,.587),n=zo(l,.114);u=oo(oo(e,t),n)}else u=e;if("otsu"===t){c=function(e,t){let n,s,r,a,i,o,l=Gc([-1]),u=Gc([0]),c=Gc([0]);for(let h=0;h`Error in transform: image must be rank 4,but got rank ${i.rank}.`)),O(2===o.rank&&(o.shape[0]===i.shape[0]||1===o.shape[0])&&8===o.shape[1],(()=>"Error in transform: Input transform should be batch x 8 or 1 x 8")),O(null==a||2===a.length,(()=>`Error in transform: outputShape must be [height, width] or null, but got ${a}.`));const l={image:i,transforms:o},u={interpolation:n,fillMode:s,fillValue:r,outputShape:a};return Or.runKernel(ys,l,u)}});const tp=qr({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){O(t%1==0,(()=>`bandPart(): numLower must be an integer, got ${t}.`)),O(n%1==0,(()=>`bandPart(): numUpper must be an integer, got ${n}.`));const s=Gr(e,"a","bandPart");O(s.rank>=2,(()=>`bandPart(): Rank must be at least 2, got ${s.rank}.`));const r=s.shape,[a,i]=s.shape.slice(-2);if(!(t<=a))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${a}).`);if(!(n<=i))throw new Error(`bandPart(): numUpper (${n}) must not be greater than the number of columns (${i}).`);t<0&&(t=a),n<0&&(n=i);const o=_o(cc(0,a,1,"int32"),[-1,1]),l=cc(0,i,1,"int32"),u=gu(o,l),c=xu(lu(u,no(+t,"int32")),tu(u,no(-n,"int32"))),h=Au([a,i],s.dtype);return _o(Bc(Qc(_o(s,[-1,a,i])).map((e=>Il(c,e,h)))),r)}});const np=qr({gramSchmidt_:
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e){let t;if(Array.isArray(e)){t=!1,O(null!=e&&e.length>0,(()=>"Gram-Schmidt process: input must not be null, undefined, or empty"));const n=e[0].shape[0];for(let t=1;t`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[t].shape[0]} vs. ${n})`))}else t=!0,e=Mc(e,e.shape[0],0).map((e=>Pc(e,[0])));O(e.length<=e[0].shape[0],(()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`));const n=[],s=e;for(let t=0;t{let e=s[t];if(t>0)for(let s=0;s{O(2===e.shape.length,(()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`));const n=e.shape[0],s=e.shape[1];let r=Zl(n),a=Ja(e);const i=Hc([[1]],[1,1]);let o=Ja(i);const l=n>=s?s:n;for(let e=0;e{const t=Bo(a,[e,e],[n-e,1]),l=Hl(t),u=Bo(a,[e,e],[1,1]),c=Il(eu(u,0),Hc([[-1]]),Hc([[1]])),h=gu(u,zo(c,l)),p=vl(t,h);o=1===p.shape[0]?Ja(i):Mo([i,Bo(p,[1,0],[p.shape[0]-1,p.shape[1]])],0);const d=du(vl(Lo(c,h),l)),f=Bo(a,[e,0],[n-e,s]),m=zo(d,o),g=ah(o);if(0===e)a=gu(f,Lo(m,Lo(g,f)));else{const t=gu(f,Lo(m,Lo(g,f)));a=Mo([Bo(a,[0,0],[e,s]),t],0)}const y=ah(m),b=Bo(r,[0,e],[n,r.shape[1]-e]);if(0===e)r=gu(b,Lo(Lo(b,o),y));else{const t=gu(b,Lo(Lo(b,o),y));r=Mo([Bo(r,[0,0],[n,e]),t],1)}return[o,a,r]})),Ji([t,l,u])}return!t&&n>s&&(r=Bo(r,[0,0],[n,s]),a=Bo(a,[0,0],[s,s])),[r,a]}))}const rp=qr({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(O(e.rank>=2,(()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`)),2===e.rank)return sp(e,t);{const n=e.shape.slice(0,e.shape.length-2).reduce(((e,t)=>e*t)),s=Qc(_o(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),r=[],a=[];s.forEach((e=>{const[n,s]=sp(e,t);r.push(n),a.push(s)}));return[_o(Bc(r,0),e.shape),_o(Bc(a,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 ap;!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"}(ap||(ap={}));const ip=qr({computeWeightedLoss_:function(e,t,n=ap.SUM_BY_NONZERO_WEIGHTS){const s=Gr(e,"losses","computeWeightedLoss");let r=null;null!=t&&(r=Gr(t,"weights","computeWeightedLoss"));const a=null==r?s:zo(s,r);if(n===ap.NONE)return a;if(n===ap.SUM)return Ul(a);if(n===ap.MEAN){if(null==r)return Ru(a);{const e=s.size/r.size,t=vl(Ul(a),Ul(r));return e>1?vl(t,no(e)):t}}if(n===ap.SUM_BY_NONZERO_WEIGHTS){if(null==r)return vl(Ul(a),no(s.size));{const e=zo(r,Fu(s.shape)),t=Za(Ul(Bu(e,no(0))),"float32");return vl(Ul(a),t)}}throw Error(`Unknown reduction: ${n}`)}});const op=qr({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,s=ap.SUM_BY_NONZERO_WEIGHTS){const r=Gr(e,"labels","absoluteDifference"),a=Gr(t,"predictions","absoluteDifference");let i=null;null!=n&&(i=Gr(n,"weights","absoluteDifference")),M(r.shape,a.shape,"Error in absoluteDifference: ");const o=ro(gu(r,a));return ip(o,i,s)}});const lp=qr({cosineDistance_:function(e,t,n,s,r=ap.SUM_BY_NONZERO_WEIGHTS){const a=Gr(e,"labels","cosineDistance"),i=Gr(t,"predictions","cosineDistance");let o=null;null!=s&&(o=Gr(s,"weights","cosineDistance")),M(a.shape,i.shape,"Error in cosineDistance: ");const l=no(1),u=gu(l,Ul(zo(a,i),n,!0));return ip(u,o,r)}});const up=qr({hingeLoss_:function(e,t,n,s=ap.SUM_BY_NONZERO_WEIGHTS){let r=Gr(e,"labels","hingeLoss");const a=Gr(t,"predictions","hingeLoss");let i=null;null!=n&&(i=Gr(n,"weights","hingeLoss")),M(r.shape,a.shape,"Error in hingeLoss: ");const o=no(1);r=gu(zo(no(2),r),o);const l=dc(gu(o,zo(r,a)));return ip(l,i,s)}});const cp=qr({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,s=1,r=ap.SUM_BY_NONZERO_WEIGHTS){const a=Gr(e,"labels","huberLoss"),i=Gr(t,"predictions","huberLoss");let o=null;null!=n&&(o=Gr(n,"weights","huberLoss")),M(a.shape,i.shape,"Error in huberLoss: ");const l=no(s),u=ro(gu(i,a)),c=Du(u,l),h=gu(u,c),p=oo(zo(no(.5),Vl(c)),zo(l,h));return ip(p,o,r)}});const hp=qr({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,s=1e-7,r=ap.SUM_BY_NONZERO_WEIGHTS){const a=Gr(e,"labels","logLoss"),i=Gr(t,"predictions","logLoss");let o=null;null!=n&&(o=Gr(n,"weights","logLoss")),M(a.shape,i.shape,"Error in logLoss: ");const l=no(1),u=no(s),c=du(zo(a,hu(oo(i,u)))),h=zo(gu(l,a),hu(oo(gu(l,i),u))),p=gu(c,h);return ip(p,o,r)}});const pp=qr({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,s=ap.SUM_BY_NONZERO_WEIGHTS){const r=Gr(e,"labels","meanSquaredError"),a=Gr(t,"predictions","meanSquaredError");let i=null;null!=n&&(i=Gr(n,"weights","meanSquaredError")),M(r.shape,a.shape,"Error in meanSquaredError: ");const o=zc(r,a);return ip(o,i,s)}});const dp=qr({sigmoidCrossEntropy_:function(e,t,n,s=0,r=ap.SUM_BY_NONZERO_WEIGHTS){let a=Gr(e,"multiClassLabels","sigmoidCrossEntropy");const i=Gr(t,"logits","sigmoidCrossEntropy");let o=null;if(null!=n&&(o=Gr(n,"weights","sigmoidCrossEntropy")),M(a.shape,i.shape,"Error in sigmoidCrossEntropy: "),s>0){const e=no(s),t=no(1),n=no(.5);a=oo(zo(a,gu(t,e)),zo(n,e))}const l=
+/**
+ * @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=Gr(e,"labels","sigmoidCrossEntropyWithLogits"),s=Gr(t,"logits","sigmoidCrossEntropyWithLogits");M(n.shape,s.shape,"Error in sigmoidCrossEntropyWithLogits: ");const r=dc(s),a=zo(s,n),i=pu(ql(du(ro(s))));return oo(gu(r,a),i)}(a,i);return ip(l,o,r)}});const fp=qr({softmaxCrossEntropy_:function(e,t,n,s=0,r=ap.SUM_BY_NONZERO_WEIGHTS){let a=Gr(e,"onehotLabels","softmaxCrossEntropy");const i=Gr(t,"logits","softmaxCrossEntropy");let o=null;if(null!=n&&(o=Gr(n,"weights","softmaxCrossEntropy")),M(a.shape,i.shape,"Error in softmaxCrossEntropy: "),s>0){const e=no(s),t=no(1),n=no(a.shape[1]);a=oo(zo(a,gu(t,e)),vl(e,n))}const l=
+/**
+ * @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 s=to(((e,t,s)=>{const r=bu(t,[n],!0),a=gu(Za(t,"float32"),r);s([e,a]);const i=du(zo(a,e));return{value:Ul(i,[n]),gradFunc:(e,t)=>{const[s,r]=t,a=_l(e.shape,[n]);return[zo(_o(e,a),gu(Za(s,"float32"),ql(r))),zo(_o(e,a),gu(ql(r),Za(s,"float32")))]}}}));return s(e,t)}(a,i);return ip(l,o,r)}});const mp=qr({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,s){const r=Gr(e,"indices","sparseFillEmptyRows","int32"),a=Gr(t,"values","sparseFillEmptyRows"),i=Gr(n,"denseShape","sparseFillEmptyRows","int32"),o=Gr(s,"defaultValue","sparseFillEmptyRows",a.dtype);if(2!==r.rank)throw new Error(`Indices should be Tensor2D but received shape\n ${r.shape}`);if(1!==a.rank)throw new Error(`Values should be Tensor1D but received shape ${a.shape}`);if(1!==i.rank)throw new Error(`Dense shape should be Tensor1D but received shape ${i.shape}`);if(0!==o.rank)throw new Error(`Default value should be a scalar but received shape ${o.shape}`);const l={indices:r,values:a,denseShape:i,defaultValue:o},u=Or.runKernel(ts,l);return{outputIndices:u[0],outputValues:u[1],emptyRowIndicator:u[2],reverseIndexMap:u[3]}}});const gp=qr({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 s=Gr(e,"inputIndices","sparseReshape","int32"),r=Gr(t,"inputShape","sparseReshape","int32"),a=Gr(n,"newShape","sparseReshape","int32");if(2!==s.rank)throw new Error(`Input indices should be Tensor2D but received shape\n ${s.shape}`);if(1!==r.rank)throw new Error(`Input shape should be Tensor1D but received shape ${r.shape}`);if(1!==a.rank)throw new Error(`New shape should be Tensor1D but received shape ${a.shape}`);const i={inputIndices:s,inputShape:r,newShape:a},o=Or.runKernel(ns,i);return{outputIndices:o[0],outputShape:o[1]}}});const yp=qr({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 s=Gr(e,"data","sparseSegmentMean"),r=Gr(t,"indices","sparseSegmentMean","int32"),a=Gr(n,"segmentIds","sparseSegmentMean","int32");if(s.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==r.rank)throw new Error(`Indices should be Tensor1D but received shape\n ${r.shape}`);if(1!==a.rank)throw new Error(`Segment ids should be Tensor1D but received shape\n ${a.shape}`);const i={data:s,indices:r,segmentIds:a};return Or.runKernel(ss,i)}});const bp=qr({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 s=Gr(e,"data","sparseSegmentSum"),r=Gr(t,"indices","sparseSegmentSum","int32"),a=Gr(n,"segmentIds","sparseSegmentSum","int32");if(s.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==r.rank)throw new Error(`Indices should be Tensor1D but received shape\n ${r.shape}`);if(1!==a.rank)throw new Error(`Segment ids should be Tensor1D but received shape\n ${a.shape}`);const i={data:s,indices:r,segmentIds:a};return Or.runKernel(rs,i)}});const xp=qr({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,s,r,a,i,o){const l=Gr(e,"data","stringNGrams","string");if("string"!==l.dtype)throw new Error("Data must be of datatype string");if(1!==l.shape.length)throw new Error(`Data must be a vector, saw: ${l.shape}`);const u=Gr(t,"dataSplits","stringNGrams");if("int32"!==u.dtype)throw new Error("Data splits must be of datatype int32");const c={separator:n,nGramWidths:s,leftPad:r,rightPad:a,padWidth:i,preserveShortSequences:o},h={data:l,dataSplits:u},p=Or.runKernel(us,h,c);return{nGrams:p[0],nGramsSplits:p[1]}}});const wp=qr({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 s=Gr(e,"input","stringSplit","string"),r=Gr(t,"delimiter","stringSplit","string");if(1!==s.rank)throw new Error(`Input should be Tensor1D but received shape ${s.shape}`);if(0!==r.rank)throw new Error(`Delimiter should be a scalar but received shape ${r.shape}`);const a={skipEmpty:n},i={input:s,delimiter:r},o=Or.runKernel(cs,i,a);return{indices:o[0],values:o[1],shape:o[2]}}});const vp=qr({stringToHashBucketFast_:
+/**
+ * @license
+ * Copyright 2021 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t){const n=Gr(e,"input","stringToHashBucketFast","string"),s={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");const r={input:n};return Or.runKernel(hs,r,s)}}),kp={fft:_c,ifft:Dc,rfft:Lc,irfft:Oc},Ip={hammingWindow:Ch,hannWindow:$h,frame:Eh,stft:Rh},Np={flipLeftRight:Fh,grayscaleToRGB:_h,resizeNearestNeighbor:Jh,resizeBilinear:Zh,rotateWithOffset:Dh,cropAndResize:Ah,nonMaxSuppression:Mh,nonMaxSuppressionAsync:jh,nonMaxSuppressionWithScore:qh,nonMaxSuppressionWithScoreAsync:Kh,nonMaxSuppressionPadded:Xh,nonMaxSuppressionPaddedAsync:Yh,threshold:Qh,transform:ep},Sp={bandPart:tp,gramSchmidt:np,qr:rp},Tp={absoluteDifference:op,computeWeightedLoss:ip,cosineDistance:lp,hingeLoss:up,huberLoss:cp,logLoss:hp,meanSquaredError:pp,sigmoidCrossEntropy:dp,softmaxCrossEntropy:fp},Cp={sparseFillEmptyRows:mp,sparseReshape:gp,sparseSegmentMean:yp,sparseSegmentSum:bp},$p={stringNGrams:xp,stringSplit:wp,stringToHashBucketFast:vp};
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+class Ep extends so{constructor(e,t,n=null){super(),this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],null==n&&(this.epsilon=Or.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const s=Or.registeredVariables[t],r=!1;null==this.accumulatedGrads[n]&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:Zi((()=>Nl(s).variable(r)))}),null==this.accumulatedUpdates[n]&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:Zi((()=>Nl(s).variable(r)))});const a=Array.isArray(e)?e[n].tensor:e[t];if(null==a)return;const i=this.accumulatedGrads[n].variable,o=this.accumulatedUpdates[n].variable;Zi((()=>{const e=oo(zo(i,this.rho),zo(Vl(a),1-this.rho)),t=zo(vl(Wl(oo(o,this.epsilon)),Wl(oo(i,this.epsilon))),a),n=oo(zo(o,this.rho),zo(Vl(t),1-this.rho));i.assign(e),o.assign(n);const r=oo(zo(t,-this.learningRate),s);s.assign(r)}))})),this.incrementIterations()}dispose(){null!=this.accumulatedUpdates&&(Ji(this.accumulatedGrads.map((e=>e.variable))),Ji(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,n=!1;this.accumulatedGrads=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)}))),this.accumulatedUpdates=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)})))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}}Ep.className="Adadelta",Ki(Ep);
+/**
+ * @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 Rp extends so{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 s=Or.registeredVariables[t];if(null==this.accumulatedGrads[n]){const e=!1;this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:Zi((()=>Jo(s.shape,this.initialAccumulatorValue).variable(e)))}}const r=Array.isArray(e)?e[n].tensor:e[t];if(null==r)return;const a=this.accumulatedGrads[n].variable;Zi((()=>{const e=oo(a,Vl(r));a.assign(e);const t=oo(zo(vl(r,Wl(oo(e,Or.backend.epsilon()))),-this.learningRate),s);s.assign(t)}))})),this.incrementIterations()}dispose(){null!=this.accumulatedGrads&&Ji(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)}}Rp.className="Adagrad",Ki(Rp);
+/**
+ * @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 Ap extends so{constructor(e,t,n,s=null){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],Zi((()=>{this.accBeta1=no(t).variable(),this.accBeta2=no(n).variable()})),null==s&&(this.epsilon=Or.backend.epsilon())}applyGradients(e){const t=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);Zi((()=>{const n=gu(1,this.accBeta1),s=gu(1,this.accBeta2);t.forEach(((t,r)=>{const a=Or.registeredVariables[t],i=!1;null==this.accumulatedFirstMoment[r]&&(this.accumulatedFirstMoment[r]={originalName:`${t}/m`,variable:Zi((()=>Nl(a).variable(i)))}),null==this.accumulatedSecondMoment[r]&&(this.accumulatedSecondMoment[r]={originalName:`${t}/v`,variable:Zi((()=>Nl(a).variable(i)))});const o=Array.isArray(e)?e[r].tensor:e[t];if(null==o)return;const l=this.accumulatedFirstMoment[r].variable,u=this.accumulatedSecondMoment[r].variable,c=oo(zo(l,this.beta1),zo(o,1-this.beta1)),h=oo(zo(u,this.beta2),zo(Vl(o),1-this.beta2)),p=vl(c,n),d=vl(h,s);l.assign(c),u.assign(h);const f=oo(zo(vl(p,oo(Wl(d),this.epsilon)),-this.learningRate),a);a.assign(f)})),this.accBeta1.assign(zo(this.accBeta1,this.beta1)),this.accBeta2.assign(zo(this.accBeta2,this.beta2))})),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&Ji(this.accumulatedFirstMoment.map((e=>e.variable))),null!=this.accumulatedSecondMoment&&Ji(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),Zi((()=>{this.accBeta1.assign(Bl(this.beta1,this.iterations_+1)),this.accBeta2.assign(Bl(this.beta2,this.iterations_+1))}));const t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)}))),this.accumulatedSecondMoment=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)})))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}}Ap.className="Adam",Ki(Ap);
+/**
+ * @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 Fp extends so{constructor(e,t,n,s=null,r=0){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],Zi((()=>{this.iteration=no(0).variable(),this.accBeta1=no(t).variable()})),null==s&&(this.epsilon=Or.backend.epsilon())}applyGradients(e){const t=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);Zi((()=>{const n=gu(1,this.accBeta1),s=vl(-this.learningRate,oo(zo(this.iteration,this.decay),1));t.forEach(((t,r)=>{const a=Or.registeredVariables[t],i=!1;null==this.accumulatedFirstMoment[r]&&(this.accumulatedFirstMoment[r]={originalName:`${t}/m`,variable:Nl(a).variable(i)}),null==this.accumulatedWeightedInfNorm[r]&&(this.accumulatedWeightedInfNorm[r]={originalName:`${t}/v`,variable:Nl(a).variable(i)});const o=Array.isArray(e)?e[r].tensor:e[t];if(null==o)return;const l=this.accumulatedFirstMoment[r].variable,u=this.accumulatedWeightedInfNorm[r].variable,c=oo(zo(l,this.beta1),zo(o,1-this.beta1)),h=zo(u,this.beta2),p=ro(o),d=Eu(h,p);l.assign(c),u.assign(d);const f=oo(zo(vl(s,n),vl(c,oo(d,this.epsilon))),a);a.assign(f)})),this.iteration.assign(oo(this.iteration,1)),this.accBeta1.assign(zo(this.accBeta1,this.beta1))})),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&Ji(this.accumulatedFirstMoment.map((e=>e.variable))),null!=this.accumulatedWeightedInfNorm&&Ji(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)}}Fp.className="Adamax",Ki(Fp);
+/**
+ * @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 _p extends so{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 s=Array.isArray(e)?e[n].tensor:e[t];if(null==s)return;const r=Or.registeredVariables[t];Zi((()=>{const e=oo(zo(this.c,s),r);r.assign(e)}))})),this.incrementIterations()}setLearningRate(e){this.learningRate=e,null!=this.c&&this.c.dispose(),this.c=Qi(no(-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)}}_p.className="SGD",Ki(_p);
+/**
+ * @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 Dp extends _p{constructor(e,t,n=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=no(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const s=Or.registeredVariables[t];if(null==this.accumulations[n]){const e=!1;this.accumulations[n]={originalName:`${t}/momentum`,variable:Zi((()=>Nl(s).variable(e)))}}const r=this.accumulations[n].variable,a=Array.isArray(e)?e[n].tensor:e[t];null!=a&&Zi((()=>{let e;const t=oo(zo(this.m,r),a);e=this.useNesterov?oo(zo(this.c,oo(a,zo(t,this.m))),s):oo(zo(this.c,t),s),r.assign(t),s.assign(e)}))})),this.incrementIterations()}dispose(){this.m.dispose(),null!=this.accumulations&&Ji(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)}}Dp.className="Momentum",Ki(Dp);
+/**
+ * @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 Op extends so{constructor(e,t=.9,n=0,s=null,r=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=s,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=r,null==s&&(this.epsilon=Or.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 s=Or.registeredVariables[t],r=!1;null==this.accumulatedMeanSquares[n]&&(this.accumulatedMeanSquares[n]={originalName:`${t}/rms`,variable:Zi((()=>Nl(s).variable(r)))}),null==this.accumulatedMoments[n]&&(this.accumulatedMoments[n]={originalName:`${t}/momentum`,variable:Zi((()=>Nl(s).variable(r)))}),null==this.accumulatedMeanGrads[n]&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${t}/mg`,variable:Zi((()=>Nl(s).variable(r)))});const a=Array.isArray(e)?e[n].tensor:e[t];if(null==a)return;const i=this.accumulatedMeanSquares[n].variable,o=this.accumulatedMoments[n].variable;Zi((()=>{const e=oo(zo(i,this.decay),zo(Vl(a),1-this.decay));if(this.centered){const t=this.accumulatedMeanGrads[n].variable,r=oo(zo(t,this.decay),zo(a,1-this.decay)),l=vl(zo(a,this.learningRate),Wl(gu(e,oo(Vl(r),this.epsilon)))),u=oo(zo(o,this.momentum),l);i.assign(e),t.assign(r),o.assign(u);const c=gu(s,u);s.assign(c)}else{const e=oo(zo(i,this.decay),zo(Vl(a),1-this.decay)),t=oo(zo(o,this.momentum),vl(zo(a,this.learningRate),Wl(oo(e,this.epsilon))));i.assign(e),o.assign(t);const n=gu(s,t);s.assign(n)}}))})),this.incrementIterations()}dispose(){null!=this.accumulatedMeanSquares&&Ji(this.accumulatedMeanSquares.map((e=>e.variable))),null!=this.accumulatedMeanGrads&&this.centered&&Ji(this.accumulatedMeanGrads.map((e=>e.variable))),null!=this.accumulatedMoments&&Ji(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)}}Op.className="RMSProp",Ki(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 Mp{static sgd(e){return new _p(e)}static momentum(e,t,n=!1){return new Dp(e,t,n)}static rmsprop(e,t=.9,n=0,s=null,r=!1){return new Op(e,t,n,s,r)}static adam(e=.001,t=.9,n=.999,s=null){return new Ap(e,t,n,s)}static adadelta(e=.001,t=.95,n=null){return new Ep(e,t,n)}static adamax(e=.002,t=.9,n=.999,s=null,r=0){return new Fp(e,t,n,s,r)}static adagrad(e,t=.1){return new Rp(e,t)}}const Lp={sgd:Mp.sgd,momentum:Mp.momentum,adadelta:Mp.adadelta,adagrad:Mp.adagrad,rmsprop:Mp.rmsprop,adamax:Mp.adamax,adam:Mp.adam},zp="undefined"!=typeof requestAnimationFrame?requestAnimationFrame:"undefined"!=typeof setImmediate?setImmediate:e=>e();function Pp(){return new Promise((e=>zp((()=>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 Bp(e,t){const n=e[0].length;e.forEach(((e,t)=>{O(e.length===n,(()=>`Error in concat${n}D: rank of tensors[${t}] must be the same as the rank of the rest (${n})`))})),O(t>=0&&t`Error in concat${n}D: axis must be between 0 and ${n-1}.`));const s=e[0];e.forEach(((e,r)=>{for(let a=0;a`Error in concat${n}D: Shape of tensors[${r}] (${e}) does not match the shape of the rest (${s}) along the non-concatenated axis ${r}.`))}))}function Wp(e,t){const n=e[0].slice();for(let s=1;s=0)if(o>=0){if(o!==a)throw new Error(`rt input.shape and shape=${t} are incompatible: rt input.shape[${r+e}] = ${a} but shape[${r+e}] = ${o}`)}else s[i]=a}return s}function Gp(e){const t={FIRST_DIM_SIZE:Vp.FIRST_DIM_SIZE,VALUE_ROWIDS:Vp.VALUE_ROWIDS,ROW_LENGTHS:Vp.ROW_LENGTHS,ROW_SPLITS:Vp.ROW_SPLITS,ROW_LIMITS:Vp.ROW_LIMITS,ROW_STARTS:Vp.ROW_STARTS},n=[];for(const s of e){if(!(s in t))break;n.push(t[s])}return n}function Hp(e){return 0===e.length?0:e[0]===Vp.FIRST_DIM_SIZE?e.length-1:e.length}function jp(e,t){if(null==e||null==t)return;const n=e.length,s=t.length;if(n>=s)throw new Error(`defaultValue.shape=${e} and ragged tensor flatValues.shape=${t}, are incompatible: defaultValue.rank = ${n} must be less than ragged tensor input flatValues.rank = ${s})`);for(let r=0;r=0&&s>=0&&1!==n&&n!==s)throw new Error(`defaultValue.shape=${e}, and ragged tensor input flatValues.shape=${t} are incompatible: defaultValue.shape[${r-e.length}] = ${n} but ragged tensor input.flatValues.shape[${r-e.length}] = ${s}`)}}!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"}(Vp||(Vp={}));
+/**
+ * @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 qp=30;function Kp(e){return e<=qp?e:se(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 Xp(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 Yp(e,t,n,s=!0){let r=[];if(s)r=r.concat(t.slice(0)),r.push(e[0]/n),r=r.concat(e.slice(1));else{r=r.concat(e[0]);const n=t.length;for(let s=0;s=2*t+1||s%2==1?r.push(s):n.push(s);s.push(...n),s.push(0),s.push(...r)}return s}function Jp(e,t,n,s=!0){const r=[];s?r.push(e[0]/n):r.push(e[0]*n);for(let n=1;nn)throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${t.shape[s-1]} vs. ${n}`);if(0===P(e.shape))throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);const r=t.shape,a=r[r.length-1];let i=1;for(let e=0;ee/u)),1].slice(0,a);return[l,i,u,c]}
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+const nd=1.7580993408473768,sd=1.0507009873554805,rd=.3275911,ad=.254829592,id=-.284496736,od=1.421413741,ld=-1.453152027,ud=1.061405429;
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function cd(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);const n=new Float32Array(2*e.length);for(let s=0;s/g,wd=",",vd="...";function kd(e,t){const n=((e=e.replace(/\s/g,"")).length-e.replace(xd,"").length)/bd.length;if(n<1)throw new Error("Equations without an arrow are not supported.");if(n>1)throw new Error(`Equation must contain exactly one arrow ("${bd}").`);const[s,r]=e.split(bd);O(-1===s.indexOf(vd),(()=>`The ellipsis notation ("${vd}") is not supported yet.`));const a=s.split(wd),i=a.length;if(t!==i)throw new Error(`Expected ${i} input tensors, received ${t}`);if(i>2)throw new Error("Support for more than 2 input tensors is not implemented yet.");const o=[];for(let e=0;e-1!==e.indexOf(t))))throw new Error(`Output subscripts contain the label ${t} not present in the input subscripts.`);-1===o.indexOf(t)&&o.push(t)}for(let e=0;e-1!==e)),{permutationIndices:n,expandDims:s}}function Nd(e,t,n){const s=new Array(e);for(let e=0;e`Expected dimension ${s[t[e][n]]} at axis ${n} of input shaped ${JSON.stringify(r)}, but got dimension ${r[n]}`))}}function Sd(e,t){const n=e,s=[];let r=0;0===e.length&&n.push(-1),r=e.length+1;for(let e=0;ee===t))}function Cd(e,t){const n=[];for(let s=0;s"Number of splits must evenly divide the axis.")),s=new Array(t).fill(e.shape[n]/t);else{const r=t.reduce(((e,t)=>(-1===t&&(e+=1),e)),0);O(r<=1,(()=>"There should be only one negative value in split array."));const a=t.indexOf(-1);if(-1!==a){const s=t.reduce(((e,t)=>t>0?e+t:e));t[a]=e.shape[n]-s}O(e.shape[n]===t.reduce(((e,t)=>e+t)),(()=>"The sum of sizes must match the size of the axis dimension.")),s=t}return s}
+/**
+ * @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 Ed(e){return`Received SparseTensor with denseShape[0] = 0 but\n indices.shape[0] = ${e}`}function Rd(e,t){return`indices(${e}, 0) is invalid: ${t} < 0`}function Ad(e,t,n){return`indices(${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 Fd(e,t){return`only one output dimension may be -1, not both ${e} and ${t}`}function _d(e,t){return`size ${e} must be non-negative, not ${t}`}function Dd(){return"reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero"}function Od(e,t){return`Input to reshape is a SparseTensor with ${P(e)}\n dense values, but the requested shape requires a multiple of ${P(t)}. inputShape=${e} outputShape= ${t}`}function Md(e,t){return`Input to reshape is a tensor with ${P(e)} dense values, but the requested shape has ${P(t)}. inputShape=${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 Ld(){return"segment ids must be >= 0"}function zd(){return"segment ids are not increasing"}function Pd(e,t){return`Segment id ${e} out of range [0, ${t}), possibly because segmentIds input is not sorted.`}function Bd(e,t,n){return`Bad: indices[${e}] == ${t} out of range [0, ${n})`}
+/**
+ * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function Wd(e,t){let n,s=!1;for(e<=qp?(n=e,s=!0):n=se(e,Math.floor(Math.sqrt(e)));!s;)n>t||n===e?s=!0:n=se(e,n+1);return n}function Vd(e,t,n){const s=[],r=e.length;for(let a=0;ar))throw new Error(`Expect batchDims in the range of [-${r}, ${r}], but got ${s}`);if(s<0&&(s+=r),s>a)throw new Error(`batchDims (${s}) must be less than rank(x) (\n ${a}).`);if(nsr(e)))}catch(e){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${e}`)}}function Hd(e){return e.map((e=>nr(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.
+ * =============================================================================
+ */
+const jd={kernelName:ke,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(e,Wc(Za(n,"float32"),-1))}}},qd={kernelName:Ie,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>{const t=Vl(Za(n,"float32")),s=Wl(gu(no(1),t));return du(vl(e,s))}}}},Kd={kernelName:Ne,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>{const t=Wl(gu(Vl(Za(n,"float32")),1));return vl(e,t)}}}},Xd={kernelName:Se,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t,r=ki(n.shape,s.shape);return{a:()=>{let t=e;const s=vi(n.shape,r);return s.length>0&&(t=Ul(t,s)),_o(t,n.shape)},b:()=>{let t=e;const n=vi(s.shape,r);return n.length>0&&(t=Ul(t,n)),_o(t,s.shape)}}}},Yd={kernelName:Te,saveAllInputs:!0,gradFunc:(e,t)=>{const n={};return t.forEach(((t,s)=>{n[s]=()=>e.clone()})),n}},Zd={kernelName:Ee,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>Nl(n)}}},Jd={kernelName:Re,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>Nl(n)}}},Qd={kernelName:Ae,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,Wl(gu(no(1),Vl(Za(n,"float32")))))}}},ef={kernelName:Fe,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>{const t=Wl(oo(no(1),Vl(Za(n,"float32"))));return vl(e,t)}}}},tf={kernelName:Oe,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t,r=ki(n.shape,s.shape);return{a:()=>{const t=oo(Vl(n),Vl(s));let a=zo(e,vl(s,t));const i=vi(n.shape,r);return i.length>0&&(a=Ul(a,i)),_o(a,n.shape)},b:()=>{const t=oo(Vl(n),Vl(s));let a=du(zo(e,vl(n,t)));const i=vi(s.shape,r);return i.length>0&&(a=Ul(a,i)),_o(a,s.shape)}}}},nf={kernelName:_e,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,oo(Vl(Za(n,"float32")),1))}}},sf={kernelName:De,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,gu(no(1),Vl(Za(n,"float32"))))}}};const rf=qr({avgPool3dGrad_:
+/**
+ * @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,s,r,a){const i=Gr(e,"dy","avgPool3dGrad"),o=Gr(t,"input","avgPool3dGrad");let l=i,u=o,c=!1;4===o.rank&&(c=!0,l=_o(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]]),u=_o(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),O(5===l.rank,(()=>`Error in avgPool3dGrad: dy must be rank 5 but got rank ${l.rank}.`)),O(5===u.rank,(()=>`Error in avgPool3dGrad: input must be rank 5 but got rank ${u.rank}.`)),Fo("avgPool3dGrad",r,a);const h={dy:l,input:u},p={filterSize:n,strides:s,pad:r,dimRoundingMode:a},d=Or.runKernel(Pe,h,p);return c?_o(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}}),af={kernelName:ze,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{filterSize:r,strides:a,pad:i,dimRoundingMode:o}=n;return{x:()=>rf(e,s,r,a,i,o)}}};const of=qr({avgPoolGrad_:
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t,n,s,r){const a=Gr(e,"dy","avgPoolGrad"),i=Gr(t,"input","avgPoolGrad");O(i.rank===a.rank,(()=>`Rank of input (${i.rank}) does not match rank of dy (${a.rank})`));let o=i,l=a,u=!1;3===i.rank&&(u=!0,o=_o(i,[1,i.shape[0],i.shape[1],i.shape[2]]),l=_o(a,[1,a.shape[0],a.shape[1],a.shape[2]])),O(4===l.rank,(()=>`Error in avgPoolGrad: dy must be rank 4 but got rank ${l.rank}.`)),O(4===o.rank,(()=>`Error in avgPoolGrad: input must be rank 4 but got rank ${o.rank}.`));const c={dy:l,input:o},h={filterSize:n,strides:s,pad:r},p=Or.runKernel(Le,c,h);return u?_o(p,[p.shape[1],p.shape[2],p.shape[3]]):p}}),lf={kernelName:Me,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{filterSize:r,strides:a,pad:i}=n;return{x:()=>of(e,s,r,a,i)}}},uf={kernelName:Be,inputsToSave:["a","b"],gradFunc:(e,t,n)=>{const[s,r]=t,{transposeA:a,transposeB:i}=n;return a||i?!a&&i?{a:()=>Lo(e,r,!1,!1),b:()=>Lo(e,s,!0,!1)}:a&&!i?{a:()=>Lo(r,e,!1,!0),b:()=>Lo(s,e,!1,!1)}:{a:()=>Lo(r,e,!0,!0),b:()=>Lo(e,s,!0,!0)}:{a:()=>Lo(e,r,!1,!0),b:()=>Lo(s,e,!0,!1)}}},cf={kernelName:We,gradFunc:(e,t,n)=>{const{blockShape:s,crops:r}=n;return{x:()=>Xu(e,s,r)}}},hf={kernelName:"BroadcastTo",gradFunc:(e,t,n)=>{const s=n,r=s.inputShape,a=s.shape,i=Array.from(a);for(let e=r.length-1;e>=0;e--)if(r[e]===a[e])i[e]=1;else if(1!==r[e])throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${a}].`);const o=[];for(let e=0;e1&&o.push(e);return{x:()=>Ul(e,o,!0)}}},pf={kernelName:Ge,gradFunc:e=>({x:()=>e.clone()})},df={kernelName:He,gradFunc:e=>({x:()=>Nl(e)})},ff={kernelName:je,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{clipValueMin:r,clipValueMax:a}=n;return{x:()=>Il(xu(tu(s,r),lu(s,a)),e,Nl(e))}}},mf={kernelName:Ke,inputsToSave:["x"],gradFunc:jd.gradFunc},gf={kernelName:Xe,saveAllInputs:!0,gradFunc:(e,t,n)=>{const s=t.map((e=>e.shape)),{axis:r}=n,a=j(r,t[0].shape)[0],i=s.map((e=>e[a]));return Mc(e,i,a).map((e=>()=>e))}},yf={kernelName:Ye,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{const[s,r]=t,{dilations:a,strides:i,pad:o,dataFormat:l}=n;return O(Eo(a),(()=>`Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`)),{x:()=>il(s.shape,e,r,i,o,l),filter:()=>yh(s,e,r.shape,i,o,l)}}},bf={kernelName:Je,inputsToSave:["dy","filter"],gradFunc:(e,t,n)=>{const[s,r]=t,{strides:a,pad:i,dataFormat:o,dimRoundingMode:l}=n;return{dy:()=>rl(e,r,a,i,o,1,l),filter:()=>yh(e,s,r.shape,a,i,o,l)}}};const xf=qr({conv3DBackpropFilter_:
+/**
+ * @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,s,r){let a=e;4===e.rank&&(a=_o(e,[1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]]));let i=t;4===i.rank&&(i=_o(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]])),O(5===a.rank,(()=>`Error in conv3dDerFilter: input must be rank 5, but got shape ${a.shape}.`)),O(5===i.rank,(()=>`Error in conv3dDerFilter: dy must be rank 5, but got shape ${i.shape}.`)),O(5===n.length,(()=>`Error in conv3dDerFilter: filterShape must be length 5, but got ${n}.`)),O(a.shape[4]===n[3],(()=>`Error in conv3dDerFilter: depth of input ${a.shape[4]}) must match input depth in filter (${n[3]}.`)),O(i.shape[4]===n[4],(()=>`Error in conv3dDerFilter: depth of dy (${i.shape[4]}) must match output depth for filter (${n[4]}).`));const o={x:a,dy:i},l={strides:s,pad:r,filterShape:n};return Or.runKernel(et,o,l)}}),wf={kernelName:Qe,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{const{dilations:s,strides:r,pad:a}=n;O(Eo(s),(()=>`Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`));const[i,o]=t;return{x:()=>ul(i.shape,e,o,r,a),filter:()=>xf(i,e,o.shape,r,a)}}},vf={kernelName:nt,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(du(Tc(Za(n,"float32"))),e)}}},kf={kernelName:st,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(Cc(Za(n,"float32")),e)}}},If={kernelName:at,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{axis:r,exclusive:a,reverse:i}=n;return{x:()=>{const t=Ol([r],s.rank);let n=fl(e,r,a,!i);return null!=t&&(n=ah(n,t)),n}}}},Nf={kernelName:ut,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{const{dilations:s,strides:r,pad:a,dimRoundingMode:i}=n,o=null==s?[1,1]:s;O(Eo(o),(()=>`Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${o}'`));const[l,u]=t;return O(4===l.rank,(()=>`Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${l.rank}.`)),O(4===u.rank,(()=>`Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${u.rank}.`)),O(l.shape[3]===u.shape[2],(()=>`Error in gradient of depthwiseConv2d: number of input channels (${l.shape[3]}) must match the inChannels dimension in filter ${u.shape[2]}.`)),O(Ro(r,o),(()=>`Error in gradient of depthwiseConv2d: Either strides or dilations must be 1. Got strides ${r} and dilations '${o}'.`)),Fo("depthwiseConv2d",a,i),{x:()=>Nh(l.shape,e,u,r,a,o,i),filter:()=>Ih(l,e,u.shape,r,a,o,i)}}},Sf={kernelName:dt,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{const[s,r]=t,a={x:s,filter:r,dy:e},i={x:s,filter:r,dy:e};return{x:()=>Or.runKernel(ft,a,n),filter:()=>Or.runKernel(mt,i,n)}}},Tf={kernelName:bt,outputsToSave:[!0],gradFunc:(e,t)=>{const[n]=t,s={dy:e,y:n};return{x:()=>Or.runKernel(xt,s)}}},Cf={kernelName:wt,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t,s=zo(ql(du(Vl(n))),2/Math.sqrt(Math.PI));return{x:()=>zo(e,s)}}},$f={kernelName:kt,outputsToSave:[!0],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(e,n)}}},Ef={kernelName:It,inputsToSave:["input"],gradFunc:(e,t)=>{const[n]=t;return{input:()=>_o(e,n.shape)}}},Rf={kernelName:Nt,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(e,ql(n))}}},Af={kernelName:$t,gradFunc:e=>({x:()=>Nl(e)})},Ff={kernelName:Et,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t,r=ki(n.shape,s.shape);return{a:()=>{const t=vl(e,Za(s,"float32")),a=vi(n.shape,r);return a.length>0?_o(Ul(t,a),n.shape):t},b:()=>{let t=zo(e,Za(n,"float32"));const a=vi(s.shape,r);a.length>0&&(t=_o(Ul(t,a),s.shape));const i=Vl(s);return du(vl(t,Za(i,"float32")))}}}},_f={kernelName:Rt,inputsToSave:["x","mean","variance","scale"],gradFunc:(e,t,n)=>{const{varianceEpsilon:s}=n,[r,a,i,o]=t,l=null==o?no(1):o,u=vi(a.shape,r.shape),c=[];if(1===a.rank){for(let e=0;e1===a.rank?_o(zo(zo(e,Yl(_o(d,[1,1,1,a.shape[0]]),c)),l),r.shape):_o(zo(zo(e,d),l),r.shape),mean:()=>{let e=zo(zo(d,no(-1)),p);return 1===a.rank&&(e=Ul(e,u)),_o(e,a.shape)},variance:()=>{let e=zo(zo(f,h),p);return 1===a.rank&&(e=Ul(e,u)),_o(e,a.shape)},scale:()=>{const t=zo(h,d);let n=zo(e,t);return 1===a.rank&&(n=Ul(n,u)),_o(n,a.shape)},offset:()=>{let t=e;return 1===a.rank&&(t=Ul(t,u)),_o(t,a.shape)}}}},Df={kernelName:At,inputsToSave:["x","indices"],gradFunc:(e,t,n)=>{const[s,r]=t,{axis:a}=n,i=j(a,s.shape)[0];return{x:()=>{const t=s.shape,n=r.size,o=t.slice(0,i),l=o.length,u=t.slice(a,t.length).slice(1),c=u.length,h=Of(0,l),p=Of(l+1,l+1+c),d=Mf([o,[n],u]),f=_o(e,d),m=_o(r,[n]),g=Mf([[l],h,p]),y=ah(f,g);let b=Jc(y,m,s.shape[i]);const x=Ml(g);return b=ah(b,x),b},indices:()=>r}}};function Of(e,t){const n=[];for(let s=e;s{const[n,s]=t;return{a:()=>Nl(n),b:()=>Nl(s)}}},zf={kernelName:Ot,gradFunc:e=>({x:()=>Za(e,"float32")})},Pf={kernelName:zt,gradFunc:e=>({x:()=>Nl(e)})},Bf={kernelName:Pt,gradFunc:e=>({x:()=>Nl(e)})},Wf={kernelName:Bt,gradFunc:e=>({x:()=>Nl(e)})},Vf={kernelName:Wt,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{alpha:r}=n,a=eu(s,0);return{x:()=>Il(a,e,zo(e,r))}}},Uf={kernelName:jt,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,oo(n,1))}}},Gf={kernelName:Ht,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,Za(n,"float32"))}}},Hf={kernelName:"LogSoftmax",inputsToSave:[],outputsToSave:[!0],gradFunc:(e,t,n)=>{const[s]=t,{axis:r}=n;return{logits:()=>{const t=ql(s);return gu(e,zo(Ul(e,r,!0),t))}}}};const jf=qr({localResponseNormalizationBackprop_:
+/**
+ * @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,s=5,r=1,a=1,i=.5){const o={x:e,y:t,dy:n},l={depthRadius:s,bias:r,alpha:a,beta:i};return Or.runKernel(Zt,o,l)}}),qf={kernelName:Yt,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{const[s,r]=t,{depthRadius:a,bias:i,alpha:o,beta:l}=n;return{x:()=>jf(s,r,e,a,i,o,l)}}};
+/**
+ * @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 Kf(e,t,n,s){return t.rankzo(e,Za(kl(n,t),e.dtype))}}
+/**
+ * @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.
+ * =============================================================================
+ */
+const Xf={kernelName:Jt,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{const s=n,{reductionIndices:r}=s,a=t[0],i=Kf(e,t[1],a,j(r,a.shape));return{x:()=>i.x()}}},Yf={kernelName:Qt,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t;return{a:()=>zo(e,Za(tu(n,s),"float32")),b:()=>zo(e,Za(ou(n,s),"float32"))}}};const Zf=qr({maxPool3dGrad_:
+/**
+ * @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,s,r,a,i){const o=Gr(e,"dy","maxPool3dGrad"),l=Gr(t,"input","maxPool3dGrad"),u=Gr(n,"output","maxPool3dGrad");let c=o,h=l,p=u,d=!1;4===l.rank&&(d=!0,c=_o(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]]),h=_o(l,[1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]]),p=_o(u,[1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]])),O(5===c.rank,(()=>`Error in maxPool3dGrad: dy must be rank 5 but got rank ${c.rank}.`)),O(5===h.rank,(()=>`Error in maxPool3dGrad: input must be rank 5 but got rank ${h.rank}.`)),O(5===p.rank,(()=>`Error in maxPool3dGrad: output must be rank 5 but got rank ${p.rank}.`)),Fo("maxPool3dGrad",a,i);const f={dy:c,input:h,output:p},m={filterSize:s,strides:r,pad:a,dimRoundingMode:i},g=Or.runKernel(sn,f,m);return d?_o(g,[g.shape[1],g.shape[2],g.shape[3],g.shape[4]]):g}}),Jf={kernelName:nn,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{const[s,r]=t,{filterSize:a,strides:i,pad:o,dimRoundingMode:l}=n;return{x:()=>Zf(e,s,r,a,i,o,l)}}};const Qf=qr({maxPoolGrad_:
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function(e,t,n,s,r,a,i){const o=Gr(e,"dy","maxPoolGrad"),l=Gr(t,"input","maxPoolGrad"),u=Gr(n,"output","maxPoolGrad");O(l.rank===o.rank,(()=>`Rank of input (${l.rank}) does not match rank of dy (${o.rank})`)),O(4===o.rank,(()=>`Error in maxPoolGrad: dy must be rank 4 but got rank ${o.rank}.`)),O(4===l.rank,(()=>`Error in maxPoolGrad: input must be rank 4 but got rank ${l.rank}.`)),Fo("maxPoolGrad",a,i);const c={dy:o,input:l,output:u},h={filterSize:s,strides:r,pad:a,dimRoundingMode:i};return Or.runKernel(tn,c,h)}}),em={kernelName:en,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{const[s,r]=t,{filterSize:a,strides:i,pad:o}=n;return{x:()=>Qf(e,s,r,a,i,o)}}},tm={kernelName:an,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{axis:r}=n,a=j(r,s.shape),i=P(Fl(s.shape,a)[1]);return{x:()=>{const t=s.shape.slice();a.forEach((e=>{t[e]=1}));const n=_o(e,t);return vl(zo(n,Fu(s.shape,"float32")),i)}}}},nm={kernelName:on,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{const s=n,{axis:r}=s,[a,i]=t,o=Kf(e,i,a,j(r,a.shape));return{x:()=>o.x()}}},sm={kernelName:un,inputsToSave:["x"],gradFunc:(e,t,n)=>{const s=t[0],{paddings:r}=n,a=r.map((e=>e[0]));return{x:()=>Bo(e,a,s.shape)}}},rm={kernelName:wn,saveAllInputs:!0,gradFunc:(e,t,n)=>{const{axis:s}=n;return Qc(e,s).map((e=>()=>e))}},am={kernelName:vn,inputsToSave:["x"],gradFunc:(e,t,n)=>{const s=t[0],{paddings:r}=n,a=r.map((e=>e[0]));return{x:()=>Bo(e,a,s.shape)}}},im={kernelName:kn,inputsToSave:["a","b"],outputsToSave:[!0],gradFunc:(e,t)=>{const[n,s,r]=t,a=n,i=s,o=ki(a.shape,i.shape);return{a:()=>{const t=Za(i,"float32");let n=zo(e,zo(t,Bl(a,gu(t,no(1)))));const s=vi(a.shape,o);return s.length>0&&(n=Ul(n,s)),_o(n,a.shape)},b:()=>{const t=eu(a,0),n=Il(t,hu(a),Nl(a));let s=zo(e,zo(r,n));const l=vi(i.shape,o);return l.length>0&&(s=Ul(s,l)),_o(s,i.shape)}}}},om={kernelName:In,inputsToSave:["x","alpha"],gradFunc:(e,t)=>{const[n,s]=t,r=eu(n,0);return{x:()=>Il(r,e,zo(e,s)),alpha:()=>{let t=Il(r,Nl(e),zo(e,n));const a=vi(s.shape,e.shape);return a.length>0&&(t=Ul(t,a)),_o(t,s.shape)}}}};function lm(e,t,n){const s=e.shape.length,r=s-n.length,a=Ol(n,s);let i=e;null!=a&&(i=ah(e,a));const o=i.shape.slice(),l=o.splice(s-n.length,n.length).reduce(((e,t)=>e*t),1);o.push(l);let u=
+/**
+ * @license
+ * Copyright 2022 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,n){const s=e.shape.slice();s[n]=1;const r=_o(t,s),a=dl(e,n,!0,!1),i=dl(e,n,!0,!0),o=zo(a,i);return zo(r,o)}(i.reshape(o),t,r);if(u=u.reshape(i.shape),null!=a){const e=Ml(a);u=ah(u,e)}return u}const um={kernelName:Nn,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{axis:r}=n;let a=[];return a=null==r?s.shape.map(((e,t)=>t)):"number"==typeof r?[r]:r,{x:()=>lm(s,e,a)}}},cm={kernelName:En,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,du(Vl(n)))}}},hm={kernelName:Mn,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t,s=zo(lu(n,6),Wc(n));return{x:()=>zo(e,Za(s,"float32"))}}},pm={kernelName:Rn,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(e,Za(Wc(n),"float32"))}}},dm={kernelName:An,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>_o(e,n.shape)}}},fm={kernelName:Pn,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>du(vl(e,zo(Bl(n,1.5),2)))}}},mm={kernelName:Un,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>{const t=eu(n,no(0)),s=no(nd),r=no(sd),a=zo(e,r),i=zo(zo(e,s),ql(Za(n,"float32")));return Il(t,a,i)}}}},gm={kernelName:Hn,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(hl(Za(n,"float32")),e)}}},ym={kernelName:jn,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(pl(Za(n,"float32")),e)}}},bm={kernelName:Gn,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{begin:r,size:a}=n,i=s.shape,[o,l]=Ui(s,r,a),u=[];for(let t=0;tGu(e,u)}}},xm={kernelName:Xn,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(e,Po(n))}}},wm={kernelName:Jn,gradFunc:(e,t,n)=>{const{blockShape:s,paddings:r}=n;return{x:()=>Uo(e,s,r)}}},vm={kernelName:Qn,gradFunc:(e,t,n)=>{const{axis:s}=n;return{x:()=>Mo(e,s)}}},km={kernelName:Yn,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,zo(Wl(Za(n,"float32")),2))}}},Im={kernelName:os,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(e,zo(Za(n,"float32"),2))}}},Nm={kernelName:Zn,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,r=s.shape.slice(),{axis:a}=n;j(a,s.shape).forEach((e=>{r[e]=1}));const i=_o(e,r),o=zo(i,Fu(s.shape,"float32"));return{x:()=>o}}},Sm={kernelName:ds,inputsToSave:["x"],gradFunc:(e,t)=>{const[n]=t;return{x:()=>vl(e,Vl(hl(n)))}}},Tm={kernelName:ms,inputsToSave:["x"],gradFunc:(e,t,n)=>{const[s]=t,{reps:r}=n;return{x:()=>{let t=Nl(s);if(1===s.rank)for(let n=0;n{const[n]=t;return{x:()=>function(e,t){const n=Eu(t,Nl(t)),s=Ql(e,n);let r=tu(t,no(0,"int32"));const a=s.rank-r.rank;for(let e=0;e{const[n,s]=t,r=ki(n.shape,s.shape);return{a:()=>{const t=vl(e,Za(s,"float32")),a=vi(n.shape,r);return a.length>0?_o(Ul(t,a),n.shape):t},b:()=>{let t=zo(e,Za(n,"float32"));const a=vi(s.shape,r);a.length>0&&(t=_o(Ul(t,a),s.shape));const i=Vl(s);return du(vl(t,Za(i,"float32")))}}}},Tf,Cf,$f,Ef,Rf,Ff,Af,_f,Df,Lf,zf,Pf,Bf,Wf,Vf,Uf,Gf,Hf,qf,Xf,Xf,Yf,Jf,em,tm,nm,{kernelName:ln,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t;return{a:()=>zo(e,Za(lu(n,s),"float32")),b:()=>zo(e,Za(eu(n,s),"float32"))}}},sm,{kernelName:cn,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t,r=ki(n.shape,s.shape);return{a:()=>{const t=vi(n.shape,r);return t.length>0?_o(Ul(e,t),n.shape):e},b:()=>{const t=zo(e,du(Jl(vl(n,s)))),a=vi(s.shape,r);return a.length>0?_o(Ul(t,a),s.shape):t}}}},{kernelName:pn,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t,r=ki(n.shape,s.shape);return{a:()=>{const t=zo(e,Za(s,"float32")),a=vi(n.shape,r);return a.length>0?_o(Ul(t,a),n.shape):t},b:()=>{const t=zo(e,Za(n,"float32")),a=vi(s.shape,r);return a.length>0?_o(Ul(t,a),s.shape):t}}}},{kernelName:dn,gradFunc:e=>({x:()=>du(e)})},{kernelName:xn,inputsToSave:["indices"],gradFunc:(e,t)=>{const n=t[0];return{indices:()=>Au(n.shape,"float32")}}},{kernelName:bn,gradFunc:e=>({x:()=>Nl(e)})},rm,am,am,im,om,um,cm,hm,pm,dm,{kernelName:Dn,inputsToSave:["images"],gradFunc:(e,t,n)=>{const[s]=t,r={dy:e,images:s};return{images:()=>Or.runKernel(On,r,n)}}},{kernelName:Fn,inputsToSave:["images"],gradFunc:(e,t,n)=>{const[s]=t,r={dy:e,images:s};return{images:()=>Or.runKernel(_n,r,n)}}},{kernelName:Ln,gradFunc:(e,t,n)=>{const{dims:s}=n,r=j(s,e.shape);return{x:()=>mc(e,r)}}},{kernelName:zn,gradFunc:e=>({x:()=>Nl(e)})},fm,{kernelName:Vn,inputsToSave:["condition"],gradFunc:(e,t)=>{const[n]=t;return{condition:()=>Za(Nl(n),"float32"),t:()=>zo(e,Za(n,e.dtype)),e:()=>zo(e,Za(wu(n),e.dtype))}}},mm,{kernelName:Kn,outputsToSave:[!0],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(e,zo(n,gu(no(1),n)))}}},{kernelName:qn,gradFunc:e=>({x:()=>Nl(e)})},gm,ym,bm,{kernelName:es,outputsToSave:[!0],gradFunc:(e,t,n)=>{const[s]=t,{dim:r}=n,a=zo(e,s);return{logits:()=>gu(a,zo(Ul(a,[r],true),s))}}},xm,wm,wm,vm,vm,km,{kernelName:is,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t,r=no(2);return{a:()=>zo(e,zo(r,gu(n,s))),b:()=>zo(e,zo(r,gu(s,n)))}}},Im,{kernelName:Is,gradFunc:e=>({x:()=>Nl(e)})},{kernelName:ps,inputsToSave:["a","b"],gradFunc:(e,t)=>{const[n,s]=t,r=ki(n.shape,s.shape);return{a:()=>{let t=e;const s=vi(n.shape,r);return s.length>0&&(t=Ul(t,s)),_o(t,n.shape)},b:()=>{let t=e;const n=vi(s.shape,r);return n.length>0&&(t=Ul(t,n)),_o(du(t),s.shape)}}}},Nm,Sm,{kernelName:fs,outputsToSave:[!0],gradFunc:(e,t)=>{const[n]=t;return{x:()=>zo(gu(no(1),Vl(n)),e)}}},Tm,{kernelName:bs,gradFunc:(e,t,n)=>{const s=n,{perm:r}=s,a=Ml(r);return{x:()=>ah(e,a)}}},{kernelName:ws,gradFunc:(e,t,n)=>{const s=n,{axis:r}=s;return{value:()=>Bc(e,r)}}},Cm,{kernelName:ks,gradFunc:e=>({x:()=>Nl(e)})}];for(const e of $m)Ls(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.
+ * =============================================================================
+ */
+yr().prototype.abs=function(){return this.throwIfDisposed(),ro(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.acos=function(){return this.throwIfDisposed(),ao(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.acosh=function(){return this.throwIfDisposed(),io(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.add=function(e){return this.throwIfDisposed(),oo(this,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.
+ * =============================================================================
+ */
+yr().prototype.all=function(e,t){return this.throwIfDisposed(),uo(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.any=function(e,t){return this.throwIfDisposed(),co(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.argMax=function(e){return this.throwIfDisposed(),ho(this,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.
+ * =============================================================================
+ */
+yr().prototype.argMin=function(e){return this.throwIfDisposed(),po(this,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.
+ * =============================================================================
+ */
+yr().prototype.asScalar=function(){return this.throwIfDisposed(),O(1===this.size,(()=>"The array must have only 1 element.")),_o(this,[])},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.asType=function(e){return this.throwIfDisposed(),Za(this,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.
+ * =============================================================================
+ */
+yr().prototype.as1D=function(){return this.throwIfDisposed(),_o(this,[this.size])},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.as2D=function(e,t){return this.throwIfDisposed(),_o(this,[e,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.
+ * =============================================================================
+ */
+yr().prototype.as3D=function(e,t,n){return this.throwIfDisposed(),_o(this,[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.
+ * =============================================================================
+ */
+yr().prototype.as4D=function(e,t,n,s){return this.throwIfDisposed(),_o(this,[e,t,n,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.
+ * =============================================================================
+ */
+yr().prototype.as5D=function(e,t,n,s,r){return this.throwIfDisposed(),_o(this,[e,t,n,s,r])},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.asin=function(){return this.throwIfDisposed(),fo(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.asinh=function(){return this.throwIfDisposed(),mo(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.atan=function(){return this.throwIfDisposed(),go(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.atan2=function(e){return this.throwIfDisposed(),yo(this,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.
+ * =============================================================================
+ */
+yr().prototype.atanh=function(){return this.throwIfDisposed(),bo(this)},yr().prototype.avgPool=function(e,t,n,s){return this.throwIfDisposed(),Do(this,e,t,n,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.
+ * =============================================================================
+ */
+yr().prototype.batchToSpaceND=function(e,t){return this.throwIfDisposed(),Uo(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.batchNorm=function(e,t,n,s,r){return this.throwIfDisposed(),Go(this,e,t,n,s,r)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.broadcastTo=function(e){return this.throwIfDisposed(),Yo(this,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.
+ * =============================================================================
+ */
+yr().prototype.cast=function(e){return this.throwIfDisposed(),Za(this,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.
+ * =============================================================================
+ */
+yr().prototype.ceil=function(){return this.throwIfDisposed(),Zo(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.clipByValue=function(e,t){return this.throwIfDisposed(),Qo(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.concat=function(e,t){return this.throwIfDisposed(),e instanceof gr&&(e=[e]),Mo([this,...e],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.
+ * =============================================================================
+ */
+yr().prototype.conv1d=function(e,t,n,s,r,a){return this.throwIfDisposed(),al(this,e,t,n,s,r,a)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.conv2dTranspose=function(e,t,n,s,r){return this.throwIfDisposed(),ol(this,e,t,n,s,r)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.conv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),rl(this,e,t,n,s,r,a)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.cos=function(){return this.throwIfDisposed(),hl(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.cosh=function(){return this.throwIfDisposed(),pl(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.cumprod=function(e,t,n){return this.throwIfDisposed(),dl(this,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.
+ * =============================================================================
+ */
+yr().prototype.cumsum=function(e,t,n){return this.throwIfDisposed(),fl(this,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.
+ * =============================================================================
+ */
+yr().prototype.depthToSpace=function(e,t){return this.throwIfDisposed(),gl(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.depthwiseConv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),yl(this,e,t,n,s,r,a)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.dilation2d=function(e,t,n,s,r){return this.throwIfDisposed(),xl(this,e,t,n,s,r)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.divNoNan=function(e){return this.throwIfDisposed(),Sl(this,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.
+ * =============================================================================
+ */
+yr().prototype.div=function(e){return this.throwIfDisposed(),vl(this,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.
+ * =============================================================================
+ */
+yr().prototype.dot=function(e){return this.throwIfDisposed(),Tl(this,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.
+ * =============================================================================
+ */
+yr().prototype.elu=function(){return this.throwIfDisposed(),$l(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.equal=function(e){return this.throwIfDisposed(),kl(this,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.
+ * =============================================================================
+ */
+yr().prototype.erf=function(){return this.throwIfDisposed(),El(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.euclideanNorm=function(e,t){return this.throwIfDisposed(),jl(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.exp=function(){return this.throwIfDisposed(),ql(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.expandDims=function(e){return this.throwIfDisposed(),Kl(this,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.
+ * =============================================================================
+ */
+yr().prototype.expm1=function(){return this.throwIfDisposed(),Xl(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.fft=function(){return this.throwIfDisposed(),_c(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.flatten=function(){return this.throwIfDisposed(),_o(this,[this.size])},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.floor=function(){return this.throwIfDisposed(),Jl(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.floorDiv=function(e){return this.throwIfDisposed(),wl(this,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.
+ * =============================================================================
+ */
+yr().prototype.gather=function(e,t){return this.throwIfDisposed(),Ql(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.greaterEqual=function(e){return this.throwIfDisposed(),tu(this,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.
+ * =============================================================================
+ */
+yr().prototype.greater=function(e){return this.throwIfDisposed(),eu(this,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.
+ * =============================================================================
+ */
+yr().prototype.ifft=function(){return this.throwIfDisposed(),Dc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.irfft=function(){return this.throwIfDisposed(),Oc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.isFinite=function(){return this.throwIfDisposed(),su(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.isInf=function(){return this.throwIfDisposed(),ru(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.isNaN=function(){return this.throwIfDisposed(),au(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.leakyRelu=function(e){return this.throwIfDisposed(),iu(this,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.
+ * =============================================================================
+ */
+yr().prototype.lessEqual=function(e){return this.throwIfDisposed(),lu(this,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.
+ * =============================================================================
+ */
+yr().prototype.less=function(e){return this.throwIfDisposed(),ou(this,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.
+ * =============================================================================
+ */
+yr().prototype.localResponseNormalization=function(e,t,n,s){return this.throwIfDisposed(),cu(this,e,t,n,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.
+ * =============================================================================
+ */
+yr().prototype.logSigmoid=function(){return this.throwIfDisposed(),mu(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.logSoftmax=function(e){return this.throwIfDisposed(),yu(this,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.
+ * =============================================================================
+ */
+yr().prototype.logSumExp=function(e,t){return this.throwIfDisposed(),bu(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.log=function(){return this.throwIfDisposed(),hu(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.log1p=function(){return this.throwIfDisposed(),pu(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.logicalAnd=function(e){return this.throwIfDisposed(),xu(this,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.
+ * =============================================================================
+ */
+yr().prototype.logicalNot=function(){return this.throwIfDisposed(),wu(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.logicalOr=function(e){return this.throwIfDisposed(),vu(this,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.
+ * =============================================================================
+ */
+yr().prototype.logicalXor=function(e){return this.throwIfDisposed(),ku(this,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.
+ * =============================================================================
+ */
+yr().prototype.matMul=function(e,t,n){return this.throwIfDisposed(),Lo(this,e,t,n)},yr().prototype.maxPool=function(e,t,n,s){return this.throwIfDisposed(),Tu(this,e,t,n,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.
+ * =============================================================================
+ */
+yr().prototype.max=function(e,t){return this.throwIfDisposed(),zl(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.maximum=function(e){return this.throwIfDisposed(),Eu(this,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.
+ * =============================================================================
+ */
+yr().prototype.mean=function(e,t){return this.throwIfDisposed(),Ru(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.min=function(e,t){return this.throwIfDisposed(),Pl(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.minimum=function(e){return this.throwIfDisposed(),Du(this,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.
+ * =============================================================================
+ */
+yr().prototype.mirrorPad=function(e,t){return this.throwIfDisposed(),Ou(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.mod=function(e){return this.throwIfDisposed(),Mu(this,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.
+ * =============================================================================
+ */
+yr().prototype.mul=function(e){return this.throwIfDisposed(),zo(this,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.
+ * =============================================================================
+ */
+yr().prototype.neg=function(){return this.throwIfDisposed(),du(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.norm=function(e,t,n){return this.throwIfDisposed(),Hl(this,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.
+ * =============================================================================
+ */
+yr().prototype.notEqual=function(e){return this.throwIfDisposed(),Bu(this,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.
+ * =============================================================================
+ */
+yr().prototype.oneHot=function(e,t=1,n=0){return this.throwIfDisposed(),Wu(this,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.
+ * =============================================================================
+ */
+yr().prototype.onesLike=function(){return this.throwIfDisposed(),Vu(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.pad=function(e,t){return this.throwIfDisposed(),Gu(this,e,t)},yr().prototype.pool=function(e,t,n,s,r,a){return this.throwIfDisposed(),Yu(this,e,t,n,s,r,a)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.pow=function(e){return this.throwIfDisposed(),Bl(this,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.
+ * =============================================================================
+ */
+yr().prototype.prelu=function(e){return this.throwIfDisposed(),Zu(this,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.
+ * =============================================================================
+ */
+yr().prototype.prod=function(e,t){return this.throwIfDisposed(),Ju(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.reciprocal=function(){return this.throwIfDisposed(),pc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.relu=function(){return this.throwIfDisposed(),dc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.relu6=function(){return this.throwIfDisposed(),fc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.reshapeAs=function(e){return this.throwIfDisposed(),_o(this,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.
+ * =============================================================================
+ */
+yr().prototype.reshape=function(e){return this.throwIfDisposed(),_o(this,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.
+ * =============================================================================
+ */
+yr().prototype.resizeBilinear=function(e,t,n){return this.throwIfDisposed(),Zh(this,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.
+ * =============================================================================
+ */
+yr().prototype.resizeNearestNeighbor=function(e,t,n){return this.throwIfDisposed(),Jh(this,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.
+ * =============================================================================
+ */
+yr().prototype.reverse=function(e){return this.throwIfDisposed(),mc(this,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.
+ * =============================================================================
+ */
+yr().prototype.rfft=function(){return this.throwIfDisposed(),Lc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.round=function(){return this.throwIfDisposed(),wc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.rsqrt=function(){return this.throwIfDisposed(),vc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.selu=function(){return this.throwIfDisposed(),kc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.separableConv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),Ic(this,e,t,n,s,r,a)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.sigmoid=function(){return this.throwIfDisposed(),Po(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.sign=function(){return this.throwIfDisposed(),Sc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.sin=function(){return this.throwIfDisposed(),Tc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.sinh=function(){return this.throwIfDisposed(),Cc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.slice=function(e,t){return this.throwIfDisposed(),Bo(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.softmax=function(e){return this.throwIfDisposed(),Fc(this,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.
+ * =============================================================================
+ */
+yr().prototype.softplus=function(){return this.throwIfDisposed(),fu(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.spaceToBatchND=function(e,t){return this.throwIfDisposed(),Xu(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.split=function(e,t){return this.throwIfDisposed(),Mc(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.sqrt=function(){return this.throwIfDisposed(),Wl(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.square=function(){return this.throwIfDisposed(),Vl(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.squaredDifference=function(e){return this.throwIfDisposed(),zc(this,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.
+ * =============================================================================
+ */
+yr().prototype.squeeze=function(e){return this.throwIfDisposed(),Pc(this,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.
+ * =============================================================================
+ */
+yr().prototype.stack=function(e,t){this.throwIfDisposed();const n=e instanceof gr?[this,e]:[this,...e];return Bc(n,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.
+ * =============================================================================
+ */
+yr().prototype.step=function(e){return this.throwIfDisposed(),Wc(this,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.
+ * =============================================================================
+ */
+yr().prototype.stridedSlice=function(e,t,n,s,r,a,i,o){return this.throwIfDisposed(),Vc(this,e,t,n,s,r,a,i,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.
+ * =============================================================================
+ */
+yr().prototype.sub=function(e){return this.throwIfDisposed(),gu(this,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.
+ * =============================================================================
+ */
+yr().prototype.sum=function(e,t){return this.throwIfDisposed(),Ul(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.tan=function(){return this.throwIfDisposed(),Uc(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.tanh=function(){return this.throwIfDisposed(),Wo(this)},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.tile=function(e){return this.throwIfDisposed(),Yl(this,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.
+ * =============================================================================
+ */
+yr().prototype.toBool=function(){return this.throwIfDisposed(),Za(this,"bool")},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.toFloat=function(){return this.throwIfDisposed(),Za(this,"float32")},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.toInt=function(){return this.throwIfDisposed(),Za(this,"int32")},
+/**
+ * @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.
+ * =============================================================================
+ */
+yr().prototype.topk=function(e,t){return this.throwIfDisposed(),Xc(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.transpose=function(e){return this.throwIfDisposed(),ah(this,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.
+ * =============================================================================
+ */
+yr().prototype.unique=function(e){return this.throwIfDisposed(),Zc(this,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.
+ * =============================================================================
+ */
+yr().prototype.unsortedSegmentSum=function(e,t){return this.throwIfDisposed(),Jc(this,e,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.
+ * =============================================================================
+ */
+yr().prototype.unstack=function(e){return this.throwIfDisposed(),Qc(this,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.
+ * =============================================================================
+ */
+yr().prototype.where=function(e,t){return this.throwIfDisposed(),Il(e,this,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.
+ * =============================================================================
+ */
+yr().prototype.zerosLike=function(){return this.throwIfDisposed(),Nl(this)};
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class Em extends Error{constructor(e){super(e),Object.setPrototypeOf(this,Em.prototype)}}class Rm extends Error{constructor(e){super(e),Object.setPrototypeOf(this,Rm.prototype)}}class Am extends Error{constructor(e){super(e),Object.setPrototypeOf(this,Am.prototype)}}class Fm extends Error{constructor(e){super(e),Object.setPrototypeOf(this,Fm.prototype)}}class _m extends Error{constructor(e){super(e),Object.setPrototypeOf(this,_m.prototype)}}Error;
+/**
+ * @license
+ * Copyright 2022 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class Dm{constructor(e){this.maxEntries=e||100,this.cache=new Map}get(e){let t;return this.cache.has(e)&&(t=this.cache.get(e),this.cache.delete(e),this.cache.set(e,t)),t}put(e,t){if(this.cache.has(e))this.cache.delete(e);else if(this.cache.size>=this.maxEntries){const e=this.cache.keys().next().value;this.cache.delete(e)}this.cache.set(e,t)}getMaxEntries(){return this.maxEntries}setMaxEntries(e){if(e<0)throw new Error(`The maxEntries of LRU caches must be at least 0, but got ${e}.`);if(this.maxEntries>e)for(let t=0;tt.toUpperCase()))}let Vm={};function Um(e){if(null==e)return null;const t={};return t.className=e.getClassName(),t.config=e.getConfig(),t}function Gm(e){if(null!=e&&"object"==typeof e)if(Array.isArray(e))e.forEach((e=>Gm(e)));else{const t=Object.keys(e);for(const n of t){const t=e[n];null!=t&&"object"==typeof t&&(Array.isArray(t)||"ndarray"!==t.type||"number"!=typeof t.value?Gm(t):e[n]=t.value)}}}function Hm(e,t={},n={},s="object",r=!1){if("string"==typeof e){const r=e;let a;if(r in n)a=n[r];else if(r in Vm)a=Vm[r];else if(a=t[r],null==a)throw new Am(`Unknown ${s}: ${e}. This may be due to one of the following reasons:\n1. The ${s} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.\n2. The custom ${s} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);return a}{const a=e;if(null==a.className||null==a.config)throw new Am(`${s}: Improper config format: ${JSON.stringify(a)}.\n'className' and 'config' must set.`);const i=a.className;let o,l;if(i in n?[o,l]=n[i]:i in Vm?[o,l]=Vm.className:i in t&&([o,l]=t[i]),null==o)throw new Am(`Unknown ${s}: ${i}. This may be due to one of the following reasons:\n1. The ${s} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.\n2. The custom ${s} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);if(null!=l){const e={};for(const t of Object.keys(Vm))e[t]=Vm[t];for(const t of Object.keys(n))e[t]=n[t];a.config.customObjects=e;const t=Object.assign({},Vm);for(const e of Object.keys(n))Vm[e]=n[e];Gm(a.config);const s=l(o,a.config,n,r);return Vm=Object.assign({},t),s}{const e=Object.assign({},Vm);for(const e of Object.keys(n))Vm[e]=n[e];const t=new o(a.config);return Vm=Object.assign({},e),t}}}function jm(e,t){return-1*function(e,t){return et?1:0}(e,t)}function qm(e){if(null==e)return e;const t=[];for(const n of e)-1===t.indexOf(n)&&t.push(n);return t}function Km(e){if(null==e)throw new Am(`Invalid value in obj: ${JSON.stringify(e)}`);for(const t in e)if(e.hasOwnProperty(t))return!1;return!0}function Xm(e,t,n){if(null!=n&&e.indexOf(n)<0)throw new Am(`${n} is not a valid ${t}. Valid values are ${e} or null/undefined.`)}function Ym(e,t,n=0,s=1/0){return Mm(n>=0),Mm(s>=n),Array.isArray(e)&&e.length>=n&&e.length<=s&&e.every((e=>typeof e===t))}function Zm(e,t){Array.isArray(e)?(O(e.length>0,(()=>`${t} is unexpectedly an empty array.`)),e.forEach(((e,n)=>Zm(e,`element ${n+1} of ${t}`)))):O(Number.isInteger(e)&&e>0,(()=>`Expected ${t} to be a positive integer, but got ${Jm(e)}.`))}function Jm(e){return null===e?"null":Array.isArray(e)?"["+e.map((e=>Jm(e))).join(",")+"]":"string"==typeof e?`"${e}"`:`${e}`}function Qm(e){return"relu"===e?"relu":"linear"===e?"linear":"elu"===e?"elu":null}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+let eg=0;function tg(){return eg++}const ng={};function sg(e=""){return e in ng||(ng[e]=0),ng[e]+=1,e+ng[e].toString()}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+const rg=["channelsFirst","channelsLast"],ag=["nearest","bilinear"],ig=["valid","same","causal"],og=["max","avg"],lg=["sum","mul","concat","ave"],ug=new Map;function cg(e){Xm(rg,"DataFormat",e)}function hg(e){Xm(ig,"PaddingMode",e)}function pg(e){Xm(og,"PoolMode",e)}const dg=[];function fg(e,t){dg.push(e);try{const e=t();return dg.pop(),e}catch(e){throw dg.pop(),e}}function mg(e){if(!bg(e))throw new Error("Not a valid tensor name: '"+e+"'");return(0===dg.length?"":dg.join("/")+"/")+e}function gg(e){if(!bg(e))throw new Error("Not a valid tensor name: '"+e+"'");ug.has(e)||ug.set(e,0);const t=ug.get(e);if(ug.set(e,ug.get(e)+1),t>0){const n=`${e}_${t}`;return ug.set(n,1),n}return e}const yg=new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);function bg(e){return!!e.match(yg)}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function xg(e){return e===parseInt(e.toString(),10)}function wg(e,t,n){null==t&&(t=0),null==n&&(n=e.length);let s=1;for(let r=t;rt&&(t=s)}return t}function Ig(e,t){if(t{switch(e.rank){case 1:return $c(e,t,n);case 2:return Ec(e,[t,0],[n,e.shape[1]]);case 3:return Rc(e,[t,0,0],[n,e.shape[1],e.shape[2]]);case 4:return Ac(e,[t,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3]]);case 5:return Bo(e,[t,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4]]);case 6:return Bo(e,[t,0,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4],e.shape[5]]);default:throw new Am(`sliceAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}}))}function Eg(e,t,n){return Zi((()=>{switch(e.rank){case 1:return $c(e,t,n);case 2:return Ec(e,[0,t],[e.shape[0],n]);case 3:return Rc(e,[0,0,t],[e.shape[0],e.shape[1],n]);case 4:return Ac(e,[0,0,0,t],[e.shape[0],e.shape[1],e.shape[2],n]);default:throw new Am(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}}))}function Rg(e,t,n,s){return Zi((()=>{switch(e.rank){case 1:return $c(e,t,n);case 2:switch(s){case 1:return $g(e,t,n);case 2:return Eg(e,t,n);default:throw new Am(`The axis is not within the rank of the tensor ${s}`)}case 3:switch(s){case 1:return $g(e,t,n);case 2:return Rc(e,[0,t,0],[e.shape[0],n,e.shape[2]]);case 3:return Eg(e,t,n);default:throw new Am(`The axis is not within the rank of the tensor ${s}`)}case 4:switch(s){case 1:return $g(e,t,n);case 2:return Ac(e,[0,t,0,0],[e.shape[0],n,e.shape[2],e.shape[3]]);case 3:return Ac(e,[0,0,t,0],[e.shape[0],e.shape[1],n,e.shape[3]]);case 4:return Eg(e,t,n);default:throw new Am(`The axis is not within the rank of the tensor ${s}`)}default:throw new Am(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}}))}function Ag(e,t=-1){let n;return t<0&&(n=e[0].rank,t=0!==n?n:0),t===e[0].rank&&(t=-1),Mo(e,t)}function Fg(e,t){switch(e.rank){case 1:return el([e,t]);case 2:return tl([e,t],0);case 3:return nl([e,t],0);case 4:return sl([e,t],0);default:throw new Am(`concatAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}}function _g(e,t){if(Array.isArray(t)||(t=[t]),e.rank!==t.length)throw new Am(`The length of input n (${t.length}) does not match the number of dimensions in input x (${e.rank})`);return Yl(e,t)}function Dg(e,t=0,n=1,s,r){return oc(e,t,n,s,r)}function Og(e,t,n,s){if(e.rank<2||t.rank<2)throw new Fm(`dot requires both inputs to be rank >= 2 but got x shape = ${e.shape} and y shape = ${t.shape}`);if(t.rank>=3){if(e.shape.slice(-1)[0]!==t.shape.slice(-2)[0])throw new Fm(`If rank y >= 3, then the second last dim of y must equal the last dim of x but got x shape = ${e.shape} and y shape = ${t.shape}`)}if(2===e.rank&&2===t.rank){return Th({a:e,b:t,transposeA:!1,transposeB:!1,bias:s?zg(e.rank,s,"channelsLast"):null,activation:n})}{const r=e.shape.slice(),a=r.pop();e=_o(e,[-1,a]);const i=t.shape.slice(),o=i.pop(),l=i.pop(),u=[...i,o],c=Array.from({length:t.rank},((e,n)=>0===n?t.rank-2:n<=t.rank-2?n-1:n));t=_o(ah(t,c),[l,-1]);const h=[...r,...u];return _o(Th({a:e,b:t,transposeA:!1,transposeB:!1,bias:s?zg(e.rank,s,"channelsLast"):null,activation:n}),h)}}function Mg(e,t,n){return Zi((()=>(t=Array.isArray(t)?Gc(t,"int32"):Za(t,"int32"),Ql(e,t,n))))}function Lg(e){return zo(e,e)}function zg(e,t,n){const s=t.shape;if(1!==t.rank&&t.rank!==e)throw new Am(`Unexpected bias dimensions: ${t.rank}; expected it to be 1 or ${e}`);if(5===e){if("channelsFirst"===n)return 1===s.length?_o(t,[1,s[0],1,1,1]):_o(t,[1,s[3],s[0],s[1],s[2]]);if("channelsLast"===n)return 1===s.length?_o(t,[1,1,1,1,s[0]]):_o(t,[1].concat(s))}else if(4===e){if("channelsFirst"===n)return 1===s.length?_o(t,[1,s[0],1,1]):_o(t,[1,s[2],s[0],s[1]]);if("channelsLast"===n)return 1===s.length?_o(t,[1,1,1,s[0]]):_o(t,[1].concat(s))}else if(3===e){if("channelsFirst"===n)return 1===s.length?_o(t,[1,s[0],1]):_o(t,[1,s[1],s[0]]);if("channelsLast"===n)return 1===s.length?_o(t,[1,1,s[0]]):_o(t,[1].concat(s))}else if(e<3)return t;throw new Am(`Unsupported input rank by biasAdd: ${t.rank}`)}function Pg(e,t,n){return Zi((()=>(null==n&&(n="channelsLast"),cg(n),oo(e,zg(e.rank,t,n)))))}function Bg(e,t,n,s){return Zi((()=>dh(e,t,n,s)))}function Wg(e,t,n=!1){return n?e():t()}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+const Vg=["fanIn","fanOut","fanAvg"],Ug=["normal","uniform","truncatedNormal"];class Gg extends ji{fromConfigUsesCustomObjects(){return!1}getConfig(){return{}}}class Hg extends Gg{apply(e,t){return Au(e,t)}}Hg.className="Zeros",Ki(Hg);class jg extends Gg{apply(e,t){return Fu(e,t)}}jg.className="Ones",Ki(jg);class qg extends Gg{constructor(e){if(super(),"object"!=typeof e)throw new Am(`Expected argument of type ConstantConfig but got ${e}`);if(void 0===e.value)throw new Am(`config must have value set but got ${e}`);this.value=e.value}apply(e,t){return Zi((()=>zo(no(this.value),Fu(e,t))))}getConfig(){return{value:this.value}}}qg.className="Constant",Ki(qg);class Kg extends Gg{constructor(e){super(),this.DEFAULT_MINVAL=-.05,this.DEFAULT_MAXVAL=.05,this.minval=e.minval||this.DEFAULT_MINVAL,this.maxval=e.maxval||this.DEFAULT_MAXVAL,this.seed=e.seed}apply(e,t){return uc(e,this.minval,this.maxval,t)}getConfig(){return{minval:this.minval,maxval:this.maxval,seed:this.seed}}}Kg.className="RandomUniform",Ki(Kg);class Xg extends Gg{constructor(e){super(),this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if("float32"!==(t=t||"float32")&&"int32"!==t)throw new Fm(`randomNormal does not support dType ${t}.`);return Dg(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}}Xg.className="RandomNormal",Ki(Xg);class Yg extends Gg{constructor(e){super(),this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if("float32"!==(t=t||"float32")&&"int32"!==t)throw new Fm(`truncatedNormal does not support dType ${t}.`);return Yc(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}}Yg.className="TruncatedNormal",Ki(Yg);class Zg extends Gg{constructor(e){super(),this.gain=null!=e.gain?e.gain:1}apply(e,t){return Zi((()=>{if(2!==e.length||e[0]!==e[1])throw new Am("Identity matrix initializer can only be used for 2D square matrices.");return zo(this.gain,Zl(e[0]))}))}getConfig(){return{gain:this.gain}}}Zg.className="Identity",Ki(Zg);class Jg extends Gg{constructor(e){if(super(),e.scale<0)throw new Am(`scale must be a positive float. Got: ${e.scale}`);
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+var t;this.scale=null==e.scale?1:e.scale,this.mode=null==e.mode?"fanIn":e.mode,t=this.mode,Xm(Vg,"FanMode",t),this.distribution=null==e.distribution?"normal":e.distribution,function(e){Xm(Ug,"Distribution",e)}(this.distribution),this.seed=e.seed}apply(e,t){const n=function(e,t="channelsLast"){let n,s;if(cg(t),2===e.length)n=e[0],s=e[1];else if(-1!==[3,4,5].indexOf(e.length)){if("channelsFirst"===t){const t=wg(e,2);n=e[1]*t,s=e[0]*t}else if("channelsLast"===t){const t=wg(e,0,e.length-2);n=e[e.length-2]*t,s=e[e.length-1]*t}}else{const t=wg(e);n=Math.sqrt(t),s=Math.sqrt(t)}return[n,s]}(e),s=n[0],r=n[1];let a=this.scale;if("fanIn"===this.mode?a/=Math.max(1,s):"fanOut"===this.mode?a/=Math.max(1,r):a/=Math.max(1,(s+r)/2),"normal"===this.distribution){const n=Math.sqrt(a);if("float32"!==(t=t||"float32")&&"int32"!==t)throw new Fm(`${this.getClassName()} does not support dType ${t}.`);return Yc(e,0,n,t,this.seed)}{const n=Math.sqrt(3*a);return uc(e,-n,n,t)}}getConfig(){return{scale:this.scale,mode:this.mode,distribution:this.distribution,seed:this.seed}}}Jg.className="VarianceScaling",Ki(Jg);class Qg extends Jg{constructor(e){super({scale:1,mode:"fanAvg",distribution:"uniform",seed:null==e?null:e.seed})}getClassName(){return Jg.className}}Qg.className="GlorotUniform",Ki(Qg);class ey extends Jg{constructor(e){super({scale:1,mode:"fanAvg",distribution:"normal",seed:null==e?null:e.seed})}getClassName(){return Jg.className}}ey.className="GlorotNormal",Ki(ey);class ty extends Jg{constructor(e){super({scale:2,mode:"fanIn",distribution:"normal",seed:null==e?null:e.seed})}getClassName(){return Jg.className}}ty.className="HeNormal",Ki(ty);class ny extends Jg{constructor(e){super({scale:2,mode:"fanIn",distribution:"uniform",seed:null==e?null:e.seed})}getClassName(){return Jg.className}}ny.className="HeUniform",Ki(ny);class sy extends Jg{constructor(e){super({scale:1,mode:"fanIn",distribution:"normal",seed:null==e?null:e.seed})}getClassName(){return Jg.className}}sy.className="LeCunNormal",Ki(sy);class ry extends Jg{constructor(e){super({scale:1,mode:"fanIn",distribution:"uniform",seed:null==e?null:e.seed})}getClassName(){return Jg.className}}ry.className="LeCunNormal",Ki(ry);class ay extends Gg{constructor(e){if(super(),this.DEFAULT_GAIN=1,this.gain=null==e.gain?this.DEFAULT_GAIN:e.gain,this.seed=e.seed,null!=this.seed)throw new Fm("Random seed is not implemented for Orthogonal Initializer yet.")}apply(e,t){return Zi((()=>{if(e.length<2)throw new Fm("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${e[0]*e[1]}) elements: Slowness may result.`);const t=Dg(e[0]>e[1]?[e[1],e[0]]:e,0,1,"float32");let n=Sp.gramSchmidt(t);return e[0]>e[1]&&(n=ah(n)),zo(this.gain,n)}))}getConfig(){return{gain:this.gain,seed:this.seed}}}ay.className="Orthogonal",Ki(ay);const iy={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",heUniform:"HeUniform",identity:"Identity",leCunNormal:"LeCunNormal",leCunUniform:"LeCunUniform",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"};function oy(e,t={}){return Hm(e,qi.getMap().classNameMap,t,"initializer")}function ly(e){return Um(e)}function uy(e){if("string"==typeof e){const t=e in iy?iy[e]:e;if("GlorotNormal"===t)return new ey;if("GlorotUniform"===t)return new Qg;if("HeNormal"===t)return new ty;if("HeUniform"===t)return new ny;if("LeCunNormal"===t)return new sy;if("LeCunUniform"===t)return new ry;{const e={};return e.className=t,e.config={},oy(e)}}return e instanceof Gg?e:oy(e)}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function cy(e){return Array.isArray(e)&&Array.isArray(e[0])}function hy(e){return 0===e.length?[]:Array.isArray(e[0])?e:[e]}function py(e){let t;if(Array.isArray(e)){if(1!==e.length)throw new Am(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function dy(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(1===e.length)return e[0];throw new Am(`Expected exactly 1 Shape; got ${e.length}`)}return e}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function fy(e){let t=0;for(const n of e)0===n.shape.length?t+=1:t+=n.shape.reduce(((e,t)=>e*t));return t}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+const my="Variable";class gy{constructor(e,t="float32",n=my,s=!0,r=null){this.dtype=null==t?"float32":t,this.shape=e.shape,this.id=tg(),n=null==n?my:n,this.originalName=mg(n),this.name=gg(this.originalName),this.trainable_=s,this.constraint=r,this.val=th(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),function(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}(this.val,e),this.val.id!==e.id&&(this.val.assign(e),null!=this.constraint&&this.val.assign(this.constraint.apply(this.val))),this}dispose(){this.assertNotDisposed(),this.val.dispose()}assertNotDisposed(){if(this.val.isDisposed)throw new Error(`LayersVariable ${this.name} is already disposed.`)}get trainable(){return this.trainable_}set trainable(e){this.trainable_=e,this.val.trainable=e}}function yy(e){return e.map((e=>e.read()))}function by(e){e.forEach((e=>{e[0].write(e[1])}))}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class xy{constructor(e){this.dtype=e.dtype,this.shape=e.shape,null!=e.shape?this.ndim=e.shape.length:this.ndim=e.ndim,this.maxNDim=e.maxNDim,this.minNDim=e.minNDim,this.axes=e.axes||{}}}class wy{constructor(e,t,n,s,r,a,i){this.dtype=e,this.shape=t,this.sourceLayer=n,this.inputs=s,this.callArgs=r,this.outputTensorIndex=i,this.id=tg(),null!=a&&(this.originalName=mg(a),this.name=gg(this.originalName)),this.rank=t.length}}let vy=0;class ky{constructor(e,t){this.callArgs=t,this.id=vy++,this.outboundLayer=e.outboundLayer,this.inboundLayers=e.inboundLayers,this.nodeIndices=e.nodeIndices,this.tensorIndices=e.tensorIndices,this.inputTensors=e.inputTensors,this.outputTensors=e.outputTensors,this.inputMasks=e.inputMasks,this.outputMasks=e.outputMasks,this.inputShapes=e.inputShapes,this.outputShapes=e.outputShapes;for(const t of e.inboundLayers)null!=t&&t.outboundNodes.push(this);e.outboundLayer.inboundNodes.push(this)}getConfig(){const e=[];for(const t of this.inboundLayers)null!=t?e.push(t.name):e.push(null);return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:e,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}}let Iy=0;class Ny extends ji{constructor(e={}){super(),this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=Iy++,this.activityRegularizer=null,this.inputSpec=null,this.supportsMasking=!1,this._trainableWeights=[],this._nonTrainableWeights=[],this._losses=[],this._updates=[],this._built=!1,this.inboundNodes=[],this.outboundNodes=[];let t=e.name;if(!t){const e=this.getClassName();t=Bm(e)+"_"+sg(e)}if(this.name=t,this.trainable_=null==e.trainable||e.trainable,null!=e.inputShape||null!=e.batchInputShape){let t;if(null!=e.batchInputShape)t=e.batchInputShape;else if(null!=e.inputShape){let n=null;null!=e.batchSize&&(n=e.batchSize),t=[n].concat(e.inputShape)}this.batchInputShape=t;let n=e.dtype;null==n&&(n=e.inputDType),null==n&&(n="float32"),this.dtype=n}null!=e.weights?this.initialWeights=e.weights:this.initialWeights=null,this._refCount=null,this.fastWeightInitDuringBuild=!1}static nodeKey(e,t){return e.name+"_ib-"+t.toString()}getNodeAtIndex(e,t){if(0===this.inboundNodes.length)throw new Rm(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new Am(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return zm(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return zm(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new Em(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use \`getInputAt(nodeIndex)\` instead.`);if(0===this.inboundNodes.length)throw new Em(`Layer ${this.name} is not connected, no input to return.`);return zm(this.getNodeAtIndex(0,"input").inputTensors)}get output(){if(0===this.inboundNodes.length)throw new Em(`Layer ${this.name} has no inbound nodes.`);if(this.inboundNodes.length>1)throw new Em(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use \`getOutputAt(nodeIndex)\` instead.`);return zm(this.getNodeAtIndex(0,"output").outputTensors)}get losses(){return this._losses}calculateLosses(){return this.losses.map((e=>e()))}get updates(){return this._updates}get built(){return this._built}set built(e){this._built=e}get trainable(){return this.trainable_}set trainable(e){this._trainableWeights.forEach((t=>t.trainable=e)),this.trainable_=e}get trainableWeights(){return this.trainable_?this._trainableWeights.filter((e=>e.trainable)):[]}set trainableWeights(e){this._trainableWeights=e}get nonTrainableWeights(){return this.trainable?this._trainableWeights.filter((e=>!e.trainable)).concat(this._nonTrainableWeights):this._trainableWeights.concat(this._nonTrainableWeights)}set nonTrainableWeights(e){this._nonTrainableWeights=e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}get stateful(){return this._stateful}resetStates(){if(!this.stateful)throw new Error("Cannot call the resetStates() method of a non-stateful Layer object.")}assertInputCompatibility(e){if(e=Pm(e),null==this.inputSpec||0===this.inputSpec.length)return;const t=Pm(this.inputSpec);if(e.length!==t.length)throw new Am(`Layer ${this.name} expects ${t.length} inputs, but it received ${e.length} input tensors. Input received: ${e}`);for(let n=0;nr.maxNDim)throw new Am(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${r.maxNDim}, found ndim=${a}`);if(null!=r.minNDim&&a=0?e[s]:e[e.length+s];if(null!=a&&-1===[a,null].indexOf(i))throw new Am(`Input ${n} is incompatible with layer ${this.name}: expected axis ${s} of input shape to have value ${a} but got shape ${e}.`)}}if(null!=r.shape)for(let e=0;e{if(!this.built){this.assertInputCompatibility(e);const t=[];for(const n of Pm(e))t.push(n.shape);this.build(zm(t)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),null===this._refCount&&r&&(this._refCount=1)}if(this.assertInputCompatibility(e),r){let s=this.call(e,t);const r=Pm(s),a=[];for(let e of r)-1!==n.indexOf(e)&&(e=e.clone()),a.push(e);if(s=zm(a),null!=this.activityRegularizer)throw new Fm("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return s}{const n=function(e){e=Pm(e);const t=[];for(const n of e)t.push(n.shape);return zm(t)}(e),s=this.computeOutputShape(n);let r;const a="float32";if(this.warnOnIncompatibleInputShape(Array.isArray(e)?n[0]:n),r=null!=s&&s.length>0&&Array.isArray(s[0])?s.map(((n,s)=>new wy(a,n,this,Pm(e),t,this.name,s))):new wy(a,s,this,Pm(e),t,this.name),this.addInboundNode(e,r,null,null,n,s,t),this._refCount++,null!=this.activityRegularizer)throw new Fm("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return r}}))}warnOnIncompatibleInputShape(e){if(null!=this.batchInputShape)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach(((n,s)=>{null!=n&&null!=e[s]&&e[s]!==n&&(t=!0)})),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(null==this.inboundNodes||0===this.inboundNodes.length)throw new Em(`The layer ${this.name} has never been called and thus has no defined output shape.`);const e=[];for(const t of this.inboundNodes){const n=JSON.stringify(t.outputShapes);-1===e.indexOf(n)&&e.push(n)}if(1===e.length){const e=this.inboundNodes[0].outputShapes;return Array.isArray(e)&&Array.isArray(e[0])&&1===e.length?e[0]:e}throw new Em(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new Rm(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return fy(this.weights)}build(e){this.built=!0}getWeights(e=!1){return yy(e?this.trainableWeights:this.weights)}setWeights(e){Zi((()=>{const t=this.weights;if(t.length!==e.length)throw new Am(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. Provided weights: ${e}...`);if(0===t.length)return;const n=[],s=yy(t);for(let r=0;rr.apply(u.read()))),null==a&&(a=!0),a?this._trainableWeights.push(u):this._nonTrainableWeights.push(u),u}setFastWeightInitDuringBuild(e){this.fastWeightInitDuringBuild=e}addLoss(e){null==e||Array.isArray(e)&&0===e.length||(e=Pm(e),void 0!==this._losses&&null!==this._losses&&this.losses.push(...e))}computeOutputShape(e){return e}computeMask(e,t){if(!this.supportsMasking){if(null!=t){if(!Array.isArray(t))throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);t.forEach((e=>{if(null!=e)throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`)}))}return null}return t}addInboundNode(e,t,n,s,r,a,i=null){const o=Pm(e);t=Pm(t),n=Pm(n),s=Pm(s),r=hy(r),a=hy(a);const l=[],u=[],c=[];for(const e of o)l.push(e.sourceLayer),u.push(e.nodeIndex),c.push(e.tensorIndex);new ky({outboundLayer:this,inboundLayers:l,nodeIndices:u,tensorIndices:c,inputTensors:o,outputTensors:t,inputMasks:n,outputMasks:s,inputShapes:r,outputShapes:a},i);for(let e=0;ee.dispose())),this.weights.length}assertNotDisposed(){if(0===this._refCount)throw new Error(`Layer '${this.name}' is already disposed.`)}dispose(){if(!this.built)throw new Error(`Cannot dispose Layer ${this.name} because it has not been built yet.`);if(null===this._refCount)throw new Error(`Cannot dispose Layer ${this.name} because it has not been used yet.`);this.assertNotDisposed();let e=0;return 0==--this._refCount&&(e=this.disposeWeights()),{refCountAfterDispose:this._refCount,numDisposedVariables:e}}}function Sy(e,t,n){if((null==t||null!=n&&n>0)&&(t=e.sourceLayer,n=e.nodeIndex),0===t.inboundNodes.length)return[e];{const e=t.inboundNodes[n];if(0===e.inboundLayers.length)return e.inputTensors;{const t=[];for(let n=0;ne.name)),l=[],u=t.names();for(const e of o)-1!==u.indexOf(e)?l.push(t.getValue(e)):l.push(null);null!=s&&(s.maxNumTensors=-1/0,s.minNumTensors=1/0);const c=o.join(",")+"|"+t.names().sort().join(",");let h,p=$y.get(c);if(null==p){const e=function(e,t){O(null!=e&&e.length>0,(()=>"Expected at least one fetch, got none"));let n=[],s={};if(1===e.length){const r=Fy(e[0],t);n=r.sorted,s=r.recipientMap}else{const r=new Set;for(const a of e){const{sorted:e,recipientMap:i}=Fy(a,t);for(const t of e)r.has(t.name)||(n.push(t),r.add(t.name));for(const e in i)null==s[e]&&(s[e]=new Set),i[e].forEach((t=>s[e].add(t)))}}return{sorted:n,recipientCounts:Ay(s)}}(i,t);p=e.sorted,h=e.recipientCounts,$y.put(c,p),Ey.put(c,h)}h={},r||Object.assign(h,Ey.get(c));const d=new Cy(t);for(let e=0;es.maxNumTensors&&(s.maxNumTensors=e),e0;){const e=a[a.length-1];if(n.has(e.name)){a.pop();continue}const t=i[i.length-1]===a.length-1;if(0===e.inputs.length||t)a.pop(),s.push(e),n.add(e.name),t&&i.pop();else{i.push(a.length-1);for(const t of e.inputs)null==r[t.name]&&(r[t.name]=new Set),r[t.name].add(e.name),n.has(t.name)||a.push(t)}}return{sorted:s,recipientMap:r}}function _y(e){let t;if(1===e.sourceLayer.inboundNodes.length)t=e.sourceLayer.output;else{let n=null;for(let t=0;tWl(Ul(zo(e,e),t,!0))))}ye().registerFlag("TOPOLOGICAL_SORT_CACHE_MAX_ENTRIES",(()=>100),(function(e){null!=$y&&$y.setMaxEntries(e),null!=Ey&&Ey.setMaxEntries(e)}));class Oy extends ji{getConfig(){return{}}}class My extends Oy{constructor(e){super(),this.defaultMaxValue=2,this.defaultAxis=0,this.maxValue=null!=e.maxValue?e.maxValue:this.defaultMaxValue,this.axis=null!=e.axis?e.axis:this.defaultAxis}apply(e){return Zi((()=>{const t=Dy(e,this.axis),n=Qo(t,0,this.maxValue);return zo(e,vl(n,oo(Sg(),t)))}))}getConfig(){return{maxValue:this.maxValue,axis:this.axis}}}My.className="MaxNorm",Ki(My);class Ly extends Oy{constructor(e){super(),this.defaultAxis=0,this.axis=null!=e.axis?e.axis:this.defaultAxis}apply(e){return Zi((()=>vl(e,oo(Sg(),Dy(e,this.axis)))))}getConfig(){return{axis:this.axis}}}Ly.className="UnitNorm",Ki(Ly);class zy extends Oy{apply(e){return dc(e)}}zy.className="NonNeg",Ki(zy);class Py extends Oy{constructor(e){super(),this.defaultMinValue=0,this.defaultMaxValue=1,this.defaultRate=1,this.defaultAxis=0,this.minValue=null!=e.minValue?e.minValue:this.defaultMinValue,this.maxValue=null!=e.maxValue?e.maxValue:this.defaultMaxValue,this.rate=null!=e.rate?e.rate:this.defaultRate,this.axis=null!=e.axis?e.axis:this.defaultAxis}apply(e){return Zi((()=>{const t=Dy(e,this.axis),n=oo(zo(this.rate,Qo(t,this.minValue,this.maxValue)),zo(1-this.rate,t));return zo(e,vl(n,oo(Sg(),t)))}))}getConfig(){return{minValue:this.minValue,maxValue:this.maxValue,rate:this.rate,axis:this.axis}}}Py.className="MinMaxNorm",Ki(Py);const By={maxNorm:"MaxNorm",minMaxNorm:"MinMaxNorm",nonNeg:"NonNeg",unitNorm:"UnitNorm"};function Wy(e){return Um(e)}function Vy(e,t={}){return Hm(e,qi.getMap().classNameMap,t,"constraint")}function Uy(e){if(null==e)return null;if("string"==typeof e){return Vy({className:e in By?By[e]:e,config:{}})}return e instanceof Oy?e:Vy(e)}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+async function Gy(e){if(null==e)return;const t=[],n=[],s=[];for(const r in e){const a=e[r];if("number"!=typeof a){const e=a;t.push(e.data()),n.push(r),s.push(e)}}if(t.length>0){const r=await Promise.all(t);for(let t=0;too(this.totals[e],zo(s,n))));this.totals[e]=r,null!=t&&t.dispose()}}}async onEpochEnd(e,t){if(null!=t)for(const e of this.params.metrics)null!=this.totals[e]&&("number"==typeof this.totals[e]?t[e]=this.totals[e]/this.seen:Zi((()=>{const n=zo(vl(1,this.seen),this.totals[e]);t[e]=n,this.totals[e].dispose(),Qi(t[e])})))}}class Yy extends qy{async onTrainBegin(e){this.epoch=[],this.history={}}async onEpochEnd(e,t){null==t&&(t={}),this.epoch.push(e);for(const e in t)null==this.history[e]&&(this.history[e]=[]),this.history[e].push(t[e])}async syncData(){const e=[],t=[],n=[];for(const s in this.history){const r=this.history[s];for(let a=0;a{const i=null!=n?n():tr();return i-rnew Zy(e,t)))}class Qy{constructor(){}static registerCallbackConstructor(e,t){O(e>=0&&Number.isInteger(e),(()=>`Verbosity level is expected to be an integer >= 0, but got ${e}`)),Qy.checkForDuplicate(t),null==Qy.constructors[e]&&(Qy.constructors[e]=[]),Qy.constructors[e].push(t)}static checkForDuplicate(e){for(const t in Qy.constructors){Qy.constructors[+t].forEach((t=>{if(t===e)throw new Am("Duplicate callback constructor.")}))}}static clear(){Qy.constructors={}}static createCallbacks(e){const t=[];for(const n in Qy.constructors){const s=+n;e>=s&&t.push(...Qy.constructors[s])}return t.map((e=>new e))}}function eb(e,t,n,s,r,a,i,o,l){const u=new Yy,c=[new Xy,...Qy.createCallbacks(t)];null!=e&&c.push(...e),c.push(u);const h=new Ky(c);return h.setParams({epochs:n,initialEpoch:s,samples:r,steps:a,batchSize:i,verbose:t,doValidation:o,metrics:l}),{callbackList:h,history:u}}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function tb(e,t={},n=!1){return Hm(e,qi.getMap().classNameMap,t,"layer",n)}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function nb(e,t){return Zi((()=>{"float32"!==e.dtype&&(e=Za(e,"float32"));const n=Ul(Lg(e),t,!0),s=Jo(n.shape,Sg()),r=Wl(Eu(n,s));return vl(e,r)}))}function sb(e,t){return Zi((()=>Ru(Lg(gu(t,e)),-1)))}function rb(e,t){return Zi((()=>Ru(ro(gu(t,e)),-1)))}function ab(e,t){return Zi((()=>{const n=gu(e,t),s=Qo(ro(e),Sg(),Number.MAX_VALUE),r=ro(vl(n,s));return zo(100,Ru(r,-1))}))}function ib(e,t){return Zi((()=>{const n=Qo(t,Sg(),Number.MAX_VALUE),s=hu(oo(1,n)),r=Qo(e,Sg(),Number.MAX_VALUE),a=hu(oo(1,r));return Ru(Lg(gu(s,a)),-1)}))}function ob(e,t,n=!1){return Zi((()=>{if(n)t=Fc(t);else{const e=Ul(t,t.shape.length-1,!0);t=vl(t,e)}return t=Qo(t,Sg(),1-Sg()),du(Ul(zo(Za(e,"float32"),hu(t)),t.shape.length-1))}))}function lb(e,t,n=!1){return Zi((()=>{const s=Za(Jl(function(e){const t=[wg(e.shape)];return _o(e,t)}(e)),"int32"),r=(t=Qo(t,Sg(),1-Sg())).shape;return ob(_o(Wu(s,r[r.length-1]),r),t,n)}))}function ub(e,t){return Zi((()=>{let n;return n=Qo(t,Sg(),1-Sg()),n=hu(vl(n,gu(1,n))),Ru(function(e,t){if(!B(e.shape,t.shape))throw new Am(`logits and labels must have the same shape, but got shapes ${JSON.stringify(e.shape)} and ${JSON.stringify(t.shape)}`);return Zi((()=>{const n=dc(t),s=du(ro(t));return oo(gu(n,zo(t,e)),pu(ql(s)))}))}(e,n),-1)}))}function cb(e,t){return Zi((()=>{const n=Qo(e,Sg(),1),s=Qo(t,Sg(),1);return Ul(zo(e,hu(vl(n,s))),-1)}))}function hb(e,t){return Zi((()=>{const n=nb(e,-1),s=nb(t,-1),r=zo(n,s);return du(Ul(r,-1))}))}Qy.constructors={};const pb={meanSquaredError:sb,meanAbsoluteError:rb,meanAbsolutePercentageError:ab,meanSquaredLogarithmicError:ib,squaredHinge:function(e,t){return Zi((()=>{const n=Eu(0,gu(1,zo(e,t)));return Ru(Lg(n),-1)}))},hinge:function(e,t){return Zi((()=>{const n=Eu(0,gu(1,zo(e,t)));return Ru(n,-1)}))},categoricalHinge:function(e,t){return Zi((()=>{const n=Ul(zo(e,t),-1),s=zl(zo(gu(1,e),t),-1);return Eu(0,oo(1,gu(s,n)))}))},logcosh:function(e,t){return Zi((()=>{const n=Math.log(2),s=gu(t,e),r=gu(oo(s,fu(zo(-2,s))),n);return Ru(r,-1)}))},categoricalCrossentropy:ob,sparseCategoricalCrossentropy:lb,binaryCrossentropy:ub,kullbackLeiblerDivergence:cb,poisson:function(e,t){return Zi((()=>{const n=hu(oo(Sg(),t));return Ru(gu(t,zo(e,n)),-1)}))},cosineProximity:hb};function db(e){if("string"==typeof e){if(e in pb)return pb[e];let t=`Unknown loss ${e}`;throw e.toLowerCase().includes("softmaxcrossentropy")&&(t=`Unknown loss ${e}. Use "categoricalCrossentropy" as the string name for tf.losses.softmaxCrossEntropy`),new Am(t)}return e}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function fb(e,t){return Zi((()=>{const n=zo(.5,Vu(t)),s=Tg(eu(t,n),e.dtype);return Ru(kl(e,s),-1)}))}function mb(e,t){return Zi((()=>Tg(kl(ho(e,-1),ho(t,-1)),"float32")))}function gb(e,t){return Zi((()=>Za(Ul(xu(kl(e,1),kl(t,1))),"float32")))}function yb(e,t){return ub(e,t)}function bb(e,t){return e.rank===t.rank&&(e=Pc(e,[e.rank-1])),(t=ho(t,-1)).dtype!==e.dtype&&(t=Za(t,e.dtype)),Za(kl(e,t),"float32")}const xb=ob,wb=lb,vb={binaryAccuracy:fb,categoricalAccuracy:mb,precision:function(e,t){return Zi((()=>{const n=gb(e,t),s=function(e,t){return Zi((()=>Za(Ul(xu(kl(e,0),kl(t,1))),"float32")))}(e,t),r=oo(n,s);return Za(Il(eu(r,0),vl(n,r),0),"float32")}))},categoricalCrossentropy:xb,sparseCategoricalCrossentropy:wb,mse:sb,MSE:sb,mae:rb,MAE:rb,mape:ab,MAPE:ab,cosine:hb};function kb(e){if("string"==typeof e&&e in vb)return vb[e];if("string"!=typeof e&&null!=e)return e;throw new Am(`Unknown metric ${e}`)}function Ib(e){if(Mm(null!==e,`Unknown LossOrMetricFn ${e}`),"string"==typeof e)return e;{let t;for(const n of Object.keys(pb))if(pb[n]===e){t=n;break}if(void 0!==t)return t;for(const n of Object.keys(vb))if(vb[n]===e){t=n;break}return void 0!==t?t:e.name}}
+/**
+ * @license
+ * Copyright 2019 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+const Nb=1048576;function Sb(e,t,n=!1){if(null==e||"object"!=typeof e||Object.getPrototypeOf(e)!==Object.prototype||!Tb(e))throw new Error("User-defined metadata is expected to be a JSON object, but is not.");if(n){const n=JSON.stringify(e);n.length>Nb&&console.warn(`User-defined metadata of model "${t}" is too large in size (length=${n.length} when serialized). It is not recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= 1048576.`)}}function Tb(e){if(null===e)return!0;if("object"==typeof e){if(Object.getPrototypeOf(e)===Object.prototype){const t=Object.keys(e);for(const n of t){if("string"!=typeof n)return!1;if(!Tb(e[n]))return!1}return!0}if(Array.isArray(e)){for(const t of e)if(!Tb(t))return!1;return!0}return!1}{const t=typeof e;return"string"===t||"number"===t||"boolean"===t}}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function Cb(e,t,n,s=console.log){const r=function(e){let t=!0;const n=[],s=[];for(const t in e.nodesByDepth)n.push(e.nodesByDepth[t]);for(const e of n){if(e.length>1||1===e.length&&e[0].inboundLayers.length>1){t=!1;break}s.push(...e)}if(t)for(const n of e.layers){let e=!1;for(const r of n.inboundNodes)if(-1!==s.indexOf(r)){if(e){t=!1;break}e=!0}if(!t)break}return t}(e),a=["Layer (type)","Input Shape","Output shape","Param #"];let i;if(r?(t=t||90,n=n||[.32,.61,.89,1]):(t=t||115,n=n||[.24,.48,.7,.8,1]),n[n.length-1]<=1&&(n=n.map((e=>Math.floor(t*e)))),!r){a.push("Receives inputs"),i=[];for(const t in e.nodesByDepth)i.push(...e.nodesByDepth[t])}s("_".repeat(t)),$b(a,n,s),s("=".repeat(t));const o=e.layers;for(let e=0;e0&&(s=s.slice(0,s.length-1)+" "),s+=e[n],s=s.slice(0,t[n]),s+=" ".repeat(t[n]-s.length);n(s)}function Eb(e,t,n){let s,r;try{r=e.inboundNodes.map((e=>JSON.stringify(e.inputShapes))).join(",")}catch(e){r="multiple"}try{s=JSON.stringify(e.outputShape)}catch(e){s="multiple"}$b([`${e.name} (${e.getClassName()})`,r,s,e.countParams().toString()],t,n)}function Rb(e,t,n,s){let r,a;try{a=e.inboundNodes.map((e=>JSON.stringify(e.inputShapes))).join(",")}catch(e){a="multiple"}try{r=JSON.stringify(e.outputShape)}catch(e){r="multiple"}const i=[];for(const t of e.inboundNodes)if(!(null!=n&&n.length>0&&-1===n.indexOf(t)))for(let e=0;ee.name))}`);qm(this.outputs).length!==this.outputs.length&&console.warn(`The list of outputs passed to the model is redundant. All outputs should only appear once. Found: ${this.outputs.map((e=>e.name))}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(const e of this.outputs){const t=e.sourceLayer,n=e.nodeIndex,s=e.tensorIndex;this.outputLayers.push(t),this.outputLayersNodeIndices.push(n),this.outputLayersTensorIndices.push(s)}for(const e of this.inputs){const t=e.sourceLayer,n=e.nodeIndex,s=e.tensorIndex;Mm(0===n,"input layer has >1 nodes"),Mm(0===s,"input layer has >1 tensors"),this.inputLayers.push(t),this.inputLayersNodeIndices.push(n),this.inputLayersTensorIndices.push(s)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let t=0;te.shape)),this.internalOutputShapes=this.outputs.map((e=>e.shape));const t={},n={},s={},r={},a={},i=[],o=(e,t,n,s,r,l)=>{null!=s&&null!=r&&null!=l||(s=e.sourceLayer,r=e.nodeIndex,l=e.tensorIndex);const u=s.inboundNodes[r];if(-1!==n.indexOf(u))throw new Rm(`The tensor ${e.name} at layer "${s.name}" is part of a cycle.`);if(-1!==t.indexOf(u))return;this.containerNodes.add(Ob.nodeKey(s,r)),s.id in a||(a[s.id]=Object.keys(a).length),-1===n.indexOf(u)&&n.push(u);const c=u.inboundLayers.length;for(let e=0;e=0;)n.splice(n.indexOf(u),1);i.push(u)},l=[],u=[];for(const e of this.outputs)o(e,l,u);const c=i.slice().reverse();for(const e of c){n[e.id]=e,e.id in t||(t[e.id]=0);let a=t[e.id];const i=null==s[e.outboundLayer.id]?0:s[e.outboundLayer.id];a=Math.max(a,i),s[e.outboundLayer.id]=a,r[e.outboundLayer.id]=e.outboundLayer,t[e.id]=a;for(let s=0;sparseInt(e,10))).sort(jm);this.layers=[];for(const e of d){const t=p[e];t.sort(((e,t)=>{const n=a[e.id],s=a[t.id];return ns?1:0}));for(const e of t)e instanceof Ob&&this.internalContainerRefs.push(e),this.layers.push(e)}this.layersByDepth=p,d=Object.keys(h).map((e=>parseInt(e,10))).sort(jm);const f=this.inputs.slice(),m=[];for(const e of d)for(const t of h[e]){const e=t.outboundLayer;if(null!=e){for(const n of t.inputTensors)if(-1===f.indexOf(n))throw new Rm(`Graph disconnected: cannot obtain value for tensor ${n} at layer "${e.name}". The following previous layers were accessed without issue: ${m}`);for(const e of t.outputTensors)f.push(e);m.push(e.name)}}this.nodesByDepth=h;const g=this.layers.map((e=>e.name));for(const e of g){const t=g.filter((t=>t===e)).length;if(1!==t)throw new Rm(`The name "${e}" is used ${t} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(g))}this.outboundNodes=[],this.inboundNodes=[],new ky({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map((e=>null)),outputMasks:this.outputs.map((e=>null)),inputShapes:this.inputs.map((e=>e.shape)),outputShapes:this.outputs.map((e=>e.shape))}),this.built=!0,this._refCount=1}assertNotDisposed(){if(0===this._refCount)throw new Error(`Container '${this.name}' is already disposed.`)}dispose(){this.assertNotDisposed();const e={refCountAfterDispose:null,numDisposedVariables:0};if(0==--this._refCount){for(const t of this.layers)e.numDisposedVariables+=t.dispose().numDisposedVariables;for(const t of this.internalContainerRefs)e.numDisposedVariables+=t.dispose().numDisposedVariables}return e.refCountAfterDispose=this._refCount,e}get trainable(){return this.trainable_}set trainable(e){this.layers.forEach((t=>{t._trainableWeights.forEach((t=>t.trainable=e))})),this.trainable_=e}get trainableWeights(){if(this._trainableWeights.length>0)throw new Am("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let e=[];for(const t of this.layers)e=e.concat(t.trainableWeights);return e}get nonTrainableWeights(){const e=[];for(const t of this.layers)e.push(...t.nonTrainableWeights);if(!this.trainable){const t=[];for(const e of this.layers)t.push(...e.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){const n={};let s=0;for(const e of this.layers)for(const t of e.weights){if(null!=n[t.originalName])throw new Am(`Duplicate weight name: ${t.originalName}`);n[t.originalName]=t,s++}const r=[];for(const s in e){let a=s;if(null==n[s]){const e=s.split("/");a=e.slice(0,-2).concat([e[e.length-1]]).join("/")}if(null!=n[a])r.push([n[a],e[s]]);else if(t)throw new Am(`Provided weight data has no target variable: ${s}`);delete n[a]}if(t){const e=[];for(const t in n)e.push(t);if(e.length>0)throw new Am(`${e.length} of ${s} weights are not set: ${e}`)}by(r)}updatedConfig(){const e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${Db}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){const n=_b(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return Zi((()=>{e=Pm(e);const n=new Cy;for(let t=0;t{let n;return e=Pm(e),n=null==t?Om(null,e.length):Pm(t),this.runInternalGraph(e,n)[1]}))}computeOutputShape(e){const t=hy(e);if(t.length!==this.inputLayers.length)throw new Am(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);const n={};for(let e=0;eparseInt(e,10))).sort(jm);if(s.length>1)for(const e of s){const t=this.nodesByDepth[e];for(const e of t){const t=e.outboundLayer;if(-1!==this.inputLayers.map((e=>e.id)).indexOf(t.id))continue;const s=[];for(let t=0;tparseInt(e,10))).sort(jm);for(const e of s){const t=this.nodesByDepth[e];for(const e of t){const t=e.outboundLayer,s=e.inputTensors,r=e.outputTensors,a=new Array;for(const e of s)e.id in n&&a.push(n[e.id]);if(a.length===s.length){let s,i,o,l,u={};if(null!=e.callArgs&&(u=e.callArgs),1===a.length){const[e,n]=a[0];null==u.mask&&(u.mask=n),o=Pm(t.call(e,u)),l=Pm(t.computeMask(e,n)),s=[e],i=[n]}else s=a.map((e=>e[0])),i=a.map((e=>e[1])),null==u.mask&&(u.mask=i),o=Pm(t.call(s,u)),l=Pm(t.computeMask(s,i));if(t.activityRegularizer)throw new Fm("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let e=0;e{const e=[];for(const t of this.layers)for(let n=0;n0){const e=[];for(let n=0;n0&&e.apply(zm(n),s)}function l(e){const n=e.name,a=tb(e,null!=t.customObjects?t.customObjects:{});a.setFastWeightInitDuringBuild(s),r[n]=a;e.inboundNodes.forEach((e=>{if(!(e instanceof Array))throw new Am(`Corrupted configuration, expected array for nodeData: ${e}`);i(a,e)}))}const u=t.name,c=t.layers;for(const e of c)l(e);for(;!Km(a);)for(const e of c){const t=r[e.name];if(t.name in a){const e=a[t.name];delete a[t.name];for(const n of e)o(t,n)}}const h=[],p=[],d=t.inputLayers;for(const e of d){const t=e[0],n=e[1],s=e[2];Mm(t in r);const a=r[t].inboundNodes[n].outputTensors;h.push(a[s])}const f=t.outputLayers;for(const e of f){const t=e[0],n=e[1],s=e[2];Mm(t in r);const a=r[t].inboundNodes[n].outputTensors;p.push(a[s])}return new e({inputs:h,outputs:p,name:u})}get stateful(){if(this._stateful)throw new Am("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(const e of this.layers)if(e.stateful)return!0;return!1}resetStates(){Zi((()=>{this.layers.forEach((e=>{e.stateful&&e.resetStates()}))}))}}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function Mb(e,t,n){const s=t.length;if(null==e||Array.isArray(e)&&0===e.length)return t.map((e=>null));if(1===s)return Array.isArray(e)&&1===e.length?e:"object"==typeof e&&t[0]in e?[e[t[0]]]:[e];if(Array.isArray(e)){if(e.length!==s)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${s} outputs. Make sure a set of weights is provided for each model output.`);return e}if("object"==typeof e&&Object.keys(e).length>0&&"object"==typeof e[Object.keys(e)[0]]){const n=[];return t.forEach((t=>{t in e?n.push(e[t]):n.push(null)})),n}throw new Error(`The model has multiple (${s}) outputs, so ${n} must be either an array with ${s} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function Lb(e,t){return Mb(e,t,"classWeight")}async function zb(e,t,n,s){if(null!=t||null!=s)throw new Error("Support sampleWeight is not implemented yet");if(null!=n){const t=Zi((()=>{if(1===e.shape.length)return Ja(e);if(2===e.shape.length){if(e.shape[1]>1){return ho(e,1)}if(1===e.shape[1])return _o(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)})),s=Array.from(await t.data());Ji(t);const r=[];return s.forEach((e=>{if(null==n[e])throw new Error(`classWeight must contain all classes in the training data. The class ${e} exists in the data but not in classWeight`);r.push(n[e])})),Gc(r,"float32")}return null}function Pb(e,t){return zo(e,t)}function Bb(e,t){let n,s;const r=t;n=r.xs,s=r.ys,O(null!=n&&null!=s,(()=>`A Dataset iterator for fitDataset() is expected to generate objects of the form \`{xs: xVal, ys: yVal}\`, where the two values may be \`tf.Tensor\`, an array of Tensors, or a map of string to Tensor. The provided Dataset instead generates ${t}`));const a=Wb("input",e.inputNames,n),i=Wb("output",e.outputNames,s),o=a[0].shape[0];O(a.length===e.inputs.length,(()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${a.length} inputs. (Expected input keys: ${JSON.stringify(e.inputNames)})`)),O(i.length===e.outputs.length,(()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${i.length} outputs. (Expected output keys: ${JSON.stringify(e.outputNames)})`));for(let t=0;t`Batch size mismatch: input ${e.inputNames[t]} has ${a[t].shape[0]}; expected ${o} based on input ${e.inputNames[0]}.`));for(let t=0;t`Batch size mismatch: output ${e.outputNames[t]} has ${i[t].shape[0]}; expected ${o} based on input ${e.inputNames[0]}.`));return{xs:a,ys:i}}function Wb(e,t,n){if(n instanceof gr)return[n];if(Array.isArray(n))return O(n.length===t.length,(()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`)),n;{const s=[];for(const r of t){if(null==n[r])throw new Am(`The feature data generated by the dataset lacks the required ${e} key '${r}'.`);s.push(n[r])}return s}}async function Vb(e,t,n){const s=null!=n.batchesPerEpoch;if(O(null!=e.optimizer,(()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig).")),O(null!=n,(()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call.")),O(null!=n.epochs&&n.epochs>0&&Number.isInteger(n.epochs),(()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`)),O(!s||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),(()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`)),O(null==n.validationSplit,(()=>"`validationSplit` is not supported by `fitDataset()`. Use validationData instead.")),e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;try{const r=null!=n.validationData;let a,i;if(r)if(Ub(n.validationData))O(null==n.validationBatches||n.validationBatches>0&&Number.isInteger(n.validationBatches),(()=>`For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${n.validationBatches}`));else{const e=function(e){if(3===e.length)throw new Fm("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}(n.validationData);a=e.xs,i=e.ys}const o=e.makeTrainFunction(),l=e.getDedupedMetricsNames();let u;u=r?l.slice().concat(l.map((e=>"val_"+e))):l.slice();const c=Jy(n.callbacks,n.yieldEvery),h=null==n.verbose?1:n.verbose,{callbackList:p,history:d}=eb(c,h,n.epochs,null,null,function(e,t){let n=null;null!=t.batchesPerEpoch?n=t.batchesPerEpoch:Number.isFinite(e.size)&&(n=e.size);return n}(t,n),null,r,u);p.setModel(e),e.history=d,await p.onTrainBegin(),e.stopTraining_=!1;let f=null==n.initialEpoch?0:n.initialEpoch,m=await t.iterator();for(;f=n.batchesPerEpoch:t.done){if(r){let t;t=Ub(n.validationData)?Pm(await e.evaluateDataset(n.validationData,{batches:n.validationBatches})):Pm(e.evaluate(a,i,{batchSize:null==n.validationBatchSize?32:n.validationBatchSize,verbose:0}));for(let n=0;n0&&Number.isInteger(e),(()=>`batchSize is required to be a positive integer, but got ${e}`))}function Hb(e,t,n){return null==e?[null]:Array.isArray(e)?e.map((e=>$g(e,t,n-t))):$g(e,t,n-t)}function jb(e,t){return Zi((()=>null==e?null:Array.isArray(e)?e.map((e=>jb(e,t))):Mg(e,"int32"===t.dtype?t:Za(t,"int32"))))}function qb(e,t){const n=[];let s=0,r=null;for(;s=e&&(r=e),n.push([s,r]),s=r;return n}async function Kb(e,t,n,s={}){if(e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");let r,a,i,o,l,u,c,h,p;e.isTraining=!0;try{const d=null==s.batchSize?32:s.batchSize;Gb(d);const f=!1,m=await e.standardizeUserData(t,n,s.sampleWeight,s.classWeight,f,d);r=m[0],a=m[1],p=m[2];let g,y=!1;if(null!=s.validationData&&s.validationData.length>0){if(y=!0,2!==s.validationData.length)throw 3===s.validationData.length?new Fm("validationData including sample weights is not supported yet."):new Am(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${s.validationData} is invalid.`);l=s.validationData[0],u=s.validationData[1];const t=!0,n=await e.standardizeUserData(l,u,null,null,t,d);c=n[0],h=n[1],g=c.concat(h)}else if(null!=s.validationSplit&&s.validationSplit>0&&s.validationSplit<1){y=!0;const e=Math.floor(r[0].shape[0]*(1-s.validationSplit)),t=r[0].shape[0];c=Hb(r,e,t),i=r,r=Hb(r,0,e),h=Hb(a,e,t),o=a,a=Hb(a,0,e),g=c.concat(h)}else null!=s.validationSteps&&(y=!0);const b=r.concat(a).concat(p);e.checkTrainableWeightsConsistency();const x=e.makeTrainFunction(),w=e.getDedupedMetricsNames();let v,k;y?(e.makeTestFunction(),v=e.testFunction,k=w.slice().concat(w.map((e=>"val_"+e)))):(v=null,g=[],k=w.slice());const I=Jy(s.callbacks,s.yieldEvery),N=await async function(e,t,n,s,r,a,i,o,l,u,c,h,p,d,f){null==r&&(r=32),null==a&&(a=1),null==c&&(c=!0),null==p&&(p=0);let m=!1;if(null!=l&&null!=u&&(m=!0),null!=f&&(m=!0,null==d))throw new Am("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");const g=e.checkNumSamples(n,r,d,"steps_per_epoch");let y;null!=g&&(y=Ig(0,g)),null==i&&(i=1);const{callbackList:b,history:x}=eb(o,i,a,p,g,d,r,m,h);b.setModel(e),e.history=x,await b.onTrainBegin(),e.stopTraining_=!1;for(let i=p;i{const p=o[c][0],d=o[c][1],f=$g(i,p,d-p);h.batch=c,h.size=d-p;const g=jb(n,f),y=t(g);for(let e=0;en.push(e.id)));else if(null!=t)for(const e in t){const s=t[e];n.push(s.id)}const s=[];if(e instanceof gr)-1===n.indexOf(e.id)&&s.push(e);else if(Array.isArray(e))e.forEach((e=>{-1===n.indexOf(e.id)&&s.push(e)}));else if(null!=e)for(const t in e){const r=e[t];-1===n.indexOf(r.id)&&s.push(r)}s.forEach((e=>{e.isDisposed||e.dispose()}))}function Zb(e){return Array.isArray(e)}function Jb(e){return!
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function(e){return e instanceof gr}(e)&&!Zb(e)}function Qb(e,t,n,s=!0,r=""){if(null==t||0===t.length){if(null!=e){let t=!1;if(Zb(e)&&e.length>0)t=!0;else if(Jb(e)){for(const n in e)if(e.hasOwnProperty(n)){t=!0;break}}else t=!0;if(t)throw new Am(`Error when checking model ${r} expected no data, but got ${e}`)}return[]}if(null==e)return t.map((e=>null));let a;if(Jb(e)){a=[];for(const n of t){if(null==e[n])throw new Am(`No data provided for "${n}". Need data for each key in: ${t}`);a.push(e[n])}}else if(Zb(e)){if(e.length!==t.length)throw new Am(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the model expected. Expected to see ${t.length} Tensor(s), but instead got the following list of Tensor(s): ${e}`);a=e}else{if(t.length>1)throw new Am(`The model ${r} expects ${t.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${e.shape}`);a=[e]}if(a=Xb(a),null!=n)for(let e=0;e=0&&a!==o)throw new Am(`${r} expected a batch of elements where each example has shape [${n[e].slice(1,n[e].length)}] (i.e.,tensor shape [*,${n[e].slice(1,n[e].length)}]) but the ${r} received an input with ${i.shape[0]} examples, each with shape [${i.shape.slice(1,i.shape.length)}] (tensor shape [${i.shape}])`)}}return a}function ex(e,t,n,s=!0,r=""){let a;if(Array.isArray(e)){if(e.length!==t.length)throw new Am(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the the model expected. Expected to see ${t.length} Tensor(s), but instead got ${e.length} Tensors(s).`);a=e}else{if(t.length>1)throw new Am(`The model expects ${t.length} ${r} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(e.shape)}.`);a=[e]}if(null!=n)for(let e=0;eLp.adagrad(.01),Adadelta:()=>Lp.adadelta(1,.95,Sg()),Adam:()=>Lp.adam(.001,.9,.999,Sg()),Adamax:()=>Lp.adamax(.002,.9,.999,Sg(),0),RMSProp:()=>Lp.rmsprop(.001,.9,0,Sg()),SGD:()=>Lp.sgd(.01)};if(t.adagrad=t.Adagrad,t.adadelta=t.Adadelta,t.adam=t.Adam,t.adamax=t.Adamax,t.rmsprop=t.RMSProp,t.sgd=t.SGD,e in t)return t[e]();throw new Am(`Unknown Optimizer ${e}`)}(e.optimizer),this.isOptimizerOwned=!0;else{if(!(e.optimizer instanceof so))throw new Am("User-defined optimizer must be an instance of tf.Optimizer.");this.optimizer_=e.optimizer,this.isOptimizerOwned=!1}let t=[];if(Array.isArray(e.loss)||"string"==typeof e.loss||"function"==typeof e.loss)if(Array.isArray(e.loss)){if(e.loss.length!==this.outputs.length)throw new Am(`When passing an Array as loss, it should have one entry per model output. The model has ${this.outputs.length} output(s), but you passed loss=${e.loss}.`);const n=e.loss;t=n.map((e=>db(e)))}else{const n=db(e.loss);this.outputs.forEach((e=>{t.push(n)}))}else{e.loss=e.loss;for(const t in e.loss)if(-1===this.outputNames.indexOf(t))throw new Am(`Unknown entry in loss dictionary: "${t}". Only expected the following keys: ${this.outputNames}`);for(const n of this.outputNames)null==e.loss[n]&&console.warn(`Output "${n}" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${n} during training`),t.push(db(e.loss[n]))}this.lossFunctions=t,this.feedOutputNames=[],this.feedOutputShapes=[],this.feedLossFns=[];for(let e=0;e{for(let e=0;e1&&(this.metricsTensors.push([t,e]),this.metricsNames.push(this.outputNames[e]+"_loss"))}}));const s=function(e,t){if(null==e||Array.isArray(e)&&0===e.length)return t.map((e=>[]));let n;if("string"==typeof e||"function"==typeof e)n=[e];else{if(!Array.isArray(e)&&"object"!=typeof e)throw new TypeError(`Type of metrics argument not understood. Expected an string,function, Array, or Object, found: ${e}`);n=e}if(Array.isArray(n))return t.map((e=>n));{const e=[];for(const s of t){let t=n.hasOwnProperty(s)?n[s]:[];Array.isArray(t)||(t=[t]),e.push(t)}return e}}(e.metrics,this.outputNames),r=(e,t,n)=>{this.outputNames.length>1&&(t=this.outputNames[e]+"_"+t),this.metricsNames.push(t),this.metricsTensors.push([n,e])};fg("metric",(()=>{for(let e=0;e{let n,s,a;for(const i of t){if("string"==typeof i&&-1!==["accuracy","acc","crossentropy","ce"].indexOf(i)){const t=this.internalOutputShapes[e];let r;1===t[t.length-1]||this.lossFunctions[e]===ub?-1!==["accuracy","acc"].indexOf(i)?s=fb:-1!==["crossentropy","ce"].indexOf(i)&&(s=yb):this.lossFunctions[e]===lb?-1!==["accuracy","acc"].indexOf(i)?s=bb:-1!==["crossentropy","ce"].indexOf(i)&&(s=wb):-1!==["accuracy","acc"].indexOf(i)?s=mb:-1!==["crossentropy","ce"].indexOf(i)&&(s=xb),-1!==["accuracy","acc"].indexOf(i)?r="acc":-1!==["crossentropy","ce"].indexOf(i)&&(r="ce"),a=s,n=""+r}else{const e=kb(i);a=e,n=""+Ib(i)}let t;fg(n,(()=>{t=a})),r(e,n,t)}})(s[e])}})),this.collectedTrainableWeights=this.trainableWeights}checkTrainableWeightsConsistency(){null!=this.collectedTrainableWeights&&this.trainableWeights.length!==this.collectedTrainableWeights.length&&console.warn("Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?")}evaluate(e,t,n={}){const s=null==n.batchSize?32:n.batchSize;Gb(s);const r=this.standardizeUserDataXY(e,t,!0,s);try{const e=r[0].concat(r[1]);this.makeTestFunction();const t=this.testFunction;return zm(this.testLoop(t,e,s,n.verbose,n.steps))}finally{Yb(r[0],e),Yb(r[1],t)}}async evaluateDataset(e,t){return this.makeTestFunction(),async function(e,t,n){const s=null!=(n=n||{}).batches,r=e.testFunction;let a=[];if(n.verbose>0)throw new Fm("Verbose mode is not implemented yet.");O(!s||n.batches>0&&Number.isInteger(n.batches),(()=>`Test loop expects \`batches\` to be a positive integer, but received ${JSON.stringify(n.batches)}`));const i="function"==typeof t.next?t:await t.iterator();let o=0,l=0;for(;!s||l{if(t.value){const{xs:n,ys:s}=Bb(e,t.value),i=n.concat(s),u=Zi((()=>r(i)));if(Ji(i),0===l)for(let e=0;eoo(a[e],zo(c,t)))),l>0&&Ji(n)}Ji(u),o+=c,++l}return a})),t.done){s&&console.warn(`Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least \`batches\` batches (in this case, ${n.batches} batches). You may need to use the repeat() function when building your dataset.`);break}}for(let e=0;ee.name));for(let s=0;s0){const n=[];throw t.forEach(((t,s)=>{null==t&&n.push(e[s])})),new Am(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(n)}`)}return t}predictLoop(e,t=32,n=!1){return Zi((()=>{const s=this.checkNumSamples(e);if(n)throw new Fm("Verbose predictLoop() is not implemented yet.");const r=qb(s,t),a=this.outputs.map((e=>[]));for(let t=0;t{const n=r[t][0],s=r[t][1],a=Hb(e,n,s),i=[];if(Array.isArray(a))for(let e=0;ea[t].push(e)))}return zm(a.map((e=>Mo(e,0))))}))}predict(e,t={}){const n=Xb(e);ex(n,this.inputNames,this.feedInputShapes,!1);try{const e=null==t.batchSize?32:t.batchSize;return Gb(e),this.predictLoop(n,e)}finally{Yb(n,e)}}predictOnBatch(e){ex(e,this.inputNames,this.feedInputShapes,!0);const t=(Array.isArray(e)?e[0]:e).shape[0];return this.predictLoop(e,t)}standardizeUserDataXY(e,t,n=!0,s){if(null==this.optimizer_)throw new Rm("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");const r=[];for(let e=0;ee.shape[0])));n.sort();const s=qm(t.map((e=>e.shape[0])));if(s.sort(),n.length>1)throw new Am(`All input Tensors (x) should have the same number of samples. Got array shapes: ${JSON.stringify(e.map((e=>e.shape)))}`);if(s.length>1)throw new Am(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(t.map((e=>e.shape)))}`);if(n.length>0&&s.length>0&&!B(n,s))throw new Am(`Input Tensors should have the same number of samples as target Tensors. Found ${n[0]} input sample(s) and ${s[0]} target sample(s).`)}(e=Qb(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=Qb(t,this.feedOutputNames,r,!1,"target")),function(e,t,n){const s=[sb,ub,ob];for(let r=0;r0&&e[0].shape[0]%s!=0)throw new Am(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${s}. Found: ${e[0].shape[0]} sample(s).`);return[e,t]}async standardizeUserData(e,t,n,s,r=!0,a){const[i,o]=this.standardizeUserDataXY(e,t,r,a);if(null!=n)throw new Error("sample weight is not supported yet.");let l=null;if(null!=s){const e=Lb(s,this.outputNames);l=[];for(let t=0;t{const a=this.checkNumSamples(t,n,r,"steps"),i=[];if(s>0)throw new Fm("Verbose mode is not implemented yet.");if(null!=r)throw new Fm("steps mode in testLoop() is not implemented yet");{const s=qb(a,n),r=Gc(Ig(0,a));for(let n=0;n1){r+=`_${Lm(e.slice(0,n),s)}`}t.push(r)}return t}makeTrainFunction(){return e=>{const t=[],n=e.slice(0,this.inputs.length),s=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),r=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+2*this.outputs.length),a=[],i=this.collectedTrainableWeights.map((e=>e.read()));return[this.optimizer_.minimize((()=>{const e=[];for(let t=0;t1&&e{l=oo(l,e)})),l}),!0,i)].concat(a)}}makeTestFunction(){this.testFunction=e=>Zi((()=>{const t=[];let n;const s=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=[];for(let e=0;eBm(e)))}else{const t=Object.keys(this.loss);e={};const n=this.loss;for(const s of t){if("string"!=typeof n[s])throw new Error("Serialization of non-string loss is not supported.");e[s]=Bm(n[s])}}return e}getMetricIdentifiers(){if("string"==typeof this.metrics||"function"==typeof this.metrics)return[Bm(Ib(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map((e=>Bm(Ib(e))));{const e={};for(const t in this.metrics)e[t]=Bm(Ib(this.metrics[t]));return e}}getTrainingConfig(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}}loadTrainingConfig(e){if(null!=e.weighted_metrics)throw new Error("Loading weight_metrics is not supported yet.");if(null!=e.loss_weights)throw new Error("Loading loss_weights is not supported yet.");if(null!=e.sample_weight_mode)throw new Error("Loading sample_weight_mode is not supported yet.");const t=tb(Fb(e.optimizer_config));let n,s;if("string"==typeof e.loss)n=Wm(e.loss);else if(Array.isArray(e.loss))n=e.loss.map((e=>Wm(e)));else if(null!=e.loss){n={};for(const t in e.loss)n[t]=Wm(e.loss[t])}if(Array.isArray(e.metrics))s=e.metrics.map((e=>Wm(e)));else if(null!=e.metrics){s={};for(const t in e.metrics)s[t]=Wm(e.metrics[t])}this.compile({loss:n,metrics:s,optimizer:t})}async save(e,t){if("string"==typeof e){const t=ma(e);if(0===t.length)throw new Am(`Cannot find any save handlers for URL '${e}'`);if(t.length>1)throw new Am(`Found more than one (${t.length}) save handlers for URL '${e}'`);e=t[0]}if(null==e.save)throw new Am("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");const n=await Qr(this.getNamedWeights(t)),s={modelTopology:this.toJSON(null,!1),format:"layers-model",generatedBy:`TensorFlow.js tfjs-layers v${Db}`,convertedBy:null};if(null!=t&&t.includeOptimizer&&null!=this.optimizer){s.trainingConfig=this.getTrainingConfig();const e="optimizer",{data:t,specs:r}=await Qr(await this.optimizer.getWeights(),e);n.specs.push(...r),n.data=ra([n.data,t])}if(null!=this.userDefinedMetadata){const e=!0;Sb(this.userDefinedMetadata,this.name,e),s.userDefinedMetadata=this.userDefinedMetadata}return s.weightData=n.data,s.weightSpecs=n.specs,e.save(s)}setUserDefinedMetadata(e){Sb(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}}tx.className="Model",Ki(tx);class nx extends tx{}nx.className="Functional",Ki(nx);class sx extends tx{constructor(e){if(super({inputs:[],outputs:[]}),e=e||{},this.trainable=!0,this.built=!1,this.name=null!=e.name?e.name:sg("sequential_"),null!=e.layers)for(const t of e.layers)this.add(t)}checkShape(e){if(e.inboundNodes[0].outputTensors[0].shape.some((e=>e<0)))throw new Am(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){const t=e instanceof sx||e instanceof tx;let n;if(t){if(n=e,1!==n.outputs.length)throw new Am("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(1!==n.inputs.length)throw new Am("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.")}if(0===this.outputs.length){if(0===e.inboundNodes.length){if(null==e.batchInputShape)throw new Am("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");const t=function(e){if(null==e.batchShape&&null==e.shape)throw new Error("Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.");if(null!=e.batchShape&&null!=e.shape)throw new Am("Please provide either a `shape` or `batchShape` argument to Input, but not both.");let t=e.batchShape;null!=e.shape&&null==t&&(t=[null].concat(e.shape));let n=e.dtype;return null==n&&(n="float32"),new Ty({batchInputShape:t,name:e.name,dtype:n,sparse:e.sparse}).inboundNodes[0].outputTensors[0]}({batchShape:e.batchInputShape,dtype:e.dtype,name:e.name+"_input"});e.apply(t)}if(t)this.outputs=n.outputs,this.inputs=n.inputs;else{if(1!==e.inboundNodes.length)throw new Am(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${e.name} which has ${e.inboundNodes.length} pre-existing inbound connections.`);if(1!==e.inboundNodes[0].outputTensors.length)throw new Am("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[e.inboundNodes[0].outputTensors[0]],this.inputs=Sy(this.outputs[0])}this.inboundNodes=[],new ky({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:Om(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map((e=>e.shape)),outputShapes:this.outputs[0].shape})}else{const t=e.apply(this.outputs[0]);if(Array.isArray(t))throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[t],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(e),this.built=!1}pop(){if(0===this.layers.length)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),0===this.layers.length)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{const e=this.layers.length-1;this.layers[e].outboundNodes=[],this.outputs=[this.layers[e].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}}call(e,t){return null==this.model&&this.build(),this.model.call(e,t)}build(e){if(dy(e),0===this.inputs.length||0===this.outputs.length)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new tx({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0}countParams(){return this.built||this.build(),super.countParams()}summary(e,t,n=console.log){this.built||this.build(),super.summary(e,t,n)}setWeights(e){null==this.model&&this.build(),this.model.setWeights(e)}evaluate(e,t,n={}){if(!this.built)throw new Rm("The model needs to be compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new Rm("The model needs to be compiled before being used.");return this.model.evaluateDataset(e,t)}predict(e,t={}){return null==this.model&&this.build(),this.model.predict(e,t)}predictOnBatch(e){return null==this.model&&this.build(),this.model.predictOnBatch(e)}compile(e){this.build(),this.model.compile(e),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames}get optimizer(){return null==this.model?void 0:this.model.optimizer}set optimizer(e){this.model.optimizer=e}async fit(e,t,n={}){if(!this.built)throw new Rm("The model needs to be compiled before being used.");return this.model.fit(e,t,n)}async fitDataset(e,t){if(!this.built)throw new Rm("The model needs to be compiled before being used.");return this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},s=!1){let r,a={};if(t instanceof Array){if(null==t[0].className||"Merge"===t[0].className)throw new Am("Legacy serialization format not supported yet.");r=t}else O(null!=t.layers,(()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field.")),r=t.layers,delete t.layers,a=t;const i=new e(a);if(!(i instanceof sx))throw new Fm(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(const e of r){const t=tb(e,void 0,s);s&&t.setFastWeightInitDuringBuild(!0),i.add(t)}return i}set stopTraining(e){if(null==this.model)throw new Am("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(null==this.model)throw new Am("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){const e=[];for(const t of this.layers){const n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}}sx.className="Sequential",Ki(sx);
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class rx extends ji{getConfig(){return{}}}class ax extends rx{apply(e,t=1){return function(e,t=1){if(1!==t)throw new Fm(`Support for alpha values other than 1 (${t}) is not implemented yet.`);return $l(e)}(e,t)}}ax.className="elu",Ki(ax);class ix extends rx{apply(e){return kc(e)}}ix.className="selu",Ki(ix);class ox extends rx{apply(e){return dc(e)}}ox.className="relu",Ki(ox);class lx extends rx{apply(e){return Zi((()=>Du(6,dc(e))))}}lx.className="relu6",Ki(lx);class ux extends rx{apply(e){return e}}ux.className="linear",Ki(ux);class cx extends rx{apply(e){return Po(e)}}cx.className="sigmoid",Ki(cx);class hx extends rx{apply(e){return function(e){return Zi((()=>{const t=oo(.5,zo(.2,e));return Qo(t,0,1)}))}(e)}}hx.className="hardSigmoid",Ki(hx);class px extends rx{apply(e){return fu(e)}}px.className="softplus",Ki(px);class dx extends rx{apply(e){return function(e){return Zi((()=>vl(e,oo(ro(e),1))))}(e)}}dx.className="softsign",Ki(dx);class fx extends rx{apply(e){return Wo(e)}}fx.className="tanh",Ki(fx);class mx extends rx{apply(e,t=-1){return Fc(e,t)}}mx.className="softmax",Ki(mx);class gx extends rx{apply(e,t=-1){return yu(e,t)}}gx.className="logSoftmax",Ki(gx);class yx extends rx{apply(e,t=1){return Zi((()=>zo(Po(zo(e,t)),e)))}}yx.className="swish",Ki(yx);class bx extends rx{apply(e){return Zi((()=>zo(e,Wo(fu(e)))))}}function xx(e){return e.getClassName()}function wx(e,t={}){return Hm(e,qi.getMap().classNameMap,t,"activation")}function vx(e){if(null==e){const e={className:"linear",config:{}};return wx(e)}if("string"==typeof e){const t={};return t.className=e,t.config={},wx(t)}return e instanceof rx?e:wx(e)}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function kx(e){if(null!=e&&"object"!=typeof e)throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}bx.className="mish",Ki(bx);class Ix extends ji{}class Nx extends Ix{constructor(e){super(),kx(e),this.l1=null==e||null==e.l1?.01:e.l1,this.l2=null==e||null==e.l2?.01:e.l2,this.hasL1=0!==this.l1,this.hasL2=0!==this.l2}apply(e){return Zi((()=>{let t=Au([1]);return this.hasL1&&(t=oo(t,Ul(zo(this.l1,ro(e))))),this.hasL2&&(t=oo(t,Ul(zo(this.l2,Lg(e))))),_o(t,[])}))}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}}Nx.className="L1L2",Ki(Nx);const Sx={l1l2:"L1L2"};function Tx(e){return Um(e)}function Cx(e,t={}){return Hm(e,qi.getMap().classNameMap,t,"regularizer")}function $x(e){if(null==e)return null;if("string"==typeof e){return Cx({className:e in Sx?Sx[e]:e,config:{}})}return e instanceof Ix?e:Cx(e)}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class Ex extends Ny{constructor(e){super(null==e?{}:e),this.supportsMasking=!0,null!=e&&(this.maxValue=e.maxValue)}call(e,t){e=py(e);let n=dc(e);return null!=this.maxValue&&(n=Qo(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){const e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}}Ex.className="ReLU",Ki(Ex);class Rx extends Ny{constructor(e){super(null==e?{}:e),this.DEFAULT_ALPHA=.3,null==e&&(e={}),this.alpha=null==e.alpha?this.DEFAULT_ALPHA:e.alpha}call(e,t){const n=py(e);return iu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){const e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}}Rx.className="LeakyReLU",Ki(Rx);class Ax extends Ny{constructor(e){if(super(null==e?{}:e),this.DEFAULT_ALPHA_INITIALIZER="zeros",null==e&&(e={}),this.supportsMasking=!0,this.alphaInitializer=uy(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=$x(e.alphaRegularizer),this.alphaConstraint=Uy(e.alphaConstraint),null==e.sharedAxes)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else{if("number"!=typeof e.sharedAxes)throw new Am(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`);this.sharedAxes=[e.sharedAxes]}}build(e){const t=(e=dy(e)).slice(1);if(null!=this.sharedAxes)for(const e of this.sharedAxes)t[e-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);const n={};if(null!=this.sharedAxes)for(let t=1;t(cg(t),"channelsFirst"===t?ah(e,[0,2,3,1]):e)))}function Px(e,t){return Zi((()=>(cg(t),"channelsFirst"===t?ah(e,[0,2,3,4,1]):e)))}function Bx(e,t,n,s=1,r="valid",a,i=1){return Zi((()=>{if(null==a&&(a="channelsLast"),cg(a),3!==e.shape.length)throw new Am(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(3!==t.shape.length)throw new Am(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(null!=n&&1!==n.shape.length)throw new Am(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if("channelsFirst"===a&&(e=ah(e,[0,2,1])),"causal"===r)throw new Fm("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=al(e,t,s,"same"===r?"same":"valid","NWC",i);return null!=n&&(o=Pg(o,n)),o}))}function Wx(e,t,n,s=[1,1],r="valid",a,i,o=null){return Zi((()=>{if(null==a&&(a="channelsLast"),cg(a),3!==e.rank&&4!==e.rank)throw new Am(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(3!==t.rank&&4!==t.rank)throw new Am(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=zx(e,a);if("causal"===r)throw new Fm("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=kh({x:l,filter:t,strides:s,pad:"same"===r?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),"channelsFirst"===a&&(l=ah(l,[0,3,1,2])),l}))}function Vx(e,t,n,s=[1,1,1],r="valid",a,i){return Zi((()=>{if(null==a&&(a="channelsLast"),cg(a),4!==e.rank&&5!==e.rank)throw new Am(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(4!==t.rank&&5!==t.rank)throw new Am(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=Px(e,a);if("causal"===r)throw new Fm("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=ll(o,t,s,"same"===r?"same":"valid","NDHWC",i),null!=n&&(o=Pg(o,n)),"channelsFirst"===a&&(o=ah(o,[0,4,1,2,3])),o}))}Dx.className="Softmax",Ki(Dx);class Ux extends Ny{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Ux.verifyArgs(t),this.rank=e,Zm(this.rank,"rank"),1!==this.rank&&2!==this.rank&&3!==this.rank)throw new Fm(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Ox(t.kernelSize,e,"kernelSize"),this.strides=Ox(null==t.strides?1:t.strides,e,"strides"),this.padding=null==t.padding?"valid":t.padding,hg(this.padding),this.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,cg(this.dataFormat),this.activation=vx(t.activation),this.useBias=null==t.useBias||t.useBias,this.biasInitializer=uy(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Uy(t.biasConstraint),this.biasRegularizer=$x(t.biasRegularizer),this.activityRegularizer=$x(t.activityRegularizer),this.dilationRate=Ox(null==t.dilationRate?1:t.dilationRate,e,"dilationRate"),1===this.rank&&Array.isArray(this.dilationRate)&&1!==this.dilationRate.length)throw new Am(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(2===this.rank){if("number"==typeof this.dilationRate)this.dilationRate=[this.dilationRate,this.dilationRate];else if(2!==this.dilationRate.length)throw new Am(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(3===this.rank)if("number"==typeof this.dilationRate)this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(3!==this.dilationRate.length)throw new Am(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}static verifyArgs(e){if(Mm("kernelSize"in e,"required key 'kernelSize' not in config"),"number"!=typeof e.kernelSize&&!Ym(e.kernelSize,"number",1,3))throw new Am(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){const e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:xx(this.activation),useBias:this.useBias,biasInitializer:ly(this.biasInitializer),biasRegularizer:Tx(this.biasRegularizer),activityRegularizer:Tx(this.activityRegularizer),biasConstraint:Wy(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}}class Gx extends Ux{constructor(e,t){super(e,t),this.kernel=null,Gx.verifyArgs(t),this.filters=t.filters,Zm(this.filters,"filters"),this.kernelInitializer=uy(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Uy(t.kernelConstraint),this.kernelRegularizer=$x(t.kernelRegularizer)}build(e){e=dy(e);const t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new Am(`The channel dimension of the input should be defined. Found ${e[t]}`);const n=e[t],s=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return Zi((()=>{let t;e=py(e);const n=null==this.bias?null:this.bias.read(),s=Qm(this.activation.getClassName());if(null!=s&&2===this.rank)t=Wx(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(1===this.rank)t=Bx(e,this.kernel.read(),n,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(2===this.rank)t=Wx(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate);else{if(3!==this.rank)throw new Fm("convolutions greater than 3D are not implemented yet.");t=Vx(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate)}null!=this.activation&&(t=this.activation.apply(t))}return t}))}computeOutputShape(e){e=dy(e);const t=[],n="channelsLast"===this.dataFormat?e.slice(1,e.length-1):e.slice(2);for(let e=0;e 0 but got ${JSON.stringify(e.filters)}`)}}class Hx extends Gx{constructor(e){super(2,e),Hx.verifyArgs(e)}getConfig(){const e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if("number"!=typeof e.kernelSize&&!Ym(e.kernelSize,"number",1,2))throw new Am(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}}Hx.className="Conv2D",Ki(Hx);class jx extends Gx{constructor(e){super(3,e),jx.verifyArgs(e)}getConfig(){const e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if("number"!=typeof e.kernelSize&&(!Array.isArray(e.kernelSize)||1!==e.kernelSize.length&&3!==e.kernelSize.length))throw new Am(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}}jx.className="Conv3D",Ki(jx);class qx extends Hx{constructor(e){if(super(e),this.inputSpec=[new xy({ndim:4})],"same"!==this.padding&&"valid"!==this.padding)throw new Am(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(4!==(e=dy(e)).length)throw new Am("Input should have rank 4; Received input shape: "+JSON.stringify(e));const t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new Am("The channel dimension of the inputs should be defined. Found `None`.");const n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new xy({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return Zi((()=>{let t=py(e);if(4!==t.shape.length)throw new Am(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${t.shape.length}`);const n=t.shape,s=n[0];let r,a;"channelsFirst"===this.dataFormat?(r=2,a=3):(r=1,a=2);const i=n[r],o=n[a],l=this.kernelSize[0],u=this.kernelSize[1],c=this.strides[0],h=this.strides[1],p=[s,Lx(i,c,l,this.padding),Lx(o,h,u,this.padding),this.filters];"channelsLast"!==this.dataFormat&&(t=ah(t,[0,2,3,1]));let d=ol(t,this.kernel.read(),p,this.strides,this.padding);return"channelsLast"!==this.dataFormat&&(d=ah(d,[0,3,1,2])),null!=this.bias&&(d=Pg(d,this.bias.read(),this.dataFormat)),null!=this.activation&&(d=this.activation.apply(d)),d}))}computeOutputShape(e){const t=(e=dy(e)).slice();let n,s,r;"channelsFirst"===this.dataFormat?(n=1,s=2,r=3):(n=3,s=1,r=2);const a=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[s]=Lx(t[s],o,a,this.padding),t[r]=Lx(t[r],l,i,this.padding),t}getConfig(){const e=super.getConfig();return delete e.dilationRate,e}}qx.className="Conv2DTranspose",Ki(qx);class Kx extends jx{constructor(e){if(super(e),this.inputSpec=[new xy({ndim:5})],"same"!==this.padding&&"valid"!==this.padding)throw new Am(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(5!==(e=dy(e)).length)throw new Am("Input should have rank 5; Received input shape: "+JSON.stringify(e));const t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new Am("The channel dimension of the inputs should be defined. Found `None`.");const n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new xy({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return Zi((()=>{let t=py(e);if(5!==t.shape.length)throw new Am(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${t.shape.length}`);const n=t.shape,s=n[0];let r,a,i;"channelsFirst"===this.dataFormat?(i=2,r=3,a=4):(i=1,r=2,a=3);const o=n[i],l=n[r],u=n[a],c=this.kernelSize[0],h=this.kernelSize[1],p=this.kernelSize[2],d=this.strides[0],f=this.strides[1],m=this.strides[2],g=[s,Lx(o,d,c,this.padding),Lx(l,f,h,this.padding),Lx(u,m,p,this.padding),this.filters];"channelsLast"!==this.dataFormat&&(t=ah(t,[0,2,3,4,1]));let y=cl(t,this.kernel.read(),g,this.strides,this.padding);return"channelsLast"!==this.dataFormat&&(y=ah(y,[0,4,1,2,3])),null!==this.bias&&(y=Pg(y,this.bias.read(),this.dataFormat)),null!==this.activation&&(y=this.activation.apply(y)),y}))}computeOutputShape(e){const t=(e=dy(e)).slice();let n,s,r,a;"channelsFirst"===this.dataFormat?(n=1,s=2,r=3,a=4):(n=4,s=1,r=2,a=3);const i=this.kernelSize[0],o=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],c=this.strides[1],h=this.strides[2];return t[n]=this.filters,t[s]=Lx(t[s],u,i,this.padding),t[r]=Lx(t[r],c,o,this.padding),t[a]=Lx(t[a],h,l,this.padding),t}getConfig(){const e=super.getConfig();return delete e.dilationRate,e}}Kx.className="Conv3DTranspose",Ki(Kx);class Xx extends Gx{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,null==t.filters)throw new Am("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(null!=t.kernelInitializer||null!=t.kernelRegularizer||null!=t.kernelConstraint)throw new Am("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(null!=t.padding&&"same"!==t.padding&&"valid"!==t.padding)throw new Am(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=null==t.depthMultiplier?1:t.depthMultiplier,this.depthwiseInitializer=uy(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=$x(t.depthwiseRegularizer),this.depthwiseConstraint=Uy(t.depthwiseConstraint),this.pointwiseInitializer=uy(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=$x(t.pointwiseRegularizer),this.pointwiseConstraint=Uy(t.pointwiseConstraint)}build(e){if((e=dy(e)).length{let t;if(e=py(e),1===this.rank)throw new Fm("1D separable convolution is not implemented yet.");return 2===this.rank&&("channelsFirst"===this.dataFormat&&(e=ah(e,[0,2,3,1])),t=Ic(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(t=Pg(t,this.bias.read(),this.dataFormat)),null!=this.activation&&(t=this.activation.apply(t)),"channelsFirst"===this.dataFormat&&(t=ah(t,[0,3,1,2])),t}))}getConfig(){const e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=ly(this.depthwiseInitializer),e.pointwiseInitializer=ly(this.pointwiseInitializer),e.depthwiseRegularizer=Tx(this.depthwiseRegularizer),e.pointwiseRegularizer=Tx(this.pointwiseRegularizer),e.depthwiseConstraint=Wy(this.depthwiseConstraint),e.pointwiseConstraint=Wy(this.pointwiseConstraint),e}}Xx.className="SeparableConv";class Yx extends Xx{constructor(e){super(2,e)}}Yx.className="SeparableConv2D",Ki(Yx);class Zx extends Gx{constructor(e){super(1,e),Zx.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){const e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if("number"!=typeof e.kernelSize&&!Ym(e.kernelSize,"number",1,1))throw new Am(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}}Zx.className="Conv1D",Ki(Zx);class Jx extends Ny{constructor(e){super(e),"number"==typeof e.cropping?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:"number"==typeof e.cropping[0]?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=void 0===e.dataFormat?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return"channelsFirst"===this.dataFormat?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return Zi((()=>{if(e=py(e),"channelsLast"===this.dataFormat){const t=Rg(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Rg(t,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}{const t=Rg(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Rg(t,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}}))}getConfig(){const e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}}Jx.className="Cropping2D",Ki(Jx);class Qx extends Ny{constructor(e){var t;super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=null==e.size?this.DEFAULT_SIZE:e.size,this.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,cg(this.dataFormat),this.interpolation=null==e.interpolation?"nearest":e.interpolation,t=this.interpolation,Xm(ag,"InterpolationFormat",t)}computeOutputShape(e){if("channelsFirst"===this.dataFormat){const t=null==e[2]?null:this.size[0]*e[2],n=null==e[3]?null:this.size[1]*e[3];return[e[0],e[1],t,n]}{const t=null==e[1]?null:this.size[0]*e[1],n=null==e[2]?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return Zi((()=>{let t=py(e);const n=t.shape;if("channelsFirst"===this.dataFormat){t=ah(t,[0,2,3,1]);const e=this.size[0]*n[2],s=this.size[1]*n[3],r="nearest"===this.interpolation?Np.resizeNearestNeighbor(t,[e,s]):Np.resizeBilinear(t,[e,s]);return ah(r,[0,3,1,2])}{const e=this.size[0]*n[1],s=this.size[1]*n[2];return"nearest"===this.interpolation?Np.resizeNearestNeighbor(t,[e,s]):Np.resizeBilinear(t,[e,s])}}))}getConfig(){const e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}}Qx.className="UpSampling2D",Ki(Qx);class ew extends Ux{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=null==e.depthMultiplier?1:e.depthMultiplier,this.depthwiseInitializer=uy(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Uy(e.depthwiseConstraint),this.depthwiseRegularizer=$x(e.depthwiseRegularizer)}build(e){if((e=dy(e)).length<4)throw new Am(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);const t="channelsFirst"===this.dataFormat?1:3;if(null==e[t]||e[t]<0)throw new Am(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);const n=e[t],s=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",s,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return Zi((()=>{let t=
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function(e,t,n=[1,1],s="valid",r,a){return Zi((()=>{null==r&&(r="channelsLast"),cg(r);let i=zx(e,r);if(4!==e.rank)throw new Am(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(4!==t.rank)throw new Am(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=yl(i,t,n,"same"===s?"same":"valid","NHWC",a),"channelsFirst"===r&&(i=ah(i,[0,3,1,2])),i}))}(e=py(e),this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(t=Pg(t,this.bias.read(),this.dataFormat)),null!=this.activation&&(t=this.activation.apply(t)),t}))}computeOutputShape(e){e=dy(e);const t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2],s="channelsFirst"===this.dataFormat?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Mx(t,this.kernelSize[0],this.padding,this.strides[0]),a=Mx(n,this.kernelSize[1],this.padding,this.strides[1]);return"channelsFirst"===this.dataFormat?[e[0],s,r,a]:[e[0],r,a,s]}getConfig(){const e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=ly(this.depthwiseInitializer),e.depthwiseRegularizer=Tx(this.depthwiseRegularizer),e.depthwiseConstraint=Wy(this.depthwiseRegularizer),e}}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function tw(e,t,n,s){if(Array.isArray(e)){if(null!=t||null!=n)throw new Am("When inputs is an array, neither initialState or constants should be provided");null!=s&&(n=e.slice(e.length-s,e.length),e=e.slice(0,e.length-s)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(e){return null==e||Array.isArray(e)?e:[e]}return{inputs:e,initialState:t=r(t),constants:n=r(n)}}function nw(e,t,n,s=!1,r,a,i=!1,o=!1){return Zi((()=>{const l=t.shape.length;if(l<3)throw new Am(`Input should be at least 3D, but is ${l}D.`);const u=[1,0].concat(Ig(2,l));if(t=ah(t,u),null!=a)throw new Fm("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),null!=r&&((r=Za(Za(r,"bool"),"float32")).rank===l-1&&(r=Kl(r,-1)),r=ah(r,u)),s&&(t=mc(t,0),null!=r&&(r=mc(r,0)));const c=[];let h,p=n;const d=t.shape[0],f=Qc(t);let m,g;null!=r&&(m=Qc(r));for(let t=0;te(n,p)));if(null==r)h=s[0],p=s[1];else{const e=Zi((()=>{const e=m[t],n=gu(Vu(e),e);return{output:oo(zo(s[0],e),zo(p[0],n)),newStates:p.map(((t,r)=>oo(zo(s[1][r],e),zo(t,n))))}}));h=e.output,p=e.newStates}o&&c.push(h)}if(o){g=Bc(c,1)}return[h,g,p]}))}ew.className="DepthwiseConv2D",Ki(ew);class sw extends Ny{constructor(e){let t;if(super(e),null==e.cell)throw new Am("cell property is missing for the constructor of RNN.");if(t=Array.isArray(e.cell)?new hw({cells:e.cell}):e.cell,null==t.stateSize)throw new Am("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=null!=e.returnSequences&&e.returnSequences,this.returnState=null!=e.returnState&&e.returnState,this.goBackwards=null!=e.goBackwards&&e.goBackwards,this._stateful=null!=e.stateful&&e.stateful,this.unroll=null!=e.unroll&&e.unroll,this.supportsMasking=!0,this.inputSpec=[new xy({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(null==this.states_){return Ig(0,Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1).map((e=>null))}return this.states_}setStates(e){this.states_=e}computeOutputShape(e){cy(e)&&(e=e[0]);let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);const n=t[0];let s;if(s=this.returnSequences?[e[0],e[1],n]:[e[0],n],this.returnState){const n=[];for(const s of t)n.push([e[0],s]);return[s].concat(n)}return s}computeMask(e,t){return Zi((()=>{Array.isArray(t)&&(t=t[0]);const e=this.returnSequences?t:null;if(this.returnState){const t=this.states.map((e=>null));return[e].concat(t)}return e}))}get states(){if(null==this.states_){const e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;ne.shape[e.shape.length-1])),r))throw new Am(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=r.map((e=>new xy({shape:[null,e]})));this.stateful&&this.resetStates()}resetStates(e,t=!1){Zi((()=>{if(!this.stateful)throw new Em("Cannot call resetStates() on an RNN Layer that is not stateful.");const n=this.inputSpec[0].shape[0];if(null==n)throw new Am("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(null==this.states_)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map((e=>Au([n,e]))):this.states_=[Au([n,this.cell.stateSize])];else if(null==e)Ji(this.states_),null!=this.keptStates&&(Ji(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map((e=>Au([n,e]))):this.states_[0]=Au([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new Am(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);!0===t?this.keptStates.push(this.states_.slice()):Ji(this.states_);for(let t=0;tQi(e.clone())))}))}apply(e,t){let n=null==t?null:t.initialState,s=null==t?null:t.constants;null==t&&(t={});const r=tw(e,n,s,this.numConstants);e=r.inputs,n=r.initialState,s=r.constants;let a=[],i=[];if(null!=n){t.initialState=n,a=a.concat(n),this.stateSpec=[];for(const e of n)this.stateSpec.push(new xy({shape:e.shape}));i=i.concat(this.stateSpec)}null!=s&&(t.constants=s,a=a.concat(s),this.numConstants=s.length);if(a[0]instanceof wy){const n=[e].concat(a),s=this.inputSpec.concat(i),r=this.inputSpec;this.inputSpec=s;const o=super.apply(n,t);return this.inputSpec=r,o}return super.apply(e,t)}call(e,t){return Zi((()=>{const n=null==t?null:t.mask,s=null==t?null:t.training;let r=null==t?null:t.initialState;e=py(e),null==r&&(r=this.stateful?this.states_:this.getInitialState(e));const a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==a)throw new Am(`RNN Layer has ${a} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");const i={training:s},o=nw(((e,t)=>{const n=this.cell.call([e].concat(t),i);return[n[0],n.slice(1)]}),e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],c=o[2];this.stateful&&this.resetStates(c,s);const h=this.returnSequences?u:l;return this.returnState?[h].concat(c):h}))}getInitialState(e){return Zi((()=>{let t=Au(e.shape);return t=Ul(t,[1,2]),t=Cg(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map((e=>e>1?_g(t,[1,e]):t)):this.cell.stateSize>1?[_g(t,[1,this.cell.stateSize])]:[t]}))}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),null!=this.cell&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){const e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};null!=this.numConstants&&(t.numConstants=this.numConstants);const n=this.cell.getConfig();return this.getClassName()===sw.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){const s=tb(t.cell,n);return new e(Object.assign(t,{cell:s}))}}sw.className="RNN",Ki(sw);class rw extends Ny{}class aw extends rw{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Zm(this.units,"units"),this.activation=vx(null==e.activation?this.DEFAULT_ACTIVATION:e.activation),this.useBias=null==e.useBias||e.useBias,this.kernelInitializer=uy(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=uy(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=uy(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=$x(e.kernelRegularizer),this.recurrentRegularizer=$x(e.recurrentRegularizer),this.biasRegularizer=$x(e.biasRegularizer),this.kernelConstraint=Uy(e.kernelConstraint),this.recurrentConstraint=Uy(e.recurrentConstraint),this.biasConstraint=Uy(e.biasConstraint),this.dropout=vg([1,kg([0,null==e.dropout?0:e.dropout])]),this.recurrentDropout=vg([1,kg([0,null==e.recurrentDropout?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=dy(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return Zi((()=>{if(2!==e.length)throw new Am(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];const s=null!=t.training&&t.training;let r;0Vu(e),rate:this.dropout,training:s,dropoutFunc:this.dropoutFunc})),0Vu(n),rate:this.recurrentDropout,training:s,dropoutFunc:this.dropoutFunc}));const a=this.dropoutMask,i=this.recurrentDropoutMask;r=Og(null!=a?zo(e,a):e,this.kernel.read()),null!=this.bias&&(r=Pg(r,this.bias.read())),null!=i&&(n=zo(n,i));let o=oo(r,Og(n,this.recurrentKernel.read()));return null!=this.activation&&(o=this.activation.apply(o)),[o,o]}))}getConfig(){const e=super.getConfig(),t={units:this.units,activation:xx(this.activation),useBias:this.useBias,kernelInitializer:ly(this.kernelInitializer),recurrentInitializer:ly(this.recurrentInitializer),biasInitializer:ly(this.biasInitializer),kernelRegularizer:Tx(this.kernelRegularizer),recurrentRegularizer:Tx(this.recurrentRegularizer),biasRegularizer:Tx(this.biasRegularizer),activityRegularizer:Tx(this.activityRegularizer),kernelConstraint:Wy(this.kernelConstraint),recurrentConstraint:Wy(this.recurrentConstraint),biasConstraint:Wy(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}}aw.className="SimpleRNNCell",Ki(aw);class iw extends sw{constructor(e){e.cell=new aw(e),super(e)}call(e,t){return Zi((()=>{null!=this.cell.dropoutMask&&(Ji(this.cell.dropoutMask),this.cell.dropoutMask=null),null!=this.cell.recurrentDropoutMask&&(Ji(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);const n=null==t?null:t.mask,s=null==t?null:t.training,r=null==t?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})}))}static fromConfig(e,t){return new e(t)}}iw.className="SimpleRNN",Ki(iw);class ow extends rw{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new Am("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Zm(this.units,"units"),this.activation=vx(void 0===e.activation?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=vx(void 0===e.recurrentActivation?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=null==e.useBias||e.useBias,this.kernelInitializer=uy(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=uy(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=uy(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=$x(e.kernelRegularizer),this.recurrentRegularizer=$x(e.recurrentRegularizer),this.biasRegularizer=$x(e.biasRegularizer),this.kernelConstraint=Uy(e.kernelConstraint),this.recurrentConstraint=Uy(e.recurrentConstraint),this.biasConstraint=Uy(e.biasConstraint),this.dropout=vg([1,kg([0,null==e.dropout?0:e.dropout])]),this.recurrentDropout=vg([1,kg([0,null==e.recurrentDropout?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){const t=(e=dy(e))[e.length-1];this.kernel=this.addWeight("kernel",[t,3*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,3*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[3*this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return Zi((()=>{if(2!==e.length)throw new Am(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);const n=null!=t.training&&t.training;let s=e[1];e=e[0],0Vu(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0Vu(s),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));const r=this.dropoutMask,a=this.recurrentDropoutMask;let i,o,l;0{null!=this.cell.dropoutMask&&(Ji(this.cell.dropoutMask),this.cell.dropoutMask=null),null!=this.cell.recurrentDropoutMask&&(Ji(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);const n=null==t?null:t.mask,s=null==t?null:t.training,r=null==t?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})}))}static fromConfig(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)}}lw.className="GRU",Ki(lw);class uw extends rw{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Zm(this.units,"units"),this.activation=vx(void 0===e.activation?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=vx(void 0===e.recurrentActivation?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=null==e.useBias||e.useBias,this.kernelInitializer=uy(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=uy(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=uy(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=$x(e.kernelRegularizer),this.recurrentRegularizer=$x(e.recurrentRegularizer),this.biasRegularizer=$x(e.biasRegularizer),this.kernelConstraint=Uy(e.kernelConstraint),this.recurrentConstraint=Uy(e.recurrentConstraint),this.biasConstraint=Uy(e.biasConstraint),this.dropout=vg([1,kg([0,null==e.dropout?0:e.dropout])]),this.recurrentDropout=vg([1,kg([0,null==e.recurrentDropout?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;const n=(e=dy(e))[e.length-1];let s;if(this.kernel=this.addWeight("kernel",[n,4*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,4*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){if(this.unitForgetBias){const e=this.biasInitializer,n=this.units;s=new((t=class extends Gg{apply(t,s){const r=e.apply([n]),a=(new jg).apply([n]),i=e.apply([2*n]);return Fg(Fg(r,a),i)}}).className="CustomInit",t)}else s=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.units],null,s,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return Zi((()=>{const n=null!=t.training&&t.training;if(3!==e.length)throw new Am(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let s=e[1];const r=e[2];e=e[0],0Vu(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0Vu(s),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));const a=this.dropoutMask,i=this.recurrentDropoutMask;let o,l,u,c;0{null!=this.cell.dropoutMask&&(Ji(this.cell.dropoutMask),this.cell.dropoutMask=null),null!=this.cell.recurrentDropoutMask&&(Ji(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);const n=null==t?null:t.mask,s=null==t?null:t.training,r=null==t?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})}))}static fromConfig(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)}}cw.className="LSTM",Ki(cw);class hw extends rw{constructor(e){super(e),this.cells=e.cells}get stateSize(){const e=[];for(const t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return Zi((()=>{let n=e.slice(1);const s=[];for(const e of this.cells.slice().reverse())Array.isArray(e.stateSize)?s.push(n.splice(0,e.stateSize.length)):s.push(n.splice(0,1));s.reverse();const r=[];let a;for(let i=0;i{fg(`RNNCell_${s}`,(()=>{n.build(e),t=Array.isArray(n.stateSize)?n.stateSize[0]:n.stateSize,e=[e[0],t]}))})),this.built=!0}getConfig(){const e=super.getConfig(),t={cells:this.cells.map((e=>({className:e.getClassName(),config:e.getConfig()})))};return Object.assign({},e,t)}static fromConfig(e,t,n={}){const s=[];for(const e of t.cells)s.push(tb(e,n));return new e({cells:s})}get trainableWeights(){if(!this.trainable)return[];const e=[];for(const t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){const e=[];for(const t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){const t=[];for(const e of this.cells)t.push(...e.trainableWeights);return t.concat(e)}return e}getWeights(){const e=[];for(const t of this.cells)e.push(...t.weights);return yy(e)}setWeights(e){const t=[];for(const n of this.cells){const s=n.weights.length,r=e.splice(s);for(let e=0;enull!=a?a(t(),n):Bg(t(),n),o=()=>Wg(i,t,s);if(!r||r<=1)return Qi(o().clone());return Array(r).fill(void 0).map(o).map((e=>Qi(e.clone())))}hw.className="StackedRNNCells",Ki(hw);
+/**
+ * @license
+ * Copyright 2020 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+var dw=function(e,t){var n={};for(var s in e)Object.prototype.hasOwnProperty.call(e,s)&&t.indexOf(s)<0&&(n[s]=e[s]);if(null!=e&&"function"==typeof Object.getOwnPropertySymbols){var r=0;for(s=Object.getOwnPropertySymbols(e);r{if(null!=this.cell.dropoutMask&&(Ji(this.cell.dropoutMask),this.cell.dropoutMask=null),null!=this.cell.recurrentDropoutMask&&(Ji(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new Am("ConvRNN2D cell does not support constants");const n=null==t?null:t.mask,s=null==t?null:t.training,r=null==t?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})}))}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return Zi((()=>{const{stateSize:t}=this.cell,n=e.shape,s=this.computeSingleOutputShape(n),r=Au([s[0],...s.slice(2)]);return Array.isArray(t)?Array(t.length).fill(r):[r]}))}resetStates(e,t=!1){Zi((()=>{if(!this.stateful)throw new Em("Cannot call resetStates() on an RNN Layer that is not stateful.");const n=this.inputSpec[0].shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)];if(null==n[0])throw new Am("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(null==this.getStates())Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map((()=>Au(r))):this.states_=[Au(r)];else if(null==e)Ji(this.states_),null!=this.keptStates&&(Ji(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map((()=>Au(r))):this.states_[0]=Au(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new Am(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):Ji(this.states_);for(let t=0;tQi(e.clone())))}))}computeSingleOutputShape(e){const{dataFormat:t,filters:n,kernelSize:s,padding:r,strides:a,dilationRate:i}=this.cell,o="channelsFirst"===t,l=e[o?3:2],u=e[o?4:3],c=Mx(l,s[0],r,a[0],i[0]),h=Mx(u,s[1],r,a[1],i[1]);return[...e.slice(0,2),...o?[n,c,h]:[c,h,n]]}}fw.className="ConvRNN2D";class mw extends uw{constructor(e){const{filters:t,kernelSize:n,strides:s,padding:r,dataFormat:a,dilationRate:i}=e;super(Object.assign({},e,{units:t})),this.filters=t,Zm(this.filters,"filters"),this.kernelSize=Ox(n,2,"kernelSize"),this.kernelSize.forEach((e=>Zm(e,"kernelSize"))),this.strides=Ox(s||1,2,"strides"),this.strides.forEach((e=>Zm(e,"strides"))),this.padding=r||"valid",hg(this.padding),this.dataFormat=a||"channelsLast",cg(this.dataFormat),this.dilationRate=Ox(i||1,2,"dilationRate"),this.dilationRate.forEach((e=>Zm(e,"dilationRate")))}build(e){var t;e=dy(e);const n="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[n])throw new Am(`The channel dimension of the input should be defined. Found ${e[n]}`);const s=e[n],r=this.kernelSize.concat([s,4*this.filters]);this.kernel=this.addWeight("kernel",r,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);const a=this.kernelSize.concat([this.filters,4*this.filters]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",a,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let e;if(this.unitForgetBias){const n=this.biasInitializer,s=this.filters;e=new((t=class extends Gg{apply(e,t){return Ag([n.apply([s]),Fu([s]),n.apply([2*s])])}}).className="CustomInit",t)}else e=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.filters],null,e,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return Zi((()=>{if(3!==e.length)throw new Am(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);const n=t.training||!1,s=e[0],r=e[1],a=e[2];0Vu(s),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));const i=this.dropoutMask,o=(e,t,n)=>t&&t[n]?zo(t[n],e):e;let l=o(s,i,0),u=o(s,i,1),c=o(s,i,2),h=o(s,i,3);0Vu(r),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));const p=this.recurrentDropoutMask;let d=o(r,p,0),f=o(r,p,1),m=o(r,p,2),g=o(r,p,3);const[y,b,x,w]=Mc(this.kernel.read(),4,3),[v,k,I,N]=this.useBias?Mc(this.bias.read(),4):[null,null,null,null];l=this.inputConv(l,y,v,this.padding),u=this.inputConv(u,b,k,this.padding),c=this.inputConv(c,x,I,this.padding),h=this.inputConv(h,w,N,this.padding);const[S,T,C,$]=Mc(this.recurrentKernel.read(),4,3);d=this.recurrentConv(d,S),f=this.recurrentConv(f,T),m=this.recurrentConv(m,C),g=this.recurrentConv(g,$);const E=this.recurrentActivation.apply(oo(l,d)),R=this.recurrentActivation.apply(oo(u,f)),A=oo(zo(R,a),zo(E,this.activation.apply(oo(c,m)))),F=zo(this.recurrentActivation.apply(oo(h,g)),this.activation.apply(A));return[F,F,A]}))}getConfig(){const e=super.getConfig(),{units:t}=e,n=dw(e,["units"]),s={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,s)}inputConv(e,t,n,s){const r=rl(e,t,this.strides,s||"valid","channelsFirst"===this.dataFormat?"NCHW":"NHWC",this.dilationRate);return n?Pg(r,n,this.dataFormat):r}recurrentConv(e,t){return rl(e,t,1,"same","channelsFirst"===this.dataFormat?"NCHW":"NHWC")}}mw.className="ConvLSTM2DCell",Ki(mw);class gw extends fw{constructor(e){const t=new mw(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}}gw.className="ConvLSTM2D",Ki(gw);
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class yw extends Ny{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(null==this.noiseShape)return this.noiseShape;const t=e.shape,n=[];for(let e=0;e{this.invokeCallHook(e,t);const n=py(e);if(0Bg(n,this.rate,s,this.seed)),(()=>n),e)}return e}))}getConfig(){const e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}}yw.className="Dropout",Ki(yw);class bw extends yw{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){const t=e.shape;return[t[0],1,t[2]]}}bw.className="SpatialDropout1D",Ki(bw);class xw extends Ny{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",null==e.batchInputShape&&null==e.inputShape&&null!=e.inputDim){let t=null;null!=e.batchSize&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Zm(this.units,"units"),this.activation=vx(e.activation),null!=e.useBias&&(this.useBias=e.useBias),this.kernelInitializer=uy(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=uy(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Uy(e.kernelConstraint),this.biasConstraint=Uy(e.biasConstraint),this.kernelRegularizer=$x(e.kernelRegularizer),this.biasRegularizer=$x(e.biasRegularizer),this.activityRegularizer=$x(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){const t=(e=dy(e))[e.length-1];null==this.kernel&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){const t=(e=dy(e)).slice();return t[t.length-1]=this.units,t}call(e,t){return Zi((()=>{this.invokeCallHook(e,t);const n=py(e),s=Qm(this.activation.getClassName());let r;return null!=s?r=Og(n,this.kernel.read(),s,this.bias?this.bias.read():null):(r=Og(n,this.kernel.read()),null!=this.bias&&(r=Pg(r,this.bias.read())),null!=this.activation&&(r=this.activation.apply(r))),r}))}getConfig(){const e={units:this.units,activation:xx(this.activation),useBias:this.useBias,kernelInitializer:ly(this.kernelInitializer),biasInitializer:ly(this.biasInitializer),kernelRegularizer:Tx(this.kernelRegularizer),biasRegularizer:Tx(this.biasRegularizer),activityRegularizer:Tx(this.activityRegularizer),kernelConstraint:Wy(this.kernelConstraint),biasConstraint:Wy(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}}xw.className="Dense",Ki(xw);class ww extends Ny{constructor(e){super(e=e||{}),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=dy(e);for(const t of e.slice(1))if(null==t)throw new Am(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],wg(e,1)]}call(e,t){return Zi((()=>{this.invokeCallHook(e,t);let n=py(e);if("channelsFirst"===this.dataFormat&&n.rank>1){const e=[0];for(let t=2;t{this.invokeCallHook(e,t);const n=py(e);return this.activation.apply(n)}))}getConfig(){const e={activation:xx(this.activation)},t=super.getConfig();return Object.assign(e,t),e}}vw.className="Activation",Ki(vw);class kw extends Ny{constructor(e){super(e),this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return Zi((()=>function(e,t){return Zi((()=>{if(2!==e.shape.length)throw new Am(`repeat() expects a rank-2 tensor, but received a rank-${e.shape.length} tensor.`);return _g(Cg(e,1),[1,t,1])}))}(e=py(e),this.n)))}getConfig(){const e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}}kw.className="RepeatVector",Ki(kw);class Iw extends Ny{constructor(e){super(e),this.targetShape=e.targetShape;for(let e=0;e{this.invokeCallHook(e,t);const n=py(e),s=n.shape,r=s.slice(0,1).concat(this.fixUnknownDimension(s.slice(1),this.targetShape));return _o(n,r)}))}getConfig(){const e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}}Iw.className="Reshape",Ki(Iw);class Nw extends Ny{constructor(e){if(super(e),null==e.dims)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);const t=Ig(1,e.dims.length+1);if(!B(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new xy({ndim:this.dims.length+1})]}computeOutputShape(e){const t=(e=dy(e)).slice();return this.dims.forEach(((n,s)=>{t[s+1]=e[n]})),t}call(e,t){return ah(py(e),this.dimsIncludingBatch)}getConfig(){const e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}}Nw.className="Permute",Ki(Nw);class Sw extends Ny{constructor(e){super(null==e?{}:e),this.supportsMasking=!0,this.maskValue=null!=e?null==e.maskValue?0:e.maskValue:0}computeOutputShape(e){return e}getConfig(){const e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){const n=py(e);return co(Bu(n,this.maskValue),-1)}call(e,t){return Zi((()=>{this.invokeCallHook(e,t);const n=py(e),s=co(Bu(n,this.maskValue),-1,!0);return zo(n,Za(s,n.dtype))}))}}Sw.className="Masking",Ki(Sw);
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class Tw extends Ny{constructor(e){if(super(e),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",null==e.batchInputShape&&null==e.inputShape){let t=null;null!=e.batchSize&&(t=e.batchSize),null==e.inputLength?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(Pm(e.inputLength))}this.inputDim=e.inputDim,Zm(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Zm(this.outputDim,"outputDim"),this.embeddingsInitializer=uy(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=$x(e.embeddingsRegularizer),this.activityRegularizer=$x(e.activityRegularizer),this.embeddingsConstraint=Uy(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return Zi((()=>this.maskZero?(e=py(e),Bu(e,Nl(e))):null))}computeOutputShape(e){if(e=dy(e),null==this.inputLength)return[...e,this.outputDim];const t=Pm(this.inputLength);if(t.length!==e.length-1)throw new Am(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let s=0;s{this.invokeCallHook(e,t);let n=py(e);"int32"!==n.dtype&&(n=Tg(n,"int32"));const s=Mg(this.embeddings.read(),_o(n,[n.size]));return _o(s,dy(this.computeOutputShape(n.shape)))}))}getConfig(){const e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:ly(this.embeddingsInitializer),embeddingsRegularizer:Tx(this.embeddingsRegularizer),activityRegularizer:Tx(this.activityRegularizer),embeddingsConstraint:Wy(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}}Tw.className="Embedding",Ki(Tw);
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class Cw extends Ny{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new Fm}computeElementwiseOpOutputShape(e,t){if(null==e||null==t)return null;if(e.length1)throw new Am(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=null==e[0]?null:e[0].slice(1);for(let t=1;te.length));-1===e.indexOf(null)&&1===qm(s).length?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return Zi((()=>{if(this.reshapeRequired){const t=[],n=e.map((e=>e.rank));if(-1===n.indexOf(null)){const s=kg(n);for(let n of e){const e=n.rank;for(let t=0;t1){const r=Ig(1,e).concat([0]);t.push(ah(s,r)),n=!0}else t.push(s)}let s=this.mergeFunction(t);const r=s.rank;if(n)if(null==r){const e=s.shape,t=e[e.length-1],n=[t].concat(e.slice(0,e.length-1));s=_o(ah(_o(s,[-1,t]),[1,0]),n)}else if(r>1){const e=[r-1].concat(Ig(0,r-1));s=ah(s,e)}return s}}return this.mergeFunction(e)}))}computeOutputShape(e){let t;t=null==e[0]?null:e[0].slice(1);for(let n=1;n{if(null==t)return null;if(!Array.isArray(t))throw new Am("`mask` should be an Array");if(!Array.isArray(e))throw new Am("`inputs` should be an Array");if(t.length!==e.length)throw new Am(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every((e=>null==e)))return null;let n=(t=t.map((e=>null==e?e:Kl(e,0))))[0];for(let e=1;e{let t=e[0].clone();for(let n=1;n{let t=e[0].clone();for(let n=1;n{let t=e[0].clone();for(let n=1;n{let t=e[0];for(let n=1;n{let t=e[0];for(let n=1;n1)throw new Am("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return Zi((()=>Ag(e,this.axis)))}computeOutputShape(e){if(!Array.isArray(e)||!Array.isArray(e[0]))throw new Am("A `Concatenate` layer should be called on a list of inputs.");const t=e,n=t[0].slice(),s=this.axis<0?n.length+this.axis:this.axis;for(const e of t.slice(1)){if(null==n[s]||null==e[s]){n[s]=null;break}n[s]+=e[s]}return n}computeMask(e,t){if(null==t)return null;if(!Array.isArray(t))throw new Am("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new Am("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new Am(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return Zi((()=>{let n=!0;if(t.forEach((e=>{null==e||(n=!1)})),n)return null;const s=[];for(let n=0;n"A `Dot` layer should be called on a list of exactly 2 inputs."));const t=e[0],n=e[1];if(t.length>3||n.length>3)throw new Fm("Dot layer does not support tensors of 4D or higher rank yet.");const s=this.interpretAxes(t,n);if(t[s[0]]!==n[s[1]])throw new Am(`Dimension incompatibility: ${t[s[0]]} !== ${n[s[1]]}`)}mergeFunction(e){if(2!==e.length)throw new Am(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t,n=e[0],s=e[1];return t=Array.isArray(this.axes)?this.axes.map(((t,n)=>Dw(t,e[n].shape.length))):[Dw(this.axes,n.shape.length),Dw(this.axes,s.shape.length)],this.normalize&&(n=nb(n,t[0]),s=nb(s,t[1])),function(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new Fm("batchDot is not implemented for tensors of 4D or higher rank yet");if(O(e.shape.length>=2,(()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`)),O(e.shape.length>=2,(()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`)),"number"==typeof n&&(n=[n,n]),"complex64"===e.dtype||"complex64"===t.dtype)throw new Fm("batchDot is not implemented for complex64-type Tensors yet.");const s=e.shape.length,r=t.shape.length;null==n&&(n=[s-1,r-2]);const a=n;return Zi((()=>{let n,i;if(s>r){n=s-r;const e=[];for(let t=0;ts){n=r-s;const t=[];for(let e=0;e0){let e;e=s>r?s+r-3:s-1;const t=[];for(let s=e;s"A `Dot` layer should be called on a list of exactly 2 inputs."));const t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new Fm("Dot layer does not support tensors of 4D or higher rank yet.");const s=this.interpretAxes(t,n);t.splice(s[0],1),n.splice(s[1],1),n.splice(0,1);const r=t.concat(n);return 1===r.length&&r.push(1),r}computeMask(e,t){return null}getConfig(){const e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}}Ow.className="Dot",Ki(Ow);
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class Mw extends Ny{constructor(e){super(e),this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){const e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return Zi((()=>{this.invokeCallHook(e,t);const n=py(e);return Wg((()=>oo(Dg(n.shape,0,this.stddev),n)),(()=>n),t.training||!1)}))}}Mw.className="GaussianNoise",Ki(Mw);class Lw extends Ny{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){const e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return Zi((()=>{this.invokeCallHook(e,t);const n=py(e);if(this.rate>0&&this.rate<1){return Wg((()=>{const e=Math.sqrt(this.rate/(1-this.rate));return zo(n,Dg(n.shape,1,e))}),(()=>n),t.training||!1)}return n}))}}Lw.className="GaussianDropout",Ki(Lw);class zw extends Ny{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||py(e).shape}computeOutputShape(e){return e}getConfig(){const e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return Zi((()=>{if(this.rate<1&&this.rate>0){const n=this._getNoiseShape(e),s=()=>{const t=py(e),s=-1.7580993408473766;let r=tu(uc(n),this.rate);r=Tg(r,"float32");const a=((1-this.rate)*(1+this.rate*s**2))**-.5,i=-a*s*this.rate,o=oo(zo(t,r),zo(oo(r,-1),s));return oo(zo(o,a),i)};return Wg(s,(()=>py(e)),t.training||!1)}return e}))}}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function Pw(e,t,n,s,r,a=.001){let i;if(2===e.rank)i=Ho(e,t,n,s,r,a);else if(3===e.rank)i=jo(e,t,n,s,r,a);else{if(4!==e.rank)throw new Fm(`batchNormalization is not implemented for array of rank ${e.rank} yet`);i=qo(e,t,n,s,r,a)}return i}function Bw(e,t,n,s,r=.001){return B(s.slice().sort(),Ig(0,e.rank-1))?function(e,t,n,s,r=.001){return Zi((()=>{const a=Lu(e,s),i=a.mean,o=a.variance;return[Pw(e,i,o,n,t,r),i,o]}))}(e,t,n,s,r):function(e,t,n,s,r=.001){return Zi((()=>{const a=Lu(e,s),i=a.mean,o=a.variance,l=[];for(const t of Ig(0,e.rank))-1!==s.indexOf(t)?l.push(1):l.push(e.shape[t]);const u=_o(i,l),c=_o(o,l),h=null==t?null:_o(t,l),p=null==n?null:_o(n,l);return[Pw(e,u,c,p,h,r),i,o]}))}(e,t,n,s,r)}zw.className="AlphaDropout",Ki(zw);class Ww extends Ny{constructor(e){null==e&&(e={}),super(e),this.supportsMasking=!0,this.axis=null==e.axis?-1:e.axis,this.momentum=null==e.momentum?.99:e.momentum,this.epsilon=null==e.epsilon?.001:e.epsilon,this.center=null==e.center||e.center,this.scale=null==e.scale||e.scale,this.betaInitializer=uy(e.betaInitializer||"zeros"),this.gammaInitializer=uy(e.gammaInitializer||"ones"),this.movingMeanInitializer=uy(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=uy(e.movingVarianceInitializer||"ones"),this.betaConstraint=Uy(e.betaConstraint),this.gammaConstraint=Uy(e.gammaConstraint),this.betaRegularizer=$x(e.betaRegularizer),this.gammaRegularizer=$x(e.gammaRegularizer)}build(e){e=dy(e);const t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(null==n)throw new Am(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new xy({ndim:e.length,axes:{[t]:n}})];const s=[n];this.scale&&(this.gamma=this.addWeight("gamma",s,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",s,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",s,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",s,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return Zi((()=>{const n=null!=t.training&&t.training,s=py(e),r=s.shape,a=r.length,i=Ig(0,a),o=this.axis>=0?this.axis:this.axis+a;i.splice(o,1);const l=Om(1,a);l[o]=r[o];const u=i.slice();u.sort();const c=!B(u,Ig(0,a).slice(0,a-1));if(!n)return(()=>{if(c){const e=_o(this.movingMean.read(),l),t=_o(this.movingVariance.read(),l),n=this.center?_o(this.beta.read(),l):null,r=this.scale?_o(this.gamma.read(),l):null;return Pw(s,e,t,n,r,this.epsilon)}return Pw(s,this.movingMean.read(),this.movingVariance.read(),null==this.beta?null:this.beta.read(),null==this.gamma?null:this.gamma.read(),this.epsilon)})();const[h,p,d]=Bw(s,this.gamma.read(),this.beta.read(),i,this.epsilon),f=(e,t,n)=>{Zi((()=>{const s=1-n,r=e.read(),a=zo(gu(r,t),s);e.write(gu(r,a))}))};return(()=>{f(this.movingMean,p,this.momentum),f(this.movingVariance,d,this.momentum)})(),h}))}getConfig(){const e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:ly(this.betaInitializer),gammaInitializer:ly(this.gammaInitializer),movingMeanInitializer:ly(this.movingMeanInitializer),movingVarianceInitializer:ly(this.movingVarianceInitializer),betaRegularizer:Tx(this.betaRegularizer),gammaRegularizer:Tx(this.gammaRegularizer),betaConstraint:Wy(this.betaConstraint),gammaConstraint:Wy(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}}Ww.className="BatchNormalization",Ki(Ww);class Vw extends Ny{constructor(e){if(null==e&&(e={}),super(e),this.axis=null==e.axis?-1:e.axis,"number"==typeof this.axis){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else{if(!Array.isArray(this.axis))throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);for(const e of this.axis)if(!Number.isInteger(e))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}this.epsilon=null==e.epsilon?.001:e.epsilon,this.center=null==e.center||e.center,this.scale=null==e.scale||e.scale,this.betaInitializer=uy(e.betaInitializer||"zeros"),this.gammaInitializer=uy(e.gammaInitializer||"ones"),this.betaRegularizer=$x(e.betaRegularizer),this.gammaRegularizer=$x(e.gammaRegularizer),this.supportsMasking=!0}build(e){const t=(e=dy(e)).length;"number"==typeof this.axis&&(this.axis=[this.axis]);for(let e=0;e=t)throw new Error(`Invalid axis: ${e}`);if(this.axis.length!==qm(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);const n=this.axis.map((t=>e[t])),s=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,s):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,s):this.beta=null,this.built=!0}call(e,t){const n=py(e),s=n.shape,r=s.length;return Zi((()=>{let{mean:e,variance:t}=Lu(n,this.axis,!0);const a=Om(1,r);for(const e of this.axis)a[e]=s[e];const i=e=>null!=e&&e.shape.length!==r?_o(e,a):e;let o=this.scale?i(this.gamma.read()):null,l=this.center?i(this.beta.read()):null;const u=[],c=[];for(let e=0;e=0?e[2]+this.padding[0][0]+this.padding[0][1]:null,n=null!=e[3]&&e[3]>=0?e[3]+this.padding[1][0]+this.padding[1][1]:null,[e[0],e[1],t,n]):(t=null!=e[1]&&e[1]>=0?e[1]+this.padding[0][0]+this.padding[0][1]:null,n=null!=e[2]&&e[2]>=0?e[2]+this.padding[1][0]+this.padding[1][1]:null,[e[0],t,n,e[3]])}call(e,t){return Zi((()=>function(e,t,n){return Zi((()=>{if(4!==e.rank)throw new Am(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(null==t&&(t=[[1,1],[1,1]]),2!==t.length||2!==t[0].length||2!==t[1].length)throw new Am("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(null==n&&(n="channelsLast"),"channelsLast"!==n&&"channelsFirst"!==n)throw new Am(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let s;return s="channelsFirst"===n?[[0,0],[0,0],t[0],t[1]]:[[0,0],t[0],t[1],[0,0]],Gu(e,s)}))}(py(e),this.padding,this.dataFormat)))}getConfig(){const e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}}
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+function Gw(e,t,n,s,r,a){return Zi((()=>{let i;cg(r),pg(a),hg(s),null==n&&(n=[1,1]),null==s&&(s="valid"),null==r&&(r="channelsLast"),null==a&&(a="max"),e=zx(e,r);const o="same"===s?"same":"valid";return i="max"===a?Tu(e,t,n,o):Do(e,t,n,o),"channelsFirst"===r&&(i=ah(i,[0,3,1,2])),i}))}function Hw(e,t,n,s,r,a){return Zi((()=>{let i;cg(r),pg(a),hg(s),null==n&&(n=[1,1,1]),null==s&&(s="valid"),null==r&&(r="channelsLast"),null==a&&(a="max"),e=Px(e,r);const o="same"===s?"same":"valid";return i="max"===a?Cu(e,t,n,o):Oo(e,t,n,o),"channelsFirst"===r&&(i=ah(i,[0,4,1,2,3])),i}))}Uw.className="ZeroPadding2D",Ki(Uw);class jw extends Ny{constructor(e){if(null==e.poolSize&&(e.poolSize=2),super(e),"number"==typeof e.poolSize)this.poolSize=[e.poolSize];else{if(!Array.isArray(e.poolSize)||1!==e.poolSize.length||"number"!=typeof e.poolSize[0])throw new Am(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);this.poolSize=e.poolSize}if(Zm(this.poolSize,"poolSize"),null==e.strides)this.strides=this.poolSize;else if("number"==typeof e.strides)this.strides=[e.strides];else{if(!Array.isArray(e.strides)||1!==e.strides.length||"number"!=typeof e.strides[0])throw new Am(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);this.strides=e.strides}Zm(this.strides,"strides"),this.padding=null==e.padding?"valid":e.padding,hg(this.padding),this.inputSpec=[new xy({ndim:3})]}computeOutputShape(e){const t=Mx((e=dy(e))[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return Zi((()=>{this.invokeCallHook(e,t),e=Cg(py(e),2);const n=this.poolingFunction(py(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Pc(n,[2])}))}getConfig(){const e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}}class qw extends jw{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return cg(r),hg(s),Gw(e,t,n,s,r,"max")}}qw.className="MaxPooling1D",Ki(qw);class Kw extends jw{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return cg(r),hg(s),Gw(e,t,n,s,r,"avg")}}Kw.className="AveragePooling1D",Ki(Kw);class Xw extends Ny{constructor(e){if(null==e.poolSize&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],null==e.strides)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(2!==e.strides.length)throw new Am(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Zm(this.poolSize,"poolSize"),Zm(this.strides,"strides"),this.padding=null==e.padding?"valid":e.padding,this.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,cg(this.dataFormat),hg(this.padding),this.inputSpec=[new xy({ndim:4})]}computeOutputShape(e){e=dy(e);let t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2];return t=Mx(t,this.poolSize[0],this.padding,this.strides[0]),n=Mx(n,this.poolSize[1],this.padding,this.strides[1]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return Zi((()=>(this.invokeCallHook(e,t),this.poolingFunction(py(e),this.poolSize,this.strides,this.padding,this.dataFormat))))}getConfig(){const e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}}class Yw extends Xw{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return cg(r),hg(s),Gw(e,t,n,s,r,"max")}}Yw.className="MaxPooling2D",Ki(Yw);class Zw extends Xw{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return cg(r),hg(s),Gw(e,t,n,s,r,"avg")}}Zw.className="AveragePooling2D",Ki(Zw);class Jw extends Ny{constructor(e){if(null==e.poolSize&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],null==e.strides)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(3!==e.strides.length)throw new Am(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Zm(this.poolSize,"poolSize"),Zm(this.strides,"strides"),this.padding=null==e.padding?"valid":e.padding,this.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,cg(this.dataFormat),hg(this.padding),this.inputSpec=[new xy({ndim:5})]}computeOutputShape(e){e=dy(e);let t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2],s="channelsFirst"===this.dataFormat?e[4]:e[3];return t=Mx(t,this.poolSize[0],this.padding,this.strides[0]),n=Mx(n,this.poolSize[1],this.padding,this.strides[1]),s=Mx(s,this.poolSize[2],this.padding,this.strides[2]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,n,s]:[e[0],t,n,s,e[4]]}call(e,t){return Zi((()=>(this.invokeCallHook(e,t),this.poolingFunction(py(e),this.poolSize,this.strides,this.padding,this.dataFormat))))}getConfig(){const e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}}class Qw extends Jw{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return cg(r),hg(s),Hw(e,t,n,s,r,"max")}}Qw.className="MaxPooling3D",Ki(Qw);class ev extends Jw{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return cg(r),hg(s),Hw(e,t,n,s,r,"avg")}}ev.className="AveragePooling3D",Ki(ev);class tv extends Ny{constructor(e){super(e),this.inputSpec=[new xy({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Fm}}class nv extends tv{constructor(e){super(e||{})}call(e,t){return Zi((()=>{const t=py(e);return Ru(t,1)}))}}nv.className="GlobalAveragePooling1D",Ki(nv);class sv extends tv{constructor(e){super(e||{})}call(e,t){return Zi((()=>{const t=py(e);return zl(t,1)}))}}sv.className="GlobalMaxPooling1D",Ki(sv);class rv extends Ny{constructor(e){super(e),this.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,cg(this.dataFormat),this.inputSpec=[new xy({ndim:4})]}computeOutputShape(e){return"channelsLast"===this.dataFormat?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Fm}getConfig(){const e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}}class av extends rv{call(e,t){return Zi((()=>{const t=py(e);return"channelsLast"===this.dataFormat?Ru(t,[1,2]):Ru(t,[2,3])}))}}av.className="GlobalAveragePooling2D",Ki(av);class iv extends rv{call(e,t){return Zi((()=>{const t=py(e);return"channelsLast"===this.dataFormat?zl(t,[1,2]):zl(t,[2,3])}))}}iv.className="GlobalMaxPooling2D",Ki(iv);
+/**
+ * @license
+ * Copyright 2018 Google LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class ov extends Ny{constructor(e){super(e),this.layer=e.layer}build(e){this.built=!0}get trainable(){return null!=this.layer&&this.layer.trainable}set trainable(e){null!=this.layer&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){const e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),null!=this.layer&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){const s=tb(t.layer,n);delete t.layer;const r={layer:s};return Object.assign(r,t),new e(r)}}class lv extends ov{constructor(e){super(e),this.supportsMasking=!0}build(e){if((e=dy(e)).length<3)throw new Am(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];const t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){const t=[(e=dy(e))[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),s=e[1];return[n[0],s].concat(n.slice(1))}call(e,t){return Zi((()=>nw(((e,n)=>[py(this.layer.call(e,t)),[]]),e=py(e),[],!1,null,null,!1,!0)[1]))}}lv.className="TimeDistributed",Ki(lv);class uv extends ov{constructor(e){super(e);const t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=tb(n),t.goBackwards=!0!==t.goBackwards;const s={};var r;if(s.className=e.layer.getClassName(),s.config=t,this.backwardLayer=tb(s),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=void 0===e.mergeMode?"concat":e.mergeMode,r=this.mergeMode,Xm(lg,"BidirectionalMergeMode",r),e.weights)throw new Fm("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,null!=this.forwardLayer&&(this.forwardLayer.trainable=e),null!=this.backwardLayer&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){const t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t,n,s,r=this.forwardLayer.computeOutputShape(e);return Array.isArray(r)&&Array.isArray(r[0])||(r=[r]),this.returnState?(s=r.slice(1),t=r[0]):t=r[0],"concat"===this.mergeMode?(t[t.length-1]*=2,n=[t]):n=null==this.mergeMode?[t,t.slice()]:[t],this.returnState?null==this.mergeMode?n.concat(s).concat(s.slice()):[t].concat(s).concat(s.slice()):zm(n)}apply(e,t){let n=null==t?null:t.initialState,s=null==t?null:t.constants;null==t&&(t={});const r=tw(e,n,s,this.numConstants);if(e=r.inputs,n=r.initialState,s=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(null==n||0===n.length)&&null==s)return super.apply(e,t);const a=[],i=[];if(null!=n){const e=n.length;if(e%2>0)throw new Am("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,a.push(...n);const s=n.map((e=>new xy({shape:e.shape})));this.forwardLayer.stateSpec=s.slice(0,e/2),this.backwardLayer.stateSpec=s.slice(e/2),i.push(...s)}if(null!=s)throw new Fm("Support for constants in Bidirectional layers is not implemented yet.");const o=a[0]instanceof wy;for(const e of a)if(e instanceof wy!==o)throw new Am("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){const n=[e].concat(a),s=this.inputSpec.concat(i),r=this.inputSpec;this.inputSpec=s;const o=super.apply(n,t);return this.inputSpec=r,o}return super.apply(e,t)}call(e,t){return Zi((()=>{const n=t.initialState;let s,r,a,i;if(null==n)s=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{const a=n.slice(0,n.length/2),i=n.slice(n.length/2);s=this.forwardLayer.call(e,Object.assign(t,{initialState:a})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:i}))}return this.returnState&&(Array.isArray(s)&&(a=s.slice(1).concat(r.slice(1))),s=s[0],r=r[0]),this.returnSequences&&(r=mc(r,1)),"concat"===this.mergeMode?i=Ag([s,r]):"sum"===this.mergeMode?i=oo(s,r):"ave"===this.mergeMode?i=zo(.5,oo(s,r)):"mul"===this.mergeMode?i=zo(s,r):null==this.mergeMode&&(i=[s,r]),this.returnState?null==this.mergeMode?i.concat(a):[i].concat(a):i}))}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){fg(this.forwardLayer.name,(()=>{this.forwardLayer.build(e)})),fg(this.backwardLayer.name,(()=>{this.backwardLayer.build(e)})),this.built=!0}computeMask(e,t){let n;if(Array.isArray(t)&&(t=t[0]),n=this.returnSequences?null==this.mergeMode?[t,t]:t:null==this.mergeMode?[null,null]:null,this.returnState){const e=this.forwardLayer.states.map((e=>null));return Array.isArray(n)?n.concat(e).concat(e):[n].concat(e).concat(e)}return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),null!=this.forwardLayer&&this.forwardLayer.setFastWeightInitDuringBuild(e),null!=this.backwardLayer&&this.backwardLayer.setFastWeightInitDuringBuild(e)}getConfig(){const e={mergeMode:this.mergeMode},t=super.getConfig();return Object.assign(e,t),e}static fromConfig(e,t){const n=tb(t.layer);if(delete t.layer,null!=t.numConstants)throw new Fm("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");const s=t;return s.layer=n,new e(s)}}uv.className="Bidirectional",Ki(uv);
+/**
+ * @license
+ * Copyright 2022 CodeSmith LLC
+ *
+ * Use of this source code is governed by an MIT-style
+ * license that can be found in the LICENSE file or at
+ * https://opensource.org/licenses/MIT.
+ * =============================================================================
+ */
+class cv extends Ny{constructor(e){super(e),this.scale=e.scale,e.offset?this.offset=e.offset:this.offset=0}getConfig(){const e={scale:this.scale,offset:this.offset},t=super.getConfig();return Object.assign(e,t),e}call(e,t){return Zi((()=>("float32"!==(e=py(e)).dtype&&(e=Tg(e,"float32")),oo(zo(e,this.scale),this.offset))))}}cv.className="Rescaling",Ki(cv);
+/**
+ * @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 hv,pv;ye().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"}(hv||(hv={})),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={}))}(pv||(pv={}));
+/**
+ * @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 dv={};function fv(e){return dv[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 mv(e,t,n,s,r){const a=t.inputParams[e];if(a&&void 0!==a.inputIndexStart){const e=a.inputIndexStart,i=0===a.inputIndexEnd?void 0:void 0===a.inputIndexEnd?e+1:a.inputIndexEnd;if("tensor"===a.type)return gv(t.inputNames[a.inputIndexStart],n,s,r);if("tensors"===a.type){return t.inputNames.slice(e,i).map((e=>gv(e,n,s,r)))}const o=gv(t.inputNames.slice(e)[0],n,s,r),l=o.dataSync();return"number"===a.type?l[0]:ie(o.shape,l)}const i=t.attrParams[e];return i&&i.value}function gv(e,t,n,s){const[r,a]=xv(e);if(null!=s){const e=s.getHashTableHandleByName(r);if(null!=e)return e}const i=n.currentContextIds.find((e=>!!t[bv(r,e)]));return void 0!==i?t[bv(r,i)][a]:void 0}function yv(e,t){const[n,s,r]=xv(e);return[bv(n,t&&t.currentContextId),s,r]}function bv(e,t){return t?`${e}-${t}`:e}function xv(e){const t=e.split(":");if(1===t.length)return[e,0,void 0];const n=t[0],s=3===t.length?t[1]:void 0;return[n,Number(t[t.length-1]),s]}function wv(e,t,n){let s=mv("pad",e,t,n);if("explicit"===s){s=mv("explicitPaddings",e,t,n);const r=[[0,0],[0,0],[0,0],[0,0]];for(let e=0;e<4;e++)r[e][0]=s[2*e],r[e][1]=s[2*e+1];return r}return s}function vv(e){return e.kept?e:Ja(e)}
+/**
+ * @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.
+ * =============================================================================
+ */
+const kv=[{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}]}],Iv=[{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:"Prod",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axes",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",notSupported:!0},{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}]}],Nv=[{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:"Switch",category:"control",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"pred",type:"tensor"}]},{tfOpName:"Merge",category:"control",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"Enter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"frame_name",name:"frameName",type:"string"},{tfName:"is_constant",name:"isConstant",type:"bool"}]},{tfOpName:"Exit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NextIteration",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayV3",category:"control",inputs:[{start:0,name:"size",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"dynamic_size",name:"dynamicSize",type:"bool"},{tfName:"clear_after_read",name:"clearAfterRead",type:"bool"},{tfName:"identical_element_shapes",name:"identicalElementShapes",type:"bool"},{tfName:"tensor_array_name",name:"name",type:"string"}]},{tfOpName:"TensorArrayWriteV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayReadV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayGatherV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"}]},{tfOpName:"TensorArrayScatterV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArrayConcatV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape_except0",name:"elementShapeExcept0",type:"shape",notSupported:!0}]},{tfOpName:"TensorArraySplitV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"tensor",type:"tensor"},{start:2,name:"lengths",type:"number[]"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArraySizeV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}]},{tfOpName:"TensorArrayCloseV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"}]},{tfOpName:"StatelessIf",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"If",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"StatelessWhile",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"While",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"TensorListScatter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListScatterV2",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"},{start:3,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGather",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListSetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListReserve",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListFromTensor",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListStack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"},{tfName:"num_elements",name:"numElements",type:"dtype"}]},{tfOpName:"TensorListSplit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"},{start:2,name:"lengths",type:"number[]"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcat",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcatV2",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPopBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPushBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListLength",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}]},{tfOpName:"TensorListResize",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"size",type:"number"}]}],Sv=[{tfOpName:"AvgPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[],notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPoolWithArgmax",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"include_batch_in_index",name:"includeBatchInIndex",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AvgPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Conv1D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"stride",name:"stride",type:"number"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NWC"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"dilation",name:"dilation",type:"number",defaultValue:1}]},{tfOpName:"Conv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"useCudnnOnGpu",name:"useCudnnOnGpu",type:"bool"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"_FusedConv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"use_cudnn_on_gpu",name:"useCudnnOnGpu",type:"bool",defaultValue:!0},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2}]},{tfOpName:"Conv2DBackpropInput",category:"convolution",inputs:[{start:2,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:0,name:"outputShape",type:"number[]"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]",notSupported:!0}]},{tfOpName:"DepthwiseConv2d",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"DepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"FusedDepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]}]},{tfOpName:"Conv3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"Dilation2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"rates",name:"dilations",type:"number[]"},{tfName:"padding",name:"pad",type:"string"}]}],Tv=[{tfOpName:"Fill",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"},{start:1,name:"value",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"LinSpace",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"num",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"OneHot",category:"creation",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"depth",type:"number"},{start:2,name:"onValue",type:"number",defaultValue:1},{start:3,name:"offValue",type:"number",defaultValue:0}],attrs:[{tfName:"axis",name:"axis",type:"number",notSupported:!0},{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"Ones",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"OnesLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"RandomStandardNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"RandomUniform",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"minval",name:"minval",type:"number",defaultValue:0},{tfName:"maxval",name:"maxval",type:"number",defaultValue:1},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"Range",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"step",type:"number",defaultValue:0}],attrs:[{tfName:"Tidx",name:"dtype",type:"dtype"}]},{tfOpName:"TruncatedNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"means",name:"mean",type:"number",defaultValue:0},{tfName:"stddev",name:"stdDev",type:"number",defaultValue:1},{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"Zeros",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"ZerosLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"Multinomial",category:"creation",inputs:[{start:0,name:"logits",type:"tensor"},{start:1,name:"numSamples",type:"number"}],attrs:[{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number"},{tfName:"T",name:"dtype",type:"dtype"},{tfName:"output_dtype",name:"output_dtype",type:"dtype"}]}],Cv=[{tfOpName:"NonMaxSuppressionV2",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV3",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV4",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"T_threshold",name:"threshold",type:"dtype",notSupported:!0},{tfName:"pad_to_max_output_size",name:"padToMaxOutputSize",type:"bool"}]},{tfOpName:"NonMaxSuppressionV5",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"},{start:5,name:"softNmsSigma",type:"number"}]},{tfOpName:"Where",category:"dynamic",inputs:[{start:0,name:"condition",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ListDiff",category:"dynamic",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],$v=[{tfOpName:"LowerBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"TopKV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"k",type:"number"}],attrs:[{tfName:"sorted",name:"sorted",type:"bool"}]},{tfOpName:"UpperBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"Unique",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"UniqueV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]}],Ev=[{tfOpName:"PlaceholderWithDefault",category:"graph",inputs:[{start:0,name:"default",type:"tensor"}],attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Placeholder",category:"graph",attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Const",category:"graph"},{tfOpName:"Identity",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IdentityN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Snapshot",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Rank",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Size",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Shape",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"ShapeN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Print",category:"graph",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"data",type:"tensors"}],attrs:[{tfName:"message",name:"message",type:"string"},{tfName:"first_n",name:"firstN",type:"number",notSupported:!0},{tfName:"summarize",name:"summarize",type:"number",defaultValue:3}]},{tfOpName:"NoOp",category:"graph",inputs:[]},{tfOpName:"StopGradient",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"FakeQuantWithMinMaxVars",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"min",name:"min",type:"number"},{tfName:"max",name:"max",type:"number"}]}],Rv=[{tfOpName:"HashTable",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"HashTableV2",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"LookupTableImport",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableImportV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFind",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFindV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableSize",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]},{tfOpName:"LookupTableSizeV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]}],Av=[{tfOpName:"ResizeBilinear",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ResizeNearestNeighbor",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"CropAndResize",category:"image",inputs:[{start:0,name:"image",type:"tensor"},{start:1,name:"boxes",type:"tensor"},{start:2,name:"boxInd",type:"tensor"},{start:3,name:"cropSize",type:"number[]"}],attrs:[{tfName:"method",name:"method",type:"string"},{tfName:"extrapolation_value",name:"extrapolationValue",type:"number"}]},{tfOpName:"ImageProjectiveTransformV3",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"transforms",type:"tensor"},{start:2,name:"outputShape",type:"number[]"},{start:3,name:"fillValue",type:"number"}],attrs:[{tfName:"interpolation",name:"interpolation",type:"string"},{tfName:"fill_mode",name:"fillMode",type:"string"}]}],Fv=[{tfOpName:"Equal",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NotEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Greater",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"GreaterEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Less",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LessEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalAnd",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalNot",category:"logical",inputs:[{start:0,name:"a",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalOr",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Select",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SelectV2",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],_v=[{tfOpName:"_FusedMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMulV2",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Transpose",category:"matrices",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"perm",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Einsum",category:"matrices",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"equation",name:"equation",type:"string"},{tfName:"N",name:"n",type:"number",defaultValue:2},{tfName:"T",name:"dtype",type:"dtype"}]}],Dv=[{tfOpName:"EuclideanNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",defaultValue:!1}]},{tfOpName:"FusedBatchNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV2",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV3",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"LRN",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"depth_radius",name:"radius",type:"number",defaultValue:5},{tfName:"bias",name:"bias",type:"number",defaultValue:1},{tfName:"alpha",name:"alpha",type:"number",defaultValue:1},{tfName:"beta",name:"beta",type:"number",defaultValue:.5}]},{tfOpName:"Softmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"LogSoftmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"SparseToDense",category:"normalization",inputs:[{start:0,name:"sparseIndices",type:"tensor"},{start:1,name:"outputShape",type:"number[]"},{start:2,name:"sparseValues",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",defaultValue:!0,notSupported:!0}]}],Ov=[{tfOpName:"Bincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}]},{tfOpName:"DenseBincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}],attrs:[{tfName:"binary_output",name:"binaryOutput",type:"bool"}]},{tfOpName:"Max",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Mean",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Min",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Sum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"All",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Any",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"ArgMax",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"ArgMin",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"Prod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Cumprod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]},{tfOpName:"Cumsum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]}],Mv=[{tfOpName:"ConcatV2",category:"slice_join",inputs:[{start:0,end:-1,name:"tensors",type:"tensors"},{start:-1,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"Concat",category:"slice_join",inputs:[{start:1,end:0,name:"tensors",type:"tensors"},{start:0,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"GatherV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"axis",type:"number",defaultValue:0}],attrs:[{tfName:"batch_dims",name:"batchDims",type:"number",defaultValue:0}]},{tfOpName:"Gather",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",notSupported:!0}]},{tfOpName:"Reverse",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"dims",type:"bool[]"}]},{tfOpName:"ReverseV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}]},{tfOpName:"Slice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"size",type:"number[]"}]},{tfOpName:"StridedSlice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"end",type:"number[]"},{start:3,name:"strides",type:"number[]"}],attrs:[{tfName:"begin_mask",name:"beginMask",type:"number",defaultValue:0},{tfName:"end_mask",name:"endMask",type:"number",defaultValue:0},{tfName:"new_axis_mask",name:"newAxisMask",type:"number",defaultValue:0},{tfName:"ellipsis_mask",name:"ellipsisMask",type:"number",defaultValue:0},{tfName:"shrink_axis_mask",name:"shrinkAxisMask",type:"number",defaultValue:0}]},{tfOpName:"Pack",category:"slice_join",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0}]},{tfOpName:"Unpack",category:"slice_join",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0},{tfName:"num",name:"num",type:"number",defaultValue:0,notSupported:!0}]},{tfOpName:"Tile",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"reps",type:"number[]"}]},{tfOpName:"Split",category:"slice_join",inputs:[{start:0,name:"axis",type:"number",defaultValue:0},{start:1,name:"x",type:"tensor"}],attrs:[{tfName:"num_split",name:"numOrSizeSplits",type:"number",defaultValue:1}]},{tfOpName:"SplitV",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"numOrSizeSplits",type:"number[]"},{start:2,name:"axis",type:"number",defaultValue:0}]},{tfOpName:"ScatterNd",category:"slice_join",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"shape",type:"number[]"}]},{tfOpName:"GatherNd",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}]},{tfOpName:"SparseToDense",category:"slice_join",inputs:[{start:0,name:"sparseIndices",type:"tensor"},{start:1,name:"outputShape",type:"number[]"},{start:2,name:"sparseValues",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",defaultValue:!1,notSupported:!0}]}],Lv=[{tfOpName:"SparseFillEmptyRows",category:"sparse",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"denseShape",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}]},{tfOpName:"SparseReshape",category:"sparse",inputs:[{start:0,name:"inputIndices",type:"tensor"},{start:1,name:"inputShape",type:"tensor"},{start:2,name:"newShape",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SparseSegmentMean",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]},{tfOpName:"SparseSegmentSum",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]}],zv=[{tfOpName:"FFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"RFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]},{tfOpName:"IRFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]}],Pv=[{tfOpName:"StringNGrams",category:"string",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"dataSplits",type:"tensor"}],attrs:[{tfName:"separator",name:"separator",type:"string"},{tfName:"ngram_widths",name:"nGramWidths",type:"number[]"},{tfName:"left_pad",name:"leftPad",type:"string"},{tfName:"right_pad",name:"rightPad",type:"string"},{tfName:"pad_width",name:"padWidth",type:"number"},{tfName:"preserve_short_sequences",name:"preserveShortSequences",type:"bool"}],outputs:["ngrams","ngrams_splits"]},{tfOpName:"StringSplit",category:"string",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"delimiter",type:"tensor"}],attrs:[{tfName:"skip_empty",name:"skipEmpty",type:"bool"}],outputs:["indices","values","shape"]},{tfOpName:"StringToHashBucketFast",category:"string",inputs:[{start:0,name:"input",type:"tensor"}],attrs:[{tfName:"num_buckets",name:"numBuckets",type:"number"}]}],Bv=[{tfOpName:"Cast",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"SrcT",name:"sdtype",type:"dtype",notSupported:!0},{tfName:"DstT",name:"dtype",type:"dtype"}]},{tfOpName:"ExpandDims",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"MirrorPad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"mode",name:"mode",type:"string"}]},{tfOpName:"Pad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"constant_value",name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"PadV2",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"},{start:2,name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"Reshape",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}]},{tfOpName:"Squeeze",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"axis",tfDeprecatedName:"squeeze_dims",name:"axis",type:"number[]"}]},{tfOpName:"SpaceToBatchND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"paddings",type:"number[]"}]},{tfOpName:"BatchToSpaceND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"crops",type:"number[]"}]},{tfOpName:"DepthToSpace",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"block_size",name:"blockSize",type:"number"},{tfName:"data_format",name:"dataFormat",type:"string"}]},{tfOpName:"BroadcastTo",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}],attrs:[]},{tfOpName:"BroadcastArgs",category:"transformation",inputs:[{start:0,name:"s0",type:"tensor"},{start:1,name:"s1",type:"tensor"}],attrs:[]}];
+/**
+ * @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 Wv{static get Instance(){return this._instance||(this._instance=new this)}constructor(){const e=[].concat(...[o,l,u,c,h,p,d,f,m,g,y,b,x,w,v,k,I,N,S].map((e=>e.json)));this.opMappers=e.reduce(((e,t)=>(e[t.tfOpName]=t,e)),{})}transformGraph(e,t={}){const n=e.node,s=[],r=[],a=[],i=n.reduce(((e,t)=>(e[t.name]=this.mapNode(t),t.op.startsWith("Placeholder")?s.push(e[t.name]):"Const"===t.op?r.push(e[t.name]):null!=t.input&&0!==t.input.length||a.push(e[t.name]),e)),{});let o=[];const l=[];let u={},c={};null!=t&&(u=this.mapSignatureEntries(t.inputs),c=this.mapSignatureEntries(t.outputs));const h=Object.keys(i);h.forEach((e=>{const t=i[e];t.inputNames.forEach(((e,n)=>{const[s,,r]=yv(e),a=i[s];if(null!=a.outputs){const e=a.outputs.indexOf(r);if(-1!==e){const r=`${s}:${e}`;t.inputNames[n]=r}}t.inputs.push(a),a.children.push(t)}))})),0===Object.keys(c).length?h.forEach((e=>{const t=i[e];0===t.children.length&&l.push(t)})):Object.keys(c).forEach((e=>{const[t]=yv(e),n=i[t];null!=n&&(n.signatureKey=c[e],l.push(n))})),Object.keys(u).length>0?Object.keys(u).forEach((e=>{const[t]=yv(e),n=i[t];n&&(n.signatureKey=u[e],o.push(n))})):o=s;let p={};null!=e.library&&null!=e.library.function&&(p=e.library.function.reduce(((e,t)=>(e[t.signature.name]=this.mapFunction(t),e)),{}));const d={nodes:i,inputs:o,outputs:l,weights:r,placeholders:s,signature:t,functions:p};return a.length>0&&(d.initNodes=a),d}mapSignatureEntries(e){return Object.keys(e||{}).reduce(((t,n)=>(t[e[n].name]=n,t)),{})}mapNode(e){const t=fv(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 s=n.type;let r;switch(n.type){case"string":r=Uv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=Uv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"string[]":r=Qv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=Qv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"number":r=Hv(e.attr,n.tfName,n.defaultValue||0),void 0===r&&n.tfDeprecatedName&&(r=Hv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"number[]":r=Jv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=Jv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"bool":r=Gv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=Gv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"bool[]":r=tk(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=tk(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"shape":r=Zv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=Zv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"shape[]":r=ek(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=ek(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"dtype":r=Kv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=Kv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"dtype[]":r=Xv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=Xv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"func":r=qv(e.attr,n.tfName,n.defaultValue),void 0===r&&n.tfDeprecatedName&&(r=qv(e.attr,n.tfDeprecatedName,n.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${n.type} for op: ${e.op}`)}return t[n.name]={value:r,type:s},t}),{})),n}mapFunction(e){const t=e.nodeDef,n=[];let s={};null!=t&&(s=t.reduce(((e,t)=>(e[t.name]=this.mapNode(t),"Const"===t.op&&n.push(e[t.name]),e)),{}));const r=[],a=[];e.signature.inputArg.forEach((e=>{const[t]=yv(e.name),n={name:t,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:jv(e.type),type:"dtype"}},children:[]};n.signatureKey=e.name,r.push(n),s[t]=n}));Object.keys(s).forEach((e=>{const t=s[e];t.inputNames.forEach(((e,n)=>{const[r,,a]=yv(e),i=s[r];if(null!=i.outputs){const e=i.outputs.indexOf(a);if(-1!==e){const s=`${r}:${e}`;t.inputNames[n]=s}}t.inputs.push(i),i.children.push(t)}))}));const i=e.ret;e.signature.outputArg.forEach((e=>{const[t,n]=yv(i[e.name]),r=s[t];null!=r&&(r.defaultOutput=n,a.push(r))}));const o=this.mapArgsToSignature(e);return{nodes:s,inputs:r,outputs:a,weights:n,placeholders:[],signature:o}}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 Vv(e,t){const n=Array.isArray(e)?String.fromCharCode.apply(null,e):function(e){const t=ye().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 Uv(e,t,n,s=!1){const r=e[t];return null!=r?Vv(r.s,s):n}function Gv(e,t,n){const s=e[t];return s?s.b:n}function Hv(e,t,n){const s=e[t]||{},r=null!=s.i?s.i:null!=s.f?s.f:n;return"number"==typeof r?r:parseInt(r,10)}function jv(e){switch("string"==typeof e&&(e=hv[e]),e){case hv.DT_FLOAT:case hv.DT_HALF:return"float32";case hv.DT_INT32:case hv.DT_INT64:case hv.DT_INT8:case hv.DT_UINT8:return"int32";case hv.DT_BOOL:return"bool";case hv.DT_DOUBLE:return"float32";case hv.DT_STRING:return"string";default:return null}}function qv(e,t,n){const s=e[t];return s&&s.func?s.func.name:n}function Kv(e,t,n){const s=e[t];return s&&s.type?jv(s.type):n}function Xv(e,t,n){const s=e[t];return s&&s.list&&s.list.type?s.list.type.map((e=>jv(e))):n}function Yv(e){if(!e.unknownRank)return null!=e.dim?e.dim.map((e=>"number"==typeof e.size?e.size:parseInt(e.size,10))):[]}function Zv(e,t,n){const s=e[t];return s&&s.shape?Yv(s.shape):n}function Jv(e,t,n){const s=e[t];return s?((s.list.f&&s.list.f.length?s.list.f:s.list.i)||[]).map((e=>"number"==typeof e?e:parseInt(e,10))):n}function Qv(e,t,n,s=!1){const r=e[t];return r&&r.list&&r.list.s?r.list.s.map((e=>Vv(e,s))):n}function ek(e,t,n){const s=e[t];return s&&s.list&&s.list.shape?s.list.shape.map((e=>Yv(e))):n}function tk(e,t,n){const s=e[t];return s&&s.list&&s.list.b?s.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 nk{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 gv(e,this.tensorMap,this.context)}getAttr(e,t){const n=this.node.rawAttrs[e];if(null!=n.tensor)return gv(e,this.tensorMap,this.context);if(null!=n.i||null!=n.f)return Hv(this.node.rawAttrs,e,t);if(null!=n.s)return Uv(this.node.rawAttrs,e,t);if(null!=n.b)return Gv(this.node.rawAttrs,e,t);if(null!=n.shape)return Zv(this.node.rawAttrs,e,t);if(null!=n.type)return Kv(this.node.rawAttrs,e,t);if(null!=n.list){if(null!=n.list.i||null!=n.list.f)return Jv(this.node.rawAttrs,e,t);if(null!=n.list.s)return Qv(this.node.rawAttrs,e,t);if(null!=n.list.shape)return ek(this.node.rawAttrs,e,t);if(null!=n.list.b)return tk(this.node.rawAttrs,e,t);if(null!=n.list.type)return Xv(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 sk(e,t,n=""){if("number"!=typeof e&&"number"!=typeof t){O(e.length===t.length,(()=>n+` Shapes ${e} and ${t} must match`));for(let s=0;sn+` Shapes ${e} and ${t} must match`))}}}function rk(e){return"number"!=typeof e&&!e.some((e=>e<0))}function ak(e,t,n){let s=ik(e,n);const r=!rk(s);if(r&&0===t.length)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${s}`);if(r&&t.forEach((e=>{s=ik(e.shape,s)})),!rk(s))throw new Error(`Non-fully-defined elementShape: ${s}`);return s}function ik(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 s=0;s=0&&a>=0&&r!==a)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[s]=r>=0?r:a}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 ok{constructor(e,t,n,s,r,a,i){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=s,this.identicalElementShapes=r,this.dynamicSize=a,this.clearAfterRead=i,this.tensors=[],this.closed_=!1,this.idTensor=no(0),Qi(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),sk(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,Qi(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 ${t}`);if(e)e=e.slice(0,this.size());else{e=[];for(let t=0;t=this.maxSize)throw new Error(`Max index must be < array size (${n} vs. ${this.maxSize})`);this.writeMany(e,Qc(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 s=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 r=0===n?0:t.size/n,a=[];Zi((()=>{t=_o(t,[1,n,r]);for(let n=0;n{if(n!==e.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${e.dtype}`);sk(t,e.shape,"TensorList shape mismatch: "),Qi(e)})),this.idTensor=no(0),this.maxNumElements=s,Qi(this.idTensor)}get id(){return this.idTensor.id}copy(){return new lk([...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.`);sk(e,this.elementShape,"TensorList shape mismatch: ");const s=ak(this.elementShape,this.tensors,e);return Zi((()=>{const e=this.tensors.map((e=>_o(e,s)));return Bc(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=ak(this.elementShape,this.tensors,e),s=this.tensors.pop();return s.kept=!1,sk(s.shape,e,"TensorList shape mismatch: "),_o(s,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(sk(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Qi(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 lk([],this.elementShape,this.elementDtype,this.maxNumElements);t.tensors.length=e;for(let n=0;nthis.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.`);sk(this.tensors[e].shape,t,"TensorList shape mismatch: ");const s=ak(this.elementShape,this.tensors,t);return _o(this.tensors[e],s)}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.`);sk(this.elementShape,t.shape,"TensorList shape mismatch: "),Qi(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}`);sk(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());const s=ak(this.elementShape,this.tensors,n);return 0===e.length?Yr([],[0].concat(s)):Zi((()=>{const t=e.map((e=>_o(this.tensors[e],s)));return Bc(t,0)}))}concat(e,t){if(e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);sk(this.elementShape,t,"TensorList shape mismatch: ");const n=ak(this.elementShape,this.tensors,t);return 0===this.size()?Yr([],[0].concat(n)):Zi((()=>{const e=this.tensors.map((e=>_o(e,n)));return Mo(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 uk=async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{const s=mv("thenBranch",e,t,n),r=mv("elseBranch",e,t,n),a=mv("cond",e,t,n),i=mv("args",e,t,n);return(await a.data())[0]?n.functionMap[s].executeFunctionAsync(i,n.tensorArrayMap,n.tensorListMap):n.functionMap[r].executeFunctionAsync(i,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{const s=mv("body",e,t,n),r=mv("cond",e,t,n),a=mv("args",e,t,n),i=await n.functionMap[r].executeFunctionAsync(a,n.tensorArrayMap,n.tensorListMap),o=a.map((e=>e.id));let l=await i[0].data();i.forEach((e=>{e.kept||-1!==o.indexOf(e.id)||e.dispose()}));let u=a;for(;l[0];){const e=u;u=await n.functionMap[s].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);const t=u.map((e=>e.id));e.forEach((e=>{e.kept||-1!==o.indexOf(e.id)||-1!==t.indexOf(e.id)||e.dispose()}));const a=await n.functionMap[r].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);l=await a[0].data(),a.forEach((e=>{e.kept||-1!==o.indexOf(e.id)||-1!==t.indexOf(e.id)||e.dispose()}))}return u}case"LoopCond":return[vv(mv("pred",e,t,n))];case"Switch":{const s=mv("pred",e,t,n);let r=mv("data",e,t,n);return r.kept||(r=vv(r)),(await s.data())[0]?[void 0,r]:[r,void 0]}case"Merge":{const s=e.inputNames.find((e=>void 0!==gv(e,t,n)));if(s){return[vv(gv(s,t,n))]}return}case"Enter":{const s=mv("frameName",e,t,n),r=mv("tensor",e,t,n);return n.enterFrame(s),[vv(r)]}case"Exit":{const s=mv("tensor",e,t,n);return n.exitFrame(),[vv(s)]}case"NextIteration":{const s=mv("tensor",e,t,n);return n.nextIteration(),[vv(s)]}case"TensorArrayV3":{const s=mv("size",e,t,n),r=mv("dtype",e,t,n),a=mv("elementShape",e,t,n),i=mv("dynamicSize",e,t,n),o=mv("clearAfterRead",e,t,n),l=mv("identicalElementShapes",e,t,n),u=mv("name",e,t,n),c=new ok(u,r,s,a,l,i,o);return n.addTensorArray(c),[c.idTensor,no(1)]}case"TensorArrayWriteV3":{const s=mv("tensorArrayId",e,t,n),r=mv("index",e,t,n),a=mv("tensor",e,t,n),i=n.getTensorArray(s.id);return i.write(r,a),[i.idTensor]}case"TensorArrayReadV3":{const s=mv("tensorArrayId",e,t,n),r=mv("index",e,t,n);return[n.getTensorArray(s.id).read(r)]}case"TensorArrayGatherV3":{const s=mv("tensorArrayId",e,t,n),r=mv("indices",e,t,n),a=mv("dtype",e,t,n);return[n.getTensorArray(s.id).gather(r,a)]}case"TensorArrayScatterV3":{const s=mv("tensorArrayId",e,t,n),r=mv("indices",e,t,n),a=mv("tensor",e,t,n),i=n.getTensorArray(s.id);return i.scatter(r,a),[i.idTensor]}case"TensorArrayConcatV3":{const s=mv("tensorArrayId",e,t,n),r=n.getTensorArray(s.id),a=mv("dtype",e,t,n);return[r.concat(a)]}case"TensorArraySplitV3":{const s=mv("tensorArrayId",e,t,n),r=mv("tensor",e,t,n),a=mv("lengths",e,t,n),i=n.getTensorArray(s.id);return i.split(a,r),[i.idTensor]}case"TensorArraySizeV3":{const s=mv("tensorArrayId",e,t,n);return[no(n.getTensorArray(s.id).size(),"int32")]}case"TensorArrayCloseV3":{const s=mv("tensorArrayId",e,t,n),r=n.getTensorArray(s.id);return r.clearAndClose(),[r.idTensor]}case"TensorListSetItem":{const s=mv("tensorListId",e,t,n),r=mv("index",e,t,n),a=mv("tensor",e,t,n),i=n.getTensorList(s.id);return i.setItem(r,a),[i.idTensor]}case"TensorListGetItem":{const s=mv("tensorListId",e,t,n),r=mv("index",e,t,n),a=mv("elementShape",e,t,n),i=mv("elementDType",e,t,n);return[n.getTensorList(s.id).getItem(r,a,i)]}case"TensorListScatterV2":case"TensorListScatter":{const s=mv("indices",e,t,n),r=function(e,t,n,s){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);const r=Math.max(...t);if(null!=s&&-1!==s&&r>=s)throw new Error(`Max index must be < array size (${r} vs. ${s})`);const a=new lk([],n,e.dtype,s),i=Qc(e,0);return t.forEach(((e,t)=>{a.setItem(e,i[t])})),a}(mv("tensor",e,t,n),s,mv("elementShape",e,t,n),mv("numElements",e,t,n));return n.addTensorList(r),[r.idTensor]}case"TensorListReserve":case"EmptyTensorList":{const s=mv("elementShape",e,t,n),r=mv("elementDType",e,t,n);let a;a="TensorListReserve"===e.op?"numElements":"maxNumElements";const i=mv(a,e,t,n),o=function(e,t,n,s){return new lk([],e,t,s)}(s,r,0,"TensorListReserve"===e.op?-1:i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{const s=mv("tensorListId",e,t,n),r=mv("indices",e,t,n),a=mv("elementShape",e,t,n),i=mv("elementDType",e,t,n);return[n.getTensorList(s.id).gather(r,i,a)]}case"TensorListStack":{const s=mv("tensorListId",e,t,n),r=mv("elementShape",e,t,n),a=mv("elementDType",e,t,n),i=mv("numElements",e,t,n);return[n.getTensorList(s.id).stack(r,a,i)]}case"TensorListFromTensor":{const s=function(e,t,n){const s=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}`);sk(e.shape.slice(1),t,"TensorList shape mismatch: ");const r=Qc(e);return new lk(r,t,s)}(mv("tensor",e,t,n),mv("elementShape",e,t,n),mv("elementDType",e,t,n));return n.addTensorList(s),[s.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{const s=mv("tensorListId",e,t,n),r=n.getTensorList(s.id),a=mv("dtype",e,t,n),i=mv("elementShape",e,t,n);return[r.concat(a,i)]}case"TensorListPushBack":{const s=mv("tensorListId",e,t,n),r=mv("tensor",e,t,n),a=n.getTensorList(s.id);return a.pushBack(r),[a.idTensor]}case"TensorListPopBack":{const s=mv("tensorListId",e,t,n),r=mv("elementShape",e,t,n),a=mv("elementDType",e,t,n);return[n.getTensorList(s.id).popBack(r,a)]}case"TensorListSplit":{const s=mv("tensor",e,t,n),r=mv("elementShape",e,t,n),a=function(e,t,n){let s=0;const r=t.map((e=>(s+=e,s)));if(s!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to\n tensor.shape[0], but sum of lengths is\n ${s}, and tensor's shape is: ${e.shape}`);const a=ik(e.shape.slice(1),n),i=0===s?0:e.size/s,o=Zi((()=>{const n=[];e=_o(e,[1,s,i]);for(let s=0;se.dispose())),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return no(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(),Zi((()=>{const e=Qc(t),s=n.length,r=e.length;O(s===r,(()=>`The number of elements doesn't match, keys has ${s} elements, the values has ${r} elements.`));for(let t=0;t{const e=[];for(let s=0;s{switch(e.category){case"arithmetic":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[s.add(mv("a",e,t,n),mv("b",e,t,n))];case"AddN":return[s.addN(mv("tensors",e,t,n))];case"FloorMod":case"Mod":return[s.mod(mv("a",e,t,n),mv("b",e,t,n))];case"Mul":return[s.mul(mv("a",e,t,n),mv("b",e,t,n))];case"RealDiv":case"Div":return[s.div(mv("a",e,t,n),mv("b",e,t,n))];case"DivNoNan":return[s.divNoNan(mv("a",e,t,n),mv("b",e,t,n))];case"FloorDiv":return[s.floorDiv(mv("a",e,t,n),mv("b",e,t,n))];case"Sub":return[s.sub(mv("a",e,t,n),mv("b",e,t,n))];case"Minimum":return[s.minimum(mv("a",e,t,n),mv("b",e,t,n))];case"Maximum":return[s.maximum(mv("a",e,t,n),mv("b",e,t,n))];case"Pow":return[s.pow(mv("a",e,t,n),mv("b",e,t,n))];case"SquaredDifference":return[s.squaredDifference(mv("a",e,t,n),mv("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"basic_math":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"Abs":case"ComplexAbs":return[s.abs(mv("x",e,t,n))];case"Acos":return[s.acos(mv("x",e,t,n))];case"Acosh":return[s.acosh(mv("x",e,t,n))];case"Asin":return[s.asin(mv("x",e,t,n))];case"Asinh":return[s.asinh(mv("x",e,t,n))];case"Atan":return[s.atan(mv("x",e,t,n))];case"Atan2":return[s.atan2(mv("x",e,t,n),mv("y",e,t,n))];case"Atanh":return[s.atanh(mv("x",e,t,n))];case"Ceil":return[s.ceil(mv("x",e,t,n))];case"Complex":return[s.complex(mv("real",e,t,n),mv("imag",e,t,n))];case"Cos":return[s.cos(mv("x",e,t,n))];case"Cosh":return[s.cosh(mv("x",e,t,n))];case"Elu":return[s.elu(mv("x",e,t,n))];case"Erf":return[s.erf(mv("x",e,t,n))];case"Exp":return[s.exp(mv("x",e,t,n))];case"Expm1":return[s.expm1(mv("x",e,t,n))];case"Floor":return[s.floor(mv("x",e,t,n))];case"Log":return[s.log(mv("x",e,t,n))];case"Log1p":return[s.log1p(mv("x",e,t,n))];case"Imag":return[s.imag(mv("x",e,t,n))];case"Neg":return[s.neg(mv("x",e,t,n))];case"Reciprocal":return[s.reciprocal(mv("x",e,t,n))];case"Real":return[s.real(mv("x",e,t,n))];case"Relu":return[s.relu(mv("x",e,t,n))];case"Round":return[s.round(mv("x",e,t,n))];case"Selu":return[s.selu(mv("x",e,t,n))];case"Sigmoid":return[s.sigmoid(mv("x",e,t,n))];case"Sin":return[s.sin(mv("x",e,t,n))];case"Sign":return[s.sign(mv("x",e,t,n))];case"Sinh":return[s.sinh(mv("x",e,t,n))];case"Softplus":return[s.softplus(mv("x",e,t,n))];case"Sqrt":return[s.sqrt(mv("x",e,t,n))];case"Square":return[s.square(mv("x",e,t,n))];case"Tanh":return[s.tanh(mv("x",e,t,n))];case"Tan":return[s.tan(mv("x",e,t,n))];case"ClipByValue":return[s.clipByValue(mv("x",e,t,n),mv("clipValueMin",e,t,n),mv("clipValueMax",e,t,n))];case"Relu6":return[s.relu6(mv("x",e,t,n))];case"Rsqrt":return[s.rsqrt(gv(e.inputNames[0],t,n))];case"Prod":return[s.prod(mv("x",e,t,n),mv("axes",e,t,n))];case"LeakyRelu":return[s.leakyRelu(mv("x",e,t,n),mv("alpha",e,t,n))];case"Prelu":return[s.prelu(mv("x",e,t,n),mv("alpha",e,t,n))];case"IsNan":return[s.isNaN(gv(e.inputNames[0],t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"control":return uk(e,t,n);case"convolution":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"Conv1D":{const r=mv("stride",e,t,n),a=mv("pad",e,t,n),i=mv("dataFormat",e,t,n).toUpperCase(),o=mv("dilation",e,t,n);return[s.conv1d(mv("x",e,t,n),mv("filter",e,t,n),r,a,i,o)]}case"Conv2D":{const r=mv("strides",e,t,n),a=wv(e,t,n),i=mv("dataFormat",e,t,n).toUpperCase(),o=mv("dilations",e,t,n);return[s.conv2d(mv("x",e,t,n),mv("filter",e,t,n),[r[1],r[2]],a,i,[o[1],o[2]])]}case"_FusedConv2D":{const{stride:r,pad:a,dataFormat:i,dilations:o,biasArg:l,preluArg:u,activationFunc:c,leakyreluAlpha:h}=ck(e,t,n);return[s.fused.conv2d({x:mv("x",e,t,n),filter:mv("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:i,dilations:[o[1],o[2]],bias:l,activation:c,preluActivationWeights:u,leakyreluAlpha:h})]}case"FusedDepthwiseConv2dNative":{const{stride:r,pad:a,dataFormat:i,dilations:o,biasArg:l,preluArg:u,activationFunc:c,leakyreluAlpha:h}=ck(e,t,n);return[s.fused.depthwiseConv2d({x:mv("x",e,t,n),filter:mv("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:i,dilations:[o[1],o[2]],bias:l,activation:c,preluActivationWeights:u,leakyreluAlpha:h})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{const r=mv("outputShape",e,t,n),a=mv("strides",e,t,n),i=wv(e,t,n);return[s.conv2dTranspose(mv("x",e,t,n),mv("filter",e,t,n),r,[a[1],a[2]],i)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{const r=mv("strides",e,t,n),a=wv(e,t,n),i=mv("dilations",e,t,n),o=mv("dataFormat",e,t,n).toUpperCase();return[s.depthwiseConv2d(mv("input",e,t,n),mv("filter",e,t,n),[r[1],r[2]],a,o,[i[1],i[2]])]}case"Conv3D":{const r=mv("strides",e,t,n),a=mv("pad",e,t,n),i=mv("dataFormat",e,t,n).toUpperCase(),o=mv("dilations",e,t,n);return[s.conv3d(mv("x",e,t,n),mv("filter",e,t,n),[r[1],r[2],r[3]],a,i,[o[1],o[2],o[3]])]}case"AvgPool":{const r=mv("strides",e,t,n),a=mv("pad",e,t,n),i=mv("kernelSize",e,t,n);return[s.avgPool(mv("x",e,t,n),[i[1],i[2]],[r[1],r[2]],a)]}case"MaxPool":{const r=mv("strides",e,t,n),a=mv("pad",e,t,n),i=mv("kernelSize",e,t,n);return[s.maxPool(mv("x",e,t,n),[i[1],i[2]],[r[1],r[2]],a)]}case"MaxPoolWithArgmax":{const r=mv("strides",e,t,n),a=mv("pad",e,t,n),i=mv("kernelSize",e,t,n),o=mv("includeBatchInIndex",e,t,n),{result:l,indexes:u}=s.maxPoolWithArgmax(mv("x",e,t,n),[i[1],i[2]],[r[1],r[2]],a,o);return[l,u]}case"AvgPool3D":{const r=mv("strides",e,t,n),a=mv("pad",e,t,n),i=mv("kernelSize",e,t,n);return[s.avgPool3d(mv("x",e,t,n),[i[1],i[2],i[3]],[r[1],r[2],r[3]],a)]}case"MaxPool3D":{const r=mv("strides",e,t,n),a=mv("pad",e,t,n),i=mv("kernelSize",e,t,n);return[s.maxPool3d(mv("x",e,t,n),[i[1],i[2],i[3]],[r[1],r[2],r[3]],a)]}case"Dilation2D":{const r=mv("strides",e,t,n),a=mv("pad",e,t,n),i=mv("dilations",e,t,n),o=r[1],l=r[2],u=i[1],c=i[2];return[s.dilation2d(mv("x",e,t,n),mv("filter",e,t,n),[o,l],a,[u,c],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"creation":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"Fill":{const r=mv("shape",e,t,n),a=mv("dtype",e,t,n),i=mv("value",e,t,n);return[s.fill(r,i,a)]}case"LinSpace":{const r=mv("start",e,t,n),a=mv("stop",e,t,n),i=mv("num",e,t,n);return[s.linspace(r,a,i)]}case"Multinomial":{const r=mv("logits",e,t,n),a=mv("numSamples",e,t,n),i=mv("seed",e,t,n);return[s.multinomial(r,a,i)]}case"OneHot":{const r=mv("indices",e,t,n),a=mv("depth",e,t,n),i=mv("onValue",e,t,n),o=mv("offValue",e,t,n),l=mv("dtype",e,t,n);return[s.oneHot(r,a,i,o,l)]}case"Ones":return[s.ones(mv("shape",e,t,n),mv("dtype",e,t,n))];case"OnesLike":return[s.onesLike(mv("x",e,t,n))];case"RandomStandardNormal":return[s.randomStandardNormal(mv("shape",e,t,n),mv("dtype",e,t,n),mv("seed",e,t,n))];case"RandomUniform":return[s.randomUniform(mv("shape",e,t,n),mv("minval",e,t,n),mv("maxval",e,t,n),mv("dtype",e,t,n))];case"Range":{const r=mv("start",e,t,n),a=mv("stop",e,t,n),i=mv("step",e,t,n);return[s.range(r,a,i,mv("dtype",e,t,n))]}case"TruncatedNormal":{const r=mv("shape",e,t,n),a=mv("mean",e,t,n),i=mv("stdDev",e,t,n),o=mv("seed",e,t,n);return[s.truncatedNormal(r,a,i,mv("dtype",e,t,n),o)]}case"Zeros":return[s.zeros(mv("shape",e,t,n),mv("dtype",e,t,n))];case"ZerosLike":return[s.zerosLike(mv("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"dynamic":return(async(e,t,n,s,r=T)=>{switch(e.op){case"NonMaxSuppressionV5":{const{boxes:s,scores:a,maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=hk(e,t,n),c=await r.image.nonMaxSuppressionWithScoreAsync(s,a,i,o,l,u);return[c.selectedIndices,c.selectedScores]}case"NonMaxSuppressionV4":{const{boxes:s,scores:a,maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=hk(e,t,n),u=mv("padToMaxOutputSize",e,t,n),c=await r.image.nonMaxSuppressionPaddedAsync(s,a,i,o,l,u);return[c.selectedIndices,c.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{const{boxes:s,scores:a,maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=hk(e,t,n);return[await r.image.nonMaxSuppressionAsync(s,a,i,o,l)]}case"Where":{const s=r.cast(mv("condition",e,t,n),"bool"),a=[await r.whereAsync(s)];return s.dispose(),a}case"ListDiff":return r.setdiff1dAsync(mv("x",e,t,n),mv("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n);case"evaluation":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"LowerBound":{const r=mv("sortedSequence",e,t,n),a=mv("values",e,t,n);return[s.lowerBound(r,a)]}case"TopKV2":{const r=mv("x",e,t,n),a=mv("k",e,t,n),i=mv("sorted",e,t,n),o=s.topk(r,a,i);return[o.values,o.indices]}case"UpperBound":{const r=mv("sortedSequence",e,t,n),a=mv("values",e,t,n);return[s.upperBound(r,a)]}case"Unique":{const r=mv("x",e,t,n),a=s.unique(r);return[a.values,a.indices]}case"UniqueV2":{const r=mv("x",e,t,n),a=mv("axis",e,t,n),i=s.unique(r,a);return[i.values,i.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"image":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"ResizeBilinear":{const r=mv("images",e,t,n),a=mv("size",e,t,n),i=mv("alignCorners",e,t,n),o=mv("halfPixelCenters",e,t,n);return[s.image.resizeBilinear(r,[a[0],a[1]],i,o)]}case"ResizeNearestNeighbor":{const r=mv("images",e,t,n),a=mv("size",e,t,n),i=mv("alignCorners",e,t,n),o=mv("halfPixelCenters",e,t,n);return[s.image.resizeNearestNeighbor(r,[a[0],a[1]],i,o)]}case"CropAndResize":{const r=mv("image",e,t,n),a=mv("boxes",e,t,n),i=mv("boxInd",e,t,n),o=mv("cropSize",e,t,n),l=mv("method",e,t,n),u=mv("extrapolationValue",e,t,n);return[s.image.cropAndResize(r,a,i,o,l,u)]}case"ImageProjectiveTransformV3":{const r=mv("images",e,t,n),a=mv("transforms",e,t,n),i=mv("outputShape",e,t,n),o=mv("fillValue",e,t,n),l=mv("interpolation",e,t,n),u=mv("fillMode",e,t,n);return[s.image.transform(r,a,l.toLowerCase(),u.toLowerCase(),o,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"graph":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":const r=mv("default",e,t,n);return[gv(e.name,t,n)||r];case"Placeholder":return[gv(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":case"Snapshot":return[vv(mv("x",e,t,n))];case"IdentityN":return mv("x",e,t,n).map((e=>vv(e)));case"Shape":return[s.tensor1d(mv("x",e,t,n).shape,"int32")];case"ShapeN":return mv("x",e,t,n).map((e=>s.tensor1d(e.shape)));case"Size":return[s.scalar(mv("x",e,t,n).size,"int32")];case"Rank":return[s.scalar(mv("x",e,t,n).rank,"int32")];case"NoOp":return[s.scalar(1)];case"Print":const a=mv("x",e,t,n),i=mv("data",e,t,n),o=mv("message",e,t,n),l=mv("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(o);for(let e=0;e((e,t,n,s=T)=>{switch(e.op){case"Equal":return[s.equal(mv("a",e,t,n),mv("b",e,t,n))];case"NotEqual":return[s.notEqual(mv("a",e,t,n),mv("b",e,t,n))];case"Greater":return[s.greater(mv("a",e,t,n),mv("b",e,t,n))];case"GreaterEqual":return[s.greaterEqual(mv("a",e,t,n),mv("b",e,t,n))];case"Less":return[s.less(mv("a",e,t,n),mv("b",e,t,n))];case"LessEqual":return[s.lessEqual(mv("a",e,t,n),mv("b",e,t,n))];case"LogicalAnd":return[s.logicalAnd(mv("a",e,t,n),mv("b",e,t,n))];case"LogicalNot":return[s.logicalNot(mv("a",e,t,n))];case"LogicalOr":return[s.logicalOr(mv("a",e,t,n),mv("b",e,t,n))];case"Select":case"SelectV2":return[s.where(mv("condition",e,t,n),mv("a",e,t,n),mv("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"matrices":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[s.matMul(mv("a",e,t,n),mv("b",e,t,n),mv("transposeA",e,t,n),mv("transposeB",e,t,n))];case"Einsum":return[s.einsum(mv("equation",e,t,n),...mv("tensors",e,t,n))];case"Transpose":return[s.transpose(mv("x",e,t,n),mv("perm",e,t,n))];case"_FusedMatMul":const[r,a]=mv("fusedOps",e,t,n),i="biasadd"===r,o="prelu"===a,l=mv("numArgs",e,t,n),u=mv("leakyreluAlpha",e,t,n);if(i){if(o&&2!==l)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!o&&1!==l)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}const[c,h]=mv("args",e,t,n);return[s.fused.matMul({a:mv("a",e,t,n),b:mv("b",e,t,n),transposeA:mv("transposeA",e,t,n),transposeB:mv("transposeB",e,t,n),bias:c,activation:a,preluActivationWeights:h,leakyreluAlpha:u})];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"normalization":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"EuclideanNorm":return[s.euclideanNorm(mv("x",e,t,n),mv("axis",e,t,n),mv("keepDims",e,t,n))];case"FusedBatchNorm":case"FusedBatchNormV2":case"FusedBatchNormV3":return[s.batchNorm(mv("x",e,t,n),mv("mean",e,t,n),mv("variance",e,t,n),mv("offset",e,t,n),mv("scale",e,t,n),mv("epsilon",e,t,n))];case"LRN":return[s.localResponseNormalization(mv("x",e,t,n),mv("radius",e,t,n),mv("bias",e,t,n),mv("alpha",e,t,n),mv("beta",e,t,n))];case"Softmax":return[s.softmax(mv("x",e,t,n))];case"LogSoftmax":return[s.logSoftmax(mv("x",e,t,n))];case"SparseToDense":return[s.sparseToDense(mv("sparseIndices",e,t,n),mv("outputShape",e,t,n),mv("sparseValues",e,t,n),mv("defaultValue",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"reduction":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"Max":{const r=mv("axis",e,t,n),a=mv("keepDims",e,t,n);return[s.max(mv("x",e,t,n),r,a)]}case"Mean":{const r=mv("axis",e,t,n),a=mv("keepDims",e,t,n);return[s.mean(mv("x",e,t,n),r,a)]}case"Min":{const r=mv("axis",e,t,n),a=mv("keepDims",e,t,n);return[s.min(mv("x",e,t,n),r,a)]}case"Sum":{const r=mv("axis",e,t,n),a=mv("keepDims",e,t,n);return[s.sum(mv("x",e,t,n),r,a)]}case"All":{const r=mv("axis",e,t,n),a=mv("keepDims",e,t,n);return[s.all(mv("x",e,t,n),r,a)]}case"Any":{const r=mv("axis",e,t,n),a=mv("keepDims",e,t,n);return[s.any(mv("x",e,t,n),r,a)]}case"ArgMax":{const r=mv("axis",e,t,n);return[s.argMax(mv("x",e,t,n),r)]}case"ArgMin":{const r=mv("axis",e,t,n);return[s.argMin(mv("x",e,t,n),r)]}case"Prod":{const r=mv("axis",e,t,n),a=mv("keepDims",e,t,n);return[s.prod(mv("x",e,t,n),r,a)]}case"Cumprod":{const r=mv("axis",e,t,n),a=mv("exclusive",e,t,n),i=mv("reverse",e,t,n);return[s.cumprod(mv("x",e,t,n),r,a,i)]}case"Cumsum":{const r=mv("axis",e,t,n),a=mv("exclusive",e,t,n),i=mv("reverse",e,t,n);return[s.cumsum(mv("x",e,t,n),r,a,i)]}case"Bincount":const r=mv("x",e,t,n),a=mv("weights",e,t,n),i=mv("size",e,t,n);return[s.bincount(r,a,i)];case"DenseBincount":{const r=mv("x",e,t,n),a=mv("weights",e,t,n),i=mv("size",e,t,n),o=mv("binaryOutput",e,t,n);return[s.denseBincount(r,a,i,o)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"slice_join":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"ConcatV2":case"Concat":{const r=mv("n",e,t,n),a=mv("axis",e,t,n);let i=mv("tensors",e,t,n);return i=i.slice(0,r),[s.concat(i,a)]}case"Gather":{const r=mv("x",e,t,n),a=mv("indices",e,t,n);return[s.gather(r,s.cast(a,"int32"),0)]}case"GatherV2":{const r=mv("axis",e,t,n),a=mv("batchDims",e,t,n),i=mv("x",e,t,n),o=mv("indices",e,t,n);return[s.gather(i,s.cast(o,"int32"),r,a)]}case"Reverse":{const r=mv("dims",e,t,n),a=[];for(let e=0;e{const r=mv("axis",e,t,n),a=mv("tensors",e,t,n),i=a[0].shape,o=s.squeeze(a[0]).shape,l=a.map((e=>{const t=B(e.shape,i);if(!t&&!B(s.squeeze(e).shape,o))throw new Error("the input tensors shape does not match");return t?e:s.reshape(e,i)}));return[s.stack(l,r)]}));case"Unpack":{const r=mv("axis",e,t,n),a=mv("tensor",e,t,n);return s.unstack(a,r)}case"Tile":{const r=mv("reps",e,t,n);return[s.tile(mv("x",e,t,n),r)]}case"Split":case"SplitV":{const r=mv("axis",e,t,n),a=mv("numOrSizeSplits",e,t,n),i=mv("x",e,t,n);return s.split(i,a,r)}case"ScatterNd":{const r=mv("indices",e,t,n),a=mv("values",e,t,n),i=mv("shape",e,t,n);return[s.scatterND(r,a,i)]}case"GatherNd":{const r=mv("x",e,t,n),a=mv("indices",e,t,n);return[s.gatherND(r,a)]}case"SparseToDense":{const r=mv("sparseIndices",e,t,n),a=mv("outputShape",e,t,n),i=mv("sparseValues",e,t,n),o=mv("defaultValue",e,t,n);return[s.sparseToDense(r,i,a,i.dtype===o.dtype?o:s.cast(o,i.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"sparse":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"SparseFillEmptyRows":{const{outputIndices:r,outputValues:a,emptyRowIndicator:i,reverseIndexMap:o}=s.sparse.sparseFillEmptyRows(mv("indices",e,t,n),mv("values",e,t,n),mv("denseShape",e,t,n),mv("defaultValue",e,t,n));return[r,a,i,o]}case"SparseReshape":{const{outputIndices:r,outputShape:a}=s.sparse.sparseReshape(mv("inputIndices",e,t,n),mv("inputShape",e,t,n),mv("newShape",e,t,n));return[r,a]}case"SparseSegmentMean":return[s.sparse.sparseSegmentMean(mv("data",e,t,n),mv("indices",e,t,n),mv("segmentIds",e,t,n))];case"SparseSegmentSum":return[s.sparse.sparseSegmentSum(mv("data",e,t,n),mv("indices",e,t,n),mv("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"spectral":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"FFT":return[s.fft(mv("x",e,t,n))];case"IFFT":return[s.ifft(mv("x",e,t,n))];case"RFFT":return[s.rfft(mv("x",e,t,n))];case"IRFFT":return[s.irfft(mv("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"string":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"StringNGrams":{const{nGrams:r,nGramsSplits:a}=s.string.stringNGrams(mv("data",e,t,n),mv("dataSplits",e,t,n),mv("separator",e,t,n),mv("nGramWidths",e,t,n),mv("leftPad",e,t,n),mv("rightPad",e,t,n),mv("padWidth",e,t,n),mv("preserveShortSequences",e,t,n));return[r,a]}case"StringSplit":{const{indices:r,values:a,shape:i}=s.string.stringSplit(mv("input",e,t,n),mv("delimiter",e,t,n),mv("skipEmpty",e,t,n));return[r,a,i]}case"StringToHashBucketFast":return[s.string.stringToHashBucketFast(mv("input",e,t,n),mv("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"transformation":return r((()=>((e,t,n,s=T)=>{switch(e.op){case"Cast":return[s.cast(mv("x",e,t,n),mv("dtype",e,t,n))];case"ExpandDims":{const r=mv("axis",e,t,n);return[s.expandDims(mv("x",e,t,n),r)]}case"Squeeze":{const r=mv("axis",e,t,n);return[s.squeeze(mv("x",e,t,n),r)]}case"Reshape":return[s.reshape(mv("x",e,t,n),mv("shape",e,t,n))];case"MirrorPad":return[s.mirrorPad(mv("x",e,t,n),mv("padding",e,t,n),mv("mode",e,t,n))];case"PadV2":case"Pad":return[s.pad(mv("x",e,t,n),mv("padding",e,t,n),mv("constantValue",e,t,n))];case"SpaceToBatchND":{const r=mv("blockShape",e,t,n),a=mv("paddings",e,t,n);return[s.spaceToBatchND(mv("x",e,t,n),r,a)]}case"BatchToSpaceND":{const r=mv("blockShape",e,t,n),a=mv("crops",e,t,n);return[s.batchToSpaceND(mv("x",e,t,n),r,a)]}case"DepthToSpace":{const r=mv("blockSize",e,t,n),a=mv("dataFormat",e,t,n).toUpperCase();return[s.depthToSpace(mv("x",e,t,n),r,a)]}case"BroadcastTo":return[s.broadcastTo(mv("x",e,t,n),mv("shape",e,t,n))];case"BroadcastArgs":return[s.broadcastArgs(mv("s0",e,t,n),mv("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,s)=>{switch(e.op){case"HashTable":case"HashTableV2":{const r=mv("keyDType",e,t,n),a=mv("valueDType",e,t,n),i=new pk(r,a);return s.addHashTable(e.name,i),[i.handle]}case"LookupTableImport":case"LookupTableImportV2":{const r=mv("tableHandle",e,t,n,s),a=mv("keys",e,t,n),i=mv("values",e,t,n),o=s.getHashTableById(r.id);return[await o.import(a,i)]}case"LookupTableFind":case"LookupTableFindV2":{const r=mv("tableHandle",e,t,n,s),a=mv("keys",e,t,n),i=mv("defaultValue",e,t,n),o=s.getHashTableById(r.id);return[await o.find(a,i)]}case"LookupTableSize":case"LookupTableSizeV2":{const r=mv("tableHandle",e,t,n,s);return[s.getHashTableById(r.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n,s);case"custom":const a=fv(e.op);if(a&&a.customExecutor)return a.customExecutor(new nk(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 de(a)?a.then((e=>[].concat(e))):[].concat(a)}class fk{constructor(e={},t={},n={},s={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=s,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;t0===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 mk(e,t,n,s){const r=new Set,a=[];let i=null,o=null;const l=new Set,u=Object.keys(e).map((e=>xv(e)[0]));let c=[];null!=s&&(c=s.map((e=>xv(e.name)[0])));const h=[...t];for(;h.length>0;){const e=h.pop();(xk(e)||wk(e)||vk(e))&&null==i&&(i=e,o=i.children.map((e=>e.name)).filter((e=>r.has(e)))),r.add(e.name),null==n[e.name]&&(-1===u.indexOf(e.name)&&-1===c.indexOf(e.name)&&(0!==e.inputs.length?e.inputs.forEach((e=>{l.has(e.name)||(l.add(e.name),h.push(e))})):a.push(e.name)))}return{inputs:e,outputs:t,usedNodes:r,missingInputs:a,dynamicNode:i,syncInputs:o}}const gk=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],yk=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],bk=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function xk(e){return gk.indexOf(e.op)>=0}function wk(e){return yk.indexOf(e.op)>=0}function vk(e){return bk.indexOf(e.op)>=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 kk{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,null!=e.functions&&Object.keys(e.functions).forEach((t=>{this._functionExecutorMap[t]=new kk(e.functions[t],this)}))}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){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)),{})}getCompilationKey(e,t){const n=e.map((e=>e.name)).sort(),s=t.map((e=>e.name)).sort();return n.join(this.SEPERATOR)+"--"+s.join(this.SEPERATOR)}compile(e,t){const n=mk(e,t,this.weightMap,this._initNodes),{missingInputs:s,dynamicNode:r,syncInputs:a}=n;if(null!=r)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(s.length>0){const n=t.map((e=>e.name)),r=Object.keys(e);throw new Error(`Cannot compute the outputs [${n}] from the provided inputs [${r}]. Missing the following inputs: [${s}]`)}return function(e,t,n){const{usedNodes:s,inputs:r}=n,a=[],i=Object.keys(r).map((e=>xv(e)[0])).map((t=>e.nodes[t])),o=e.initNodes;i.forEach((e=>{s.has(e.name)&&a.push(e)})),e.weights.forEach((e=>{s.has(e.name)&&a.push(e)})),null!=o&&o.forEach((e=>{s.has(e.name)&&a.push(e)}));const l=new Set,u=[];for(;a.length>0;){const e=a.pop();l.add(e.name),t[e.name]||u.push(e),e.children.forEach((e=>{!l.has(e.name)&&s.has(e.name)&&e.inputs.every((e=>l.has(e.name)))&&a.push(e)}))}return u}(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);const n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);const s=n.map((e=>this.graph.nodes[xv(e)[0]])),r=t.map((e=>xv(e)[0]));let a=r.map((e=>this.graph.nodes[e]));this.resetIntermediateTensors(),0===a.length&&(a=this._outputs);const i=this.getCompilationKey(s,a);let o=this.compiledMap.get(i);null==o&&(o=this.compile(e,a),this.compiledMap.set(i,o));const l={},u={};return Zi((()=>{const n=new fk(this.weightMap,l,u,this.functionExecutorMap),s=Object.assign({},this.weightMap);Object.keys(e).forEach((t=>{const[n,r]=xv(t),a=[];a[r]=e[t],s[n]=a}));const a=this.getFrozenTensorIds(s),i={};for(let e=0;egv(e,s,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,s,r,a,i){"control"!==t.category&&-1===a.indexOf(e)&&(n[e].forEach((e=>{null!=e&&(i[e.id]=(i[e.id]||0)+t.children.length)})),t.inputs.forEach((e=>{if("control"!==e.category){const a=function(e,t,n){return t[bv(e,n.currentContextId)]}(e.name,n,s);null!=a&&a.forEach((e=>{if(e&&!e.kept&&!r.has(e.id)){const n=i[e.id];if(1===n){if(this.keepTensorForDebug){const[n,r]=yv(t.name,s);this.intermediateTensors[n]||(this.intermediateTensors[n]=[]),this.intermediateTensors[n][r]=e}else e.dispose();delete i[e.id]}else null!=n&&i[e.id]--}}))}})))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){this.intermediateTensors&&(Object.keys(this.intermediateTensors).forEach((e=>this.intermediateTensors[e].forEach((e=>e.dispose())))),this.disposeTensorsMap())}disposeTensorsMap(){this.tensorsMap&&Object.keys(this.tensorsMap).forEach((e=>{this.tensorsMap[e].forEach((e=>{!e||e.kept||e.isDisposed||this.keepIds.has(e.id)||e.dispose()}))}))}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(const e in this.intermediateTensors)this.intermediateTensors[e].forEach((e=>e.dispose())),delete this.intermediateTensors[e]}async _executeAsync(e,t,n=!1,s={},r={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepTensorForDebug=ye().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){console.warn(e.message)}this.resetIntermediateTensors();const a=new fk(this.weightMap,s,r,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(e,a,t,n);const i=t.map((e=>gv(e,this.tensorsMap,a))),o=i.map((e=>e.id)),l=Object.keys(e).map((t=>e[t].id));return this.keepIds=new Set([...o,...l,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),null==this.parent&&a.dispose(this.keepIds),i}async executeFunctionAsync(e,t,n){const s=e.reduce(((e,t,n)=>(e[this.inputs[n].name]=t,e)),{});return this._executeAsync(s,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,s){const r=Object.keys(e),a=r.map((e=>this.graph.nodes[xv(e)[0]])),i=n.map((e=>xv(e)[0]));let o=i.map((e=>this.graph.nodes[e]));0===o.length&&(o=this._outputs);const{usedNodes:l,missingInputs:u,dynamicNode:c,syncInputs:h}=mk(e,o,this.weightMap,this._initNodes),p=[...a,...this.graph.weights,...this._initNodes||[]].map((e=>({node:e,contexts:t.currentContext}))),d=Object.assign({},this.weightMap);Object.keys(e).forEach((t=>{const[n,s]=xv(t),r=[];r[s]=e[t],d[n]=r}));const f={},m=this.getFrozenTensorIds(d),g={};for(;p.length>0;){const e=this.processStack(a,p,t,d,g,m,i,f,l);await Promise.all(e)}null!=c||s||console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");const y=o.filter((e=>!xk(e)&&!gv(e.name,d,t))).map((e=>e.name));if(y.length>0){let e="";throw null!=c&&(e=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${h}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${e}`)}return d}processStack(e,t,n,s,r,a,i,o,l){const u=[];for(;t.length>0;){const e=t.pop();n.currentContext=e.contexts;let c="";if("Enter"===e.node.op&&mv("isConstant",e.node,s,n)&&([c]=yv(e.node.name,n)),null==s[e.node.name]){const h=dk(e.node,s,n,this._resourceManager);c||([c]=yv(e.node.name,n));const p=n.currentContext;de(h)?u.push(h.then((u=>(s[c]=u,n.currentContext=p,this.checkTensorForDisposal(c,e.node,s,n,a,i,o),this.processChildNodes(e.node,t,n,s,r,l),u)))):(s[c]=h,this.checkTensorForDisposal(c,e.node,s,n,a,i,o),this.processChildNodes(e.node,t,n,s,r,l))}else this.processChildNodes(e.node,t,n,s,r,l)}return u}processChildNodes(e,t,n,s,r,a){e.children.forEach((e=>{const[i]=yv(e.name,n);!r[i]&&a.has(e.name)&&("Merge"===e.op?e.inputNames.some((e=>!!gv(e,s,n)))&&(r[i]=!0,t.push({contexts:n.currentContext,node:e})):e.inputNames.every((e=>!!gv(e,s,n)))&&(r[i]=!0,t.push({contexts:n.currentContext,node:e})))}))}dispose(){Object.keys(this.weightMap).forEach((e=>this.weightMap[e].forEach((e=>e.dispose()))))}checkInputShapeAndType(e){Object.keys(e).forEach((t=>{const n=e[t],[s]=xv(t),r=this.graph.nodes[s];if(r.attrParams.shape&&r.attrParams.shape.value){const e=r.attrParams.shape.value;O(e.length===n.shape.length&&n.shape.every(((t,n)=>-1===e[n]||e[n]===t)),(()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${e}], but was [${n.shape}]`))}r.attrParams.dtype&&r.attrParams.dtype.value&&O(n.dtype===r.attrParams.dtype.value,(()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${n.dtype}`))}))}mapInputs(e){const t={};for(const n in e)if(null!=this._signature&&null!=this._signature.inputs&&null!=this._signature.inputs[n]){t[this._signature.inputs[n].name]=e[n]}else t[n]=e[n];return t}checkInputs(e){const t=Object.keys(e).filter((e=>{const[t]=xv(e);return null==this.graph.nodes[t]}));if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map((e=>{if(null!=this._signature&&null!=this._signature.outputs&&null!=this._signature.outputs[e]){return this._signature.outputs[e].name}return e}),{})}checkOutputs(e){e.forEach((e=>{const[t]=xv(e);if(!this.graph.nodes[t])throw new Error(`The output '${e}' is not found in the graph`)}))}}class Ik{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 Nk="?tfjs-format=file",Sk="model.json";class Tk{constructor(t,n={},s=e){this.modelUrl=t,this.loadOptions=n,this.version="n/a",this.io=s,null==n&&(this.loadOptions={}),this.resourceManager=new Ik}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){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 '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),null==this.handler.load)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");const e=this.handler.load();return de(e)?e.then((e=>this.loadSync(e))):this.loadSync(e)}loadSync(e){this.artifacts=e;const t=this.artifacts.modelTopology;let n=this.artifacts.signature;if(null!=this.artifacts.userDefinedMetadata){const e=this.artifacts.userDefinedMetadata;null!=e.signature&&(n=e.signature),null!=e.structuredOutputKeys&&(this.structuredOutputKeys=e.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;const s=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new kk(Wv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(s),this.executor.resourceManager=this.resourceManager,null!=e.modelInitializer&&null!=e.modelInitializer.node){const t=Wv.Instance.transformGraph(e.modelInitializer);this.initializer=new kk(t),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if("string"==typeof e){const t=this.io.getSaveHandlers(e);if(0===t.length)throw new Error(`Cannot find any save handlers for URL '${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)}predict(e,t){const n=this.execute(e,this.outputNodes);if(this.structuredOutputKeys){const e={};return(n instanceof gr?[n]:n).forEach(((t,n)=>e[this.structuredOutputKeys[n]]=t)),e}return n}normalizeInputs(e){if(!(e instanceof gr||Array.isArray(e)))return e;if((e=Array.isArray(e)?e:[e]).length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce(((t,n,s)=>(t[n]=e[s],t)),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);const n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);const n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce(((t,n)=>(t[n]=[e[n]],t)),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}}async function Ck(t,n={},s=e){if(null==t)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");null==n&&(n={}),n.fromTFHub&&"string"==typeof t&&(t=function(e){e.endsWith("/")||(e+="/");return`${e}${Sk}${Nk}`}(t));const r=new Tk(t,n,s);return await r.load(),r}function $k(e,t,n=new Map,s=new Set){if(null==e)return null;if("function"==typeof Blob&&e instanceof Blob)return e.slice();if(s.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);const r=t(e);if(r.recurse&&null!==r.value)throw new Error("A deep map function may not return both a value and recurse=true.");if(r.recurse){if(Fk(e)){const r=Array.isArray(e)?[]:{};s.add(e);for(const a in e){const i=$k(e[a],t,n,s);r[a]=i}return s.delete(e),e.__proto__&&(r.__proto__=e.__proto__),r}throw new Error(`Can't recurse into non-iterable type: ${e}`)}return n.set(e,r.value),r.value}function Ek(e,t=Ak){return Rk(e,t)}function Rk(e,t,n=new Set){const s=e[0];if(n.has(s))throw new Error("Circular references are not supported.");const r=t(e);if(r.recurse&&null!==r.value)throw new Error("A deep zip function may not return both a value and recurse=true.");if(r.recurse){if(Fk(s)){const r=Array.isArray(s)?[]:{};n.add(s);for(const a in s){const s=e.map((e=>e[a])),i=Rk(s,t,n);r[a]=i}return n.delete(s),r}throw new Error(`Can't recurse into non-iterable type: ${s}`)}return r.value}function Ak(e){return null===e?null:Fk(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}function Fk(e){let t=!1;if(ye().get("IS_BROWSER"))t=e instanceof TextDecoder;else{const{StringDecoder:s}=n(551);t=e instanceof s}return null!=e&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||"object"==typeof e&&!(e instanceof gr)&&!(e instanceof Promise)&&!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 _k(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.
+ *
+ * =============================================================================
+ */
+return function(e,t){return $k(e,t)}(e,Dk)}function Dk(e){return e instanceof gr?{value:e.clone(),recurse:!1}:Fk(e)?{value:null,recurse:!0}:{value:e,recurse:!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.
+ *
+ * =============================================================================
+ */
+class Ok{constructor(e){if(this.capacity=e,this.begin=0,this.end=0,null==e)throw new RangeError("Can't create a ring buffer of unknown capacity.");if(e<1)throw new RangeError("Can't create ring buffer of capacity < 1.");this.data=new Array(e),this.doubledCapacity=2*e}wrap(e){for(;e<0;)e+=this.doubledCapacity;return e%this.doubledCapacity}get(e){if(e<0)throw new RangeError("Can't get item at a negative index.");return this.data[e%this.capacity]}set(e,t){if(e<0)throw new RangeError("Can't set item at a negative index.");this.data[e%this.capacity]=t}length(){let e=this.end-this.begin;return e<0&&(e=this.doubledCapacity+e),e}isFull(){return this.length()===this.capacity}isEmpty(){return 0===this.length()}push(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(const t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);const e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");const e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");const t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),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 Mk extends Ok{constructor(){super(Mk.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){const e=2*this.capacity,t=new Array(e),n=this.length();for(let e=0;e!0===e))}rowMajorBatch(e,t=!0){return new Hk(this,e,t)}columnMajorBatch(e,t=!0,n=Ak){return this.rowMajorBatch(e,t).map((e=>Ek(e,n)))}concatenate(e,t){return new Jk(new Bk([this,e]),t)}take(e){return e<0||null==e?this:new Gk(this,e)}skip(e){return e<0||null==e?this:new Uk(this,e)}prefetch(e){return new eI(this,e)}shuffle(e,t){return new tI(this,e,t)}serial(){return new Vk(this)}}class Bk extends Pk{constructor(e){super(),this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};const e=this.items[this.trav];return this.trav++,{value:_k(e),done:!1}}}class Wk extends Pk{constructor(e){super(),this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}}class Vk extends Pk{constructor(e){super(),this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then((()=>this.serialNext())),this.lastRead}async serialNext(){return this.upstream.next()}}class Uk extends Pk{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then((()=>this.serialNext())),this.lastRead}async serialNext(){for(;this.count++ Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}}class Hk extends Pk{constructor(e,t,n=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then((()=>this.serialNext())),this.lastRead}async serialNext(){const e=[];for(;e.length0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}}class jk extends Pk{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then((()=>this.serialNext())),this.lastRead}async serialNext(){for(;;){const e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Ji(e.value)}}}class qk extends Pk{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){const e=await this.upstream.next();if(e.done)return{value:null,done:!0};const t=Er(e.value),n=this.transform(e.value),s=Er(n);for(const e of t)$r(e,s)||e.dispose();return{value:n,done:!1}}}class Kk extends Pk{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then((()=>this.serialNext())),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}}class Xk extends Pk{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){const e=await this.upstream.next();if(e.done)return{value:null,done:!0};const t=Er(e.value),n=await this.transform(e.value),s=Er(n);for(const e of t)$r(e,s)||e.dispose();return{value:n,done:!1}}}class Yk extends Pk{constructor(){super(),this.outputQueue=new Mk,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then((()=>this.serialNext())),this.lastRead}async serialNext(){for(;0===this.outputQueue.length();)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}}class Zk extends Yk{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){const e=await this.upstream.next();if(e.done)return!1;const t=Er(e.value),n=this.transform(e.value),s=Er(n);this.outputQueue.pushAll(n);for(const e of t)$r(e,s)||e.dispose();return!0}}class Jk extends Pk{constructor(e,t){super(),this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,null==this.iterator){const e=await this.moreIterators.next();if(e.done)return{value:null,done:!0};this.iterator=e.value,null!=this.baseErrorHandler&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}const t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}}var Qk;!function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"}(Qk||(Qk={}));class eI extends Pk{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new Ok(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){const e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}}class tI extends eI{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=nc.alea(n||tr().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then((()=>this.serialNext())),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){const e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(!t.done)return this.refill(),t;this.upstreamExhausted=!0}return{value:null,done:!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 nI{constructor(){this.size=null}batch(e,t=!0){const n=this;let s;return O(e>0,(()=>`batchSize needs to be positive, but it is\n ${e}`)),s=this.size===1/0||null==this.size?this.size:t?Math.ceil(this.size/e):Math.floor(this.size/e),sI((async()=>(await n.iterator()).columnMajorBatch(e,t,rI)),s)}concatenate(e){const t=this;let n;return n=this.size===1/0||e.size===1/0?1/0:null!=this.size&&null!=e.size?this.size+e.size:null,sI((async()=>(await t.iterator()).concatenate(await e.iterator())),n)}filter(e){const t=this;let n;return n=this.size===1/0?1/0:null,sI((async()=>(await t.iterator()).filter((t=>Zi((()=>e(t)))))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){const t=this;return sI((async()=>(await t.iterator()).map((t=>Zi((()=>e(t)))))),this.size)}mapAsync(e){const t=this;return sI((async()=>(await t.iterator()).mapAsync(e)),this.size)}prefetch(e){if(null==e)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");const t=this;return sI((async()=>(await t.iterator()).prefetch(e)),this.size)}repeat(e){const t=this;let n;return n=null!=this.size&&e>0?this.size*e:0===e?0:null!=this.size&&(void 0===e||e<0)?1/0:null,sI((async()=>zk(Lk((async()=>({value:await t.iterator(),done:!1}))).take(e))),n)}skip(e){const t=this;let n;return n=null!=this.size&&e>=0&&this.size>=e?this.size-e:null!=this.size&&(this.size(await t.iterator()).skip(e)),n)}shuffle(e,t,n=!0){if(null==e||e<0)throw null==this.size?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);const s=this,r=nc.alea(t||tr().toString());return sI((async()=>{let t=r.int32();return n&&(t+=r.int32()),(await s.iterator()).shuffle(e,t.toString())}),this.size)}take(e){const t=this;let n;return n=null!=this.size&&this.size>e?e:null!=this.size&&this.size<=e?this.size:null,sI((async()=>(await t.iterator()).take(e)),n)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}}function sI(e,t=null){return new class extends nI{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function rI(e){if(null===e)return null;const t=e[0];if(null==(n=t)||null===(s=n)||"object"!=typeof s&&"function"!=typeof s||Array.isArray(n)||"object"==typeof n&&n instanceof gr||Z(n)){return{value:function(e){if(0===e.length)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof gr?Bc(e):Yr(e)}(e),recurse:!1}}var n,s;return{value:null,recurse:!0}}nI.MAX_BUFFER_SIZE=1e4;
+/**
+ * @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.
+ *
+ * =============================================================================
+ */
+Symbol("out"),Symbol("field"),Symbol("quote"),Symbol("quoteafterquote"),Symbol("quoteinquote");
+/**
+ * @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 aI(e,t){Array.isArray(e)||(e=[e]),e.forEach((e=>{null!=e&&O("complex64"!==e.dtype,(()=>`${t} does not support complex64 tensors in the CPU backend.`))}))}
+/**
+ * @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 iI=nh;class oI extends E{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new $(this,Xi())}nextDataId(){return oI.nextDataId++}write(e,t,n){this.firstUse&&(this.firstUse=!1,ye().get("IS_NODE")&&Es("\n============================\nHi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. \n============================"));const s={id:this.nextDataId()};return this.data.set(s,{values:e,dtype:n,refCount:1}),s}makeTensorInfo(e,t,n){let s;if("string"===t&&null!=n&&n.length>0&&Q(n[0])){const r=n.map((e=>nr(e)));s=this.write(r,e,t)}else s=this.write(n,e,t);return{dataId:s,shape:e,dtype:t}}refCount(e){if(this.data.has(e)){return this.data.get(e).refCount}return 0}incRef(e){this.data.get(e).refCount++}decRef(e){if(this.data.has(e)){this.data.get(e).refCount--}}move(e,t,n,s,r){this.data.set(e,{values:t,dtype:s,refCount:r})}numDataIds(){return this.data.numDataIds()}async read(e){return this.readSync(e)}readSync(e){const{dtype:t,complexTensorInfos:n}=this.data.get(e);if("complex64"===t){return cd(this.readSync(n.real.dataId),this.readSync(n.imag.dataId))}return this.data.get(e).values}bufferSync(e){const t=this.readSync(e.dataId);if("string"===e.dtype)try{const n=t.map((e=>sr(e)));return Ya(e.shape,e.dtype,n)}catch(e){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ya(e.shape,e.dtype,t)}makeOutput(e,t,n){return Xi().makeTensorFromTensorInfo(this.makeTensorInfo(t,n,e),this)}disposeData(e,t=!1){if(this.data.has(e)){if(this.data.get(e).refCount--,!t&&this.data.get(e).refCount>0)return!1;const{complexTensorInfos:n}=this.data.get(e);null!=n&&(this.disposeData(n.real.dataId,!0),this.disposeData(n.imag.dataId,!0)),this.data.delete(e)}return!0}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}async time(e){const t=tr();e();return{kernelMs:tr()-t}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]}}where(e){aI([e],"where");const t=this.readSync(e.dataId);return iI(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}}oI.nextDataId=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 lI(e,t,n){return({inputs:s,attrs:r,backend:a})=>{const{x:i}=s;if(aI(i,e),"string"===i.dtype||"string"===n)throw new Error("unaryKernelFunc does not support string input/output");const o=a,l=o.data.get(i.dataId).values,u=P(i.shape),c=n||i.dtype,h=X(c,u);for(let e=0;e{const{x:i}=s;if(aI(i,e),"string"===i.dtype||"string"===n)throw new Error("unaryKernelFunc does not support string input/output");const o=a,l=o.data.get(i.dataId).values,u=n||i.dtype,c=t(l,u,r);return o.makeTensorInfo(i.shape,u,c)}}
+/**
+ * @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.
+ * =============================================================================
+ */
+eo("cpu",(()=>new oI),1);
+/**
+ * @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.
+ * =============================================================================
+ */
+const cI=lI(bt,(e=>e>=0?e:Math.exp(e)-1)),hI={kernelName:bt,backendName:"cpu",kernelFunc:cI};
+/**
+ * @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 pI(e){const{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}const dI={kernelName:Ot,backendName:"cpu",kernelFunc:pI};
+/**
+ * @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 fI(e){const{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s;aI([r],"leakyRelu");const i=P(r.shape),o=n.data.get(r.dataId).values,l=K("float32",i);for(let e=0;e{const i=ki(t,n),o=i.length,l=re(i),u=K(a,P(i)),c=t.length,h=n.length,p=re(t),d=re(n),f=wi(t,i),m=wi(n,i);if(f.length+m.length===0)for(let t=0;ta[e]=0));const i=he(a,c,p),g=n.slice(-h);m.forEach((e=>g[e]=0));const y=he(g,h,d);u[t]=e(s[i],r[y])}return[u,i]}}
+/**
+ * @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.
+ * =============================================================================
+ */
+const yI=gI(((e,t)=>e<0?t*e:e));function bI(e){const{inputs:t,backend:n}=e,{x:s,alpha:r}=t;aI([s,r],"prelu");const a=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,[o,l]=yI(s.shape,r.shape,a,i,"float32");return n.makeTensorInfo(l,"float32",o)}const xI={kernelName:In,backendName:"cpu",kernelFunc:bI},wI=lI(Rn,(e=>Math.max(0,e))),vI={kernelName:Rn,backendName:"cpu",kernelFunc:wI},kI=lI(Mn,(e=>Math.min(Math.max(0,e),6))),II={kernelName:Mn,backendName:"cpu",kernelFunc:kI};
+/**
+ * @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 NI(e){return(t,n,s)=>{const r=K(n,t.length);for(let n=0;n1/(1+Math.exp(-e)))),TI=lI(Kn,(e=>1/(1+Math.exp(-e)))),CI={kernelName:Kn,backendName:"cpu",kernelFunc:TI};
+/**
+ * @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 $I(e,t,n,s,r){if("linear"===n)return pI({inputs:{x:t},backend:e});if("relu"===n)return wI({inputs:{x:t},backend:e});if("elu"===n)return cI({inputs:{x:t},backend:e});if("relu6"===n)return kI({inputs:{x:t},backend:e});if("prelu"===n)return bI({inputs:{x:t,alpha:s},backend:e});if("leakyrelu"===n)return fI({inputs:{x:t},backend:e,attrs:{alpha:r}});if("sigmoid"===n)return TI({inputs:{x:t},backend:e});throw new Error(`Activation ${n} has not been implemented for the CPU backend.`)}
+/**
+ * @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 EI(e){const{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,o=n.makeTensorInfo(s.shape,"complex64");return n.data.get(o.dataId).complexTensorInfos={real:n.makeTensorInfo(s.shape,"float32",a),imag:n.makeTensorInfo(r.shape,"float32",i)},o}const RI={kernelName:qe,backendName:"cpu",kernelFunc:EI};
+/**
+ * @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 AI(e,t,n="float32"){if("complex64"===n){return EI({inputs:{real:AI(e,t,"float32"),imag:AI(e,t,"float32")},backend:e})}const s=le(P(t),n);return e.makeTensorInfo(t,n,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 FI(e){const{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.real,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}const _I={kernelName:$n,backendName:"cpu",kernelFunc:FI};
+/**
+ * @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 DI(e,t,n,s){if("int32"===s){return[t,"int32",Int32Array.from(e)]}if("bool"===s){const s=er([0],n),[r,a]=gI(((e,t)=>e!==t?1:0))(t,[],e,s,"bool");return[a,"bool",r]}throw new Error(`Error in Cast: failed to cast ${n} to ${s}`)}function OI(e){const{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if("complex64"===a){if("complex64"===r.dtype)return pI({inputs:{x:r},backend:n});const e=AI(n,r.shape,r.dtype),t=OI({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),s=EI({inputs:{real:t,imag:e},backend:n});return n.disposeIntermediateTensorInfo(e),n.disposeIntermediateTensorInfo(t),s}if("complex64"===r.dtype){const e=FI({inputs:{input:r},backend:n}),t=OI({inputs:{x:e},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(e),t}if(!Y(r.dtype,a)){const e=pI({inputs:{x:r},backend:n});return{dataId:e.dataId,shape:e.shape,dtype:a}}const i=n.data.get(r.dataId).values,[o,l,u]=DI(i,r.shape,r.dtype,a);return n.makeTensorInfo(o,l,u)}const MI={kernelName:Ge,backendName:"cpu",kernelFunc:OI};
+/**
+ * @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 LI(e,t,n,s){return null==n?({inputs:n,backend:r})=>{const{a,b:i}=n,o=r;aI([a,i],e);const l=o.data.get(a.dataId).values,u=o.data.get(i.dataId).values,c="string"===a.dtype?Gd(l):l,h="string"===a.dtype?Gd(u):u,p=s||a.dtype,[d,f]=t(a.shape,i.shape,c,h,p);return o.makeTensorInfo(f,p,d)}:({inputs:e,backend:r})=>{const{a,b:i}=e,o=r;if("complex64"===a.dtype||"complex64"===i.dtype){const e=OI({inputs:{x:a},backend:o,attrs:{dtype:"complex64"}}),t=o.data.get(e.dataId),s=t.complexTensorInfos.real,r=t.complexTensorInfos.imag,l=o.data.get(s.dataId).values,u=o.data.get(r.dataId).values,c=OI({inputs:{x:i},backend:o,attrs:{dtype:"complex64"}}),h=o.data.get(c.dataId),p=h.complexTensorInfos.real,d=h.complexTensorInfos.imag,f=o.data.get(p.dataId).values,m=o.data.get(d.dataId).values,[g,y,b]=n(a.shape,i.shape,l,u,f,m),x=o.makeTensorInfo(b,"float32",g),w=o.makeTensorInfo(b,"float32",y),v=EI({inputs:{real:x,imag:w},backend:o});return o.disposeIntermediateTensorInfo(e),o.disposeIntermediateTensorInfo(c),o.disposeIntermediateTensorInfo(x),o.disposeIntermediateTensorInfo(w),v}{const e=o.data.get(a.dataId).values,n=o.data.get(i.dataId).values,r=s||a.dtype,[l,u]=t(a.shape,i.shape,e,n,r);return o.makeTensorInfo(u,r,l)}}}function zI(e){return(t,n,s,r,a,i)=>{const o=ki(t,n),l=P(o),u=o.length,c=re(o),h=K("float32",l),p=K("float32",l),d=wi(t,o),f=wi(n,o),m=cd(s,r),g=cd(a,i),y=t.length,b=re(t),x=n.length,w=re(n);if(d.length+f.length===0)for(let t=0;ts[e]=0));const r=he(s,y,b),a=n.slice(-x);f.forEach((e=>a[e]=0));const i=he(a,x,w),o=e(m[2*r],m[2*r+1],g[2*i],g[2*i+1]);h[t]=o.real,p[t]=o.imag}return[h,p,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.
+ * =============================================================================
+ */
+const PI=gI(((e,t)=>e+t)),BI=zI(((e,t,n,s)=>({real:e+n,imag:t+s}))),WI=LI(Se,PI,BI),VI={kernelName:Se,backendName:"cpu",kernelFunc:WI};
+/**
+ * @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 UI(e){const{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,i=P(r.shape),o=H(a,i),l=P(o);O(i===l,(()=>`The new shape (${o}) has ${l} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`)),n.incRef(r.dataId);const u=n.data.get(r.dataId);if(null!=u.complexTensorInfos){const e=u.complexTensorInfos.real,t=u.complexTensorInfos.imag;e.shape=o,t.shape=o}return{dataId:r.dataId,shape:o,dtype:r.dtype}}const GI={kernelName:An,backendName:"cpu",kernelFunc:UI};
+/**
+ * @license
+ * Copyright 2020 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the License);
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+function HI(e){const{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:i,transposeB:o}=s;aI([r,a],"matMul");const l=r.shape.length,u=a.shape.length,c=i?r.shape[l-2]:r.shape[l-1],h=o?a.shape[u-1]:a.shape[u-2],p=i?r.shape[l-1]:r.shape[l-2],d=o?a.shape[u-2]:a.shape[u-1],f=r.shape.slice(0,-2),m=a.shape.slice(0,-2),g=P(f),y=P(m),b=ki(r.shape.slice(0,-2),a.shape.slice(0,-2)).concat([p,d]);O(c===h,(()=>`Error in matMul: inner shapes (${c}) and (${h}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${i} and transposeB=${o} must match.`));const x=o?[y,d,h]:[y,h,d],w=UI({inputs:{x:r},backend:n,attrs:{shape:i?[g,c,p]:[g,p,c]}}),v=UI({inputs:{x:a},backend:n,attrs:{shape:x}}),k=i?w.shape[1]:w.shape[2],I=i?w.shape[2]:w.shape[1],N=o?v.shape[1]:v.shape[2],S=Math.max(g,y),T=n.data.get(w.dataId).values,C=n.data.get(v.dataId).values,$=re(w.shape),E=re(v.shape),[R,A,F]=i?[$[0],1,$[1]]:[$[0],$[1],1],[_,D,M]=o?[1,E[1],E[0]]:[E[1],1,E[0]],L=I*N,z=Ya([S,I,N],w.dtype),B=z.values,W=n.blockSize;for(let e=0;e{const{x:t}=e.inputs,n=e.backend;aI(t,"abs");let s=new Float32Array(P(t.shape));return s=KI(n.data.get(t.dataId).values),n.makeOutput(s,t.shape,t.dtype)}},YI=lI(Ie,(e=>Math.acos(e))),ZI={kernelName:Ie,backendName:"cpu",kernelFunc:YI},JI=lI(Ne,(e=>Math.acosh(e))),QI={kernelName:Ne,backendName:"cpu",kernelFunc:JI};const eN={kernelName:Te,backendName:"cpu",kernelFunc:
+/**
+ * @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{inputs:t,backend:n}=e,s=t;aI(t,"addN");const r=s.map((e=>n.data.get(e.dataId).values)),a=Ya(s[0].shape,s[0].dtype),i=a.values;for(let e=0;en&&(n=r,s=e)}p[e]=s}return u.forEach((e=>n.disposeIntermediateTensorInfo(e))),n.makeTensorInfo(c,"int32",p)}};const oN={kernelName:Re,backendName:"cpu",kernelFunc:
+/**
+ * @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{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;aI(r,"argMin");let i=j(a,r.shape);const o=Ol(i,r.shape.length);let l=r;const u=[];null!=o&&(l=nN({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=Ll(i.length,l.shape.length)),i=[i[0]],Dl("argMin",i,l.shape.length);const[c,h]=Fl(l.shape,i),p=le(P(c),"int32"),d=P(h),f=n.data.get(l.dataId).values;for(let e=0;en.disposeIntermediateTensorInfo(e))),n.makeTensorInfo(c,"int32",p)}},lN=lI(Ae,(e=>Math.asin(e))),uN={kernelName:Ae,backendName:"cpu",kernelFunc:lN},cN=lI(Fe,(e=>Math.asinh(e))),hN={kernelName:Fe,backendName:"cpu",kernelFunc:cN},pN=lI(_e,(e=>Math.atan(e))),dN={kernelName:_e,backendName:"cpu",kernelFunc:pN},fN=gI(((e,t)=>Math.atan2(e,t))),mN=LI(Oe,fN),gN={kernelName:Oe,backendName:"cpu",kernelFunc:mN},yN=lI(De,(e=>Math.atanh(e))),bN={kernelName:De,backendName:"cpu",kernelFunc:yN};
+/**
+ * @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 xN(e,t,n,s,r,a){const i=r.strideHeight,o=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,h=r.effectiveFilterWidth,p=r.padInfo.top,d=r.padInfo.left,f="max"===a?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Ya(r.outShape,n),g=m.values,y=r.outShape[1]*r.outShape[2]*r.outShape[3],b=r.outShape[2]*r.outShape[3],x=r.outShape[3];for(let t=0;ty?y=i:"avg"===a&&(b+=i,w++)}if(isNaN(y))break}g[I+n*x+t]="avg"===a?b/w:y}}}return m}function wN(e,t,n,s,r=!1,a=!1){const i=Ya(s.outShape,"int32"),o=s.strideHeight,l=s.strideWidth,u=s.dilationHeight,c=s.dilationWidth,h=s.effectiveFilterHeight,p=s.effectiveFilterWidth,d=s.padInfo.top,f=s.padInfo.left,m=Ya(t,n,e);for(let e=0;ew&&(w=u,v=r?a?((e*s.inHeight+n)*s.inWidth+o)*s.inChannels+t:(n*s.inWidth+o)*s.inChannels+t:i*p+l)}}i.set(v,e,n,o,t)}}return i}function vN(e,t,n,s,r,a){const i=r.strideDepth,o=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,h=r.dilationWidth,p=r.effectiveFilterDepth,d=r.effectiveFilterHeight,f=r.effectiveFilterWidth,m=r.padInfo.front,g=r.padInfo.top,y=r.padInfo.left,b="max"===a?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,x=Ya(r.outShape,n),w=x.values,v=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],k=r.outShape[2]*r.outShape[3]*r.outShape[4],I=r.outShape[3]*r.outShape[4],N=r.outShape[4];for(let t=0;tk?k=r:"avg"===a&&(I+=r,S++),isNaN(k))break}if(isNaN(k))break}if(isNaN(k))break}w[g+t]="avg"===a?I/S:k}}}}return x}const kN={kernelName:Me,backendName:"cpu",kernelFunc:
+/**
+ * @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{inputs:t,backend:n,attrs:s}=e,{x:r}=t;aI(r,"avgPool");const{filterSize:a,strides:i,pad:o,dimRoundingMode:l}=s;O(Ro(i,1),(()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '1'`));const u=wo(r.shape,a,i,1,o,l);let c;if(1===u.filterWidth&&1===u.filterHeight&&B(u.inShape,u.outShape))c=pI({inputs:{x:r},backend:n});else{const e=n.data.get(r.dataId).values,t=re(r.shape),s=xN(e,r.shape,r.dtype,t,u,"avg");c=n.makeTensorInfo(u.outShape,r.dtype,s.values)}return c}};const IN={kernelName:ze,backendName:"cpu",kernelFunc:
+/**
+ * @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{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=s;aI(r,"avgPool3d");const c=vo(r.shape,a,i,1,o,l,u),h=vN(n.data.get(r.dataId).values,r.shape,r.dtype,re(r.shape),c,"avg");return n.makeTensorInfo(h.shape,"float32",h.values)}};const NN={kernelName:Pe,backendName:"cpu",kernelFunc:
+/**
+ * @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{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=s;aI([r,a],"avgPool3DGrad");const c=vo(a.shape,i,o,1,l,u),h=c.strideDepth,p=c.strideHeight,d=c.strideWidth,f=c.filterDepth,m=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,b=c.dilationHeight,x=c.dilationWidth,w=c.effectiveFilterDepth,v=c.effectiveFilterHeight,k=c.effectiveFilterWidth,I=w-1-c.padInfo.front,N=k-1-c.padInfo.left,S=v-1-c.padInfo.top,T=Ya(a.shape,"float32"),C=1/(f*m*g),$=n.bufferSync(r);for(let e=0;e=c.outDepth||Math.floor(s)!==s))for(let n=0;n=c.outHeight||Math.floor(r)!==r))for(let n=0;n=c.outWidth||Math.floor(a)!==a)continue;l+=$.get(e,s,r,a,t)}}}T.set(l*C,e,n,s,r,t)}return n.makeTensorInfo(T.shape,T.dtype,T.values)}};const SN={kernelName:Le,backendName:"cpu",kernelFunc:
+/**
+ * @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{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,i=a;aI([r,a],"avgPoolGrad");const{filterSize:o,strides:l,pad:u}=s,c=wo(i.shape,o,l,1,u),h=c.strideHeight,p=c.strideWidth,d=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,b=c.effectiveFilterWidth,x=b-1-c.padInfo.left,w=y-1-c.padInfo.top,v=Ya(i.shape,"float32"),k=1/(d*f),I=n.data.get(r.dataId).values,N=Ya(r.shape,"float32",I);for(let e=0;e