text: !function (t, e) { "object" == typeof exports && "undefined" != typeof module ? e(exports) : "function" == typeof define && define.amd ? define(["exports"], e) : e((t = t || self).faceapi = t.faceapi || {}) }(this, function (c) { "use strict"; var r = function (t, e) { return (r = Object.setPrototypeOf || { __proto__: [] } instanceof Array && function (t, e) { t.__proto__ = e } || function (t, e) { for (var n in e) e.hasOwnProperty(n) && (t[n] = e[n]) })(t, e) }; function t(t, e) { function n() { this.constructor = t } r(t, e), t.prototype = null === e ? Object.create(e) : (n.prototype = e.prototype, new n) } function y(i, a, s, u) { return new (s = s || Promise)(function (t, e) { function n(t) { try { o(u.next(t)) } catch (t) { e(t) } } function r(t) { try { o(u.throw(t)) } catch (t) { e(t) } } function o(e) { e.done ? t(e.value) : new s(function (t) { t(e.value) }).then(n, r) } o((u = u.apply(i, a || [])).next()) }) } function R(n, r) { var o, i, a, t, s = { label: 0, sent: function () { if (1 & a[0]) throw a[1]; return a[1] }, trys: [], ops: [] }; return t = { next: e(0), throw: e(1), return: e(2) }, "function" == typeof Symbol && (t[Symbol.iterator] = function () { return this }), t; function e(e) { return function (t) { return function (e) { if (o) throw new TypeError("Generator is already executing."); for (; s;)try { if (o = 1, i && (a = 2 & e[0] ? i.return : e[0] ? i.throw || ((a = i.return) && a.call(i), 0) : i.next) && !(a = a.call(i, e[1])).done) return a; switch (i = 0, a && (e = [2 & e[0], a.value]), e[0]) { case 0: case 1: a = e; break; case 4: return s.label++, { value: e[1], done: !1 }; case 5: s.label++, i = e[1], e = [0]; continue; case 7: e = s.ops.pop(), s.trys.pop(); continue; default: if (!(a = 0 < (a = s.trys).length && a[a.length - 1]) && (6 === e[0] || 2 === e[0])) { s = 0; continue } if (3 === e[0] && (!a || e[1] > a[0] && e[1] < a[3])) { s.label = e[1]; break } if (6 === e[0] && s.label < a[1]) { s.label = a[1], a = e; break } if (a && s.label < a[2]) { s.label = a[2], s.ops.push(e); break } a[2] && s.ops.pop(), s.trys.pop(); continue }e = r.call(n, s) } catch (t) { e = [6, t], i = 0 } finally { o = a = 0 } if (5 & e[0]) throw e[1]; return { value: e[0] ? e[1] : void 0, done: !0 } }([e, t]) } } } var o = (e.prototype.setPlatform = function (t, e) { null != this.platform && console.warn("Platform " + this.platformName + " has already been set. Overwriting the platform with " + e + "."), this.platformName = t, this.platform = e }, e.prototype.registerFlag = function (t, e, n) { if (this.flagRegistry[t] = { evaluationFn: e, setHook: n }, null != this.urlFlags[t]) { var r = this.urlFlags[t]; console.warn("Setting feature override from URL " + t + ": " + r + "."), this.set(t, r) } }, e.prototype.get = function (t) { return t in this.flags || (this.flags[t] = this.evaluateFlag(t)), this.flags[t] }, e.prototype.getNumber = function (t) { return this.get(t) }, e.prototype.getBool = function (t) { return this.get(t) }, e.prototype.getFlags = function () { return this.flags }, Object.defineProperty(e.prototype, "features", { get: function () { return this.flags }, enumerable: !0, configurable: !0 }), e.prototype.set = function (t, e) { if (null == this.flagRegistry[t]) throw new Error("Cannot set flag " + t + " as it has not been registered."); this.flags[t] = e, null != this.flagRegistry[t].setHook && this.flagRegistry[t].setHook(e) }, e.prototype.evaluateFlag = function (t) { if (null == this.flagRegistry[t]) throw new Error("Cannot evaluate flag '" + t + "': no evaluation function found."); return this.flagRegistry[t].evaluationFn() }, e.prototype.setFlags = function (t) { this.flags = Object.assign({}, t) }, e.prototype.reset = function () { this.flags = {}, this.urlFlags = {}, this.populateURLFlags() }, e.prototype.populateURLFlags = function () { var o = this; if (void 0 !== this.global && void 0 !== this.global.location && void 0 !== this.global.location.search) { var t, r, e = (t = this.global.location.search, r = {}, t.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g, function (t) { for (var e = [], n = 1; n < arguments.length; n++)e[n - 1] = arguments[n]; return function (t, e, n) { t[decodeURIComponent(e)] = decodeURIComponent(n || "") }(r, e[0], e[1]), e.join("=") }), r); "tfjsflags" in e && e.tfjsflags.split(",").forEach(function (t) { var e = t.split(":"), n = e[0], r = e[1]; o.urlFlags[n] = function (t, e) { if ("true" === (e = e.toLowerCase()) || "false" === e) return "true" === e; if ("" + +e === e) return +e; throw new Error("Could not parse value flag value " + e + " for flag " + t + ".") }(n, r) }) } }, e); function e(t) { this.global = t, this.flags = {}, this.flagRegistry = {}, this.urlFlags = {}, this.populateURLFlags() } function _() { return i } var i = null, u = new Map, n = new Map; function g(t, e) { var n = f(t, e); return u.get(n) } function l(t) { return n.get(t) } function a(t) { for (var e = u.entries(), n = []; ;) { var r = e.next(), o = r.done, i = r.value; if (o) break; var a = i[0], s = i[1]; a.split("_")[0] === t && n.push(s) } return n } function s(t) { var e = t.kernelName, n = t.backendName, r = f(e, n); if (u.has(r)) throw new Error("The kernel '" + e + "' for backend '" + n + "' is already registered"); u.set(r, t) } function h(t) { var e = t.kernelName; n.has(e) && console.warn("Overriding the gradient for '" + e + "'"), n.set(e, t) } function f(t, e) { return e + "_" + t } function p(t) { for (var e = t.length, n = 0, r = 0; 0 < e;)r = Math.random() * e | 0, n = t[--e], t[e] = t[r], t[r] = n } function d(t, e, n) { return Math.max(t, Math.min(e, n)) } function E(t) { return t % 2 == 0 ? t : t + 1 } function v(t) { for (var e = 0, n = 0; n < t.length; n++)e += t[n]; return e } function P(t, e) { if (!t) throw new Error("string" == typeof e ? e : e()) } function x(t, e, n) { void 0 === n && (n = ""), P(A(t, e), function () { return n + " Shapes " + t + " and " + e + " must match" }) } function m(t) { P(null != t, function () { return "The input to the tensor constructor must be a non-null value." }) } function b(t, e, n) { if (void 0 === e && (e = []), void 0 === n && (n = !1), null == e && (e = []), Array.isArray(t) || z(t) && !n) for (var r = 0; r < t.length; ++r)b(t[r], e, n); else e.push(t); return e } function L(t) { if (0 === t.length) return 1; for (var e = t[0], n = 1; n < t.length; n++)e *= t[n]; return e } function A(t, e) { if (t === e) return !0; if (null == t || null == e) return !1; if (t.length !== e.length) return !1; for (var n = 0; n < t.length; n++)if (t[n] !== e[n]) return !1; return !0 } function B(t) { return t % 1 == 0 } function w(t) { if (null != Math.tanh) return Math.tanh(t); if (t === 1 / 0) return 1; if (t === -1 / 0) return -1; var e = Math.exp(2 * t); return (e - 1) / (e + 1) } function C(t) { var e = Math.ceil(Math.sqrt(t)); return [e, Math.ceil(t / e)] } function I(t, e) { return e <= t.length ? t : t + " ".repeat(e - t.length) } function k(i, a, s) { return void 0 === a && (a = function (t) { return 0 }), new Promise(function (e, n) { var r = 0, o = function () { if (i()) e(); else { var t = a(++r); null != s && s <= r ? n() : setTimeout(o, t) } }; o() }) } function S(t, e) { for (var n = 1, r = -1, o = 0; o < t.length; ++o)if (0 <= t[o]) n *= t[o]; else if (-1 === t[o]) { if (-1 !== r) throw Error("Shapes can only have 1 implicit size. Found -1 at dim " + r + " and dim " + o); r = o } else if (t[o] < 0) throw Error("Shapes can not be < 0. Found " + t[o] + " at dim " + o); if (-1 === r) { if (0 < e && e !== n) throw Error("Size(" + e + ") must match the product of shape " + t); return t } if (0 === n) throw Error("Cannot infer the missing size in [" + t + "] when there are 0 elements"); if (e % n != 0) throw Error("The implicit shape can't be a fractional number. Got " + e + " / " + n); var i = t.slice(); return i[r] = e / n, i } function D(t, e) { var n = e.length; return P((t = null == t ? e.map(function (t, e) { return e }) : [].concat(t)).every(function (t) { return -n <= t && t < n }), function () { return "All values in axis param must be in range [-" + n + ", " + n + ") but got axis " + t }), P(t.every(function (t) { return B(t) }), function () { return "All values in axis param must be integers but got axis " + t }), t.map(function (t) { return t < 0 ? n + t : t }) } function T(t, e) { for (var n = [], r = [], o = null != e && Array.isArray(e) && 0 === e.length, i = null == e || o ? null : D(e, t).sort(), a = 0, s = 0; s < t.length; ++s) { if (null != i) { if (i[a] === s && 1 !== t[s]) throw new Error("Can't squeeze axis " + s + " since its dim '" + t[s] + "' is not 1"); (null == i[a] || i[a] > s) && 1 === t[s] && (n.push(t[s]), r.push(s)), i[a] <= s && a++ } 1 !== t[s] && (n.push(t[s]), r.push(s)) } return { newShape: n, keptDims: r } } function N(t, e) { var n = null; if (null == t || "float32" === t) n = new Float32Array(e); else if ("int32" === t) n = new Int32Array(e); else { if ("bool" !== t) throw new Error("Unknown data type " + t); n = new Uint8Array(e) } return n } function F(t, e) { var n = null; if (null == t || "float32" === t) n = new Float32Array(e); else if ("int32" === t) n = new Int32Array(e); else if ("bool" === t) n = new Uint8Array(e); else { if ("string" !== t) throw new Error("Unknown data type " + t); n = new Array(e) } return n } function M(t, e) { for (var n = 0; n < t.length; n++) { var r = t[n]; if (isNaN(r) || !isFinite(r)) throw Error("A tensor of type " + e + " being uploaded contains " + r + ".") } } function O(t) { return "bool" === t || "complex64" === t || "float32" === t || "int32" === t || "string" === t } function W(t, e) { return !("complex64" === e || "float32" === e && "complex64" !== t || "int32" === e && "float32" !== t && "complex64" !== t || "bool" === e && "bool" === t) } function z(t) { return t instanceof Float32Array || t instanceof Int32Array || t instanceof Uint8Array } function U(t) { if ("float32" === t || "int32" === t) return 4; if ("complex64" === t) return 8; if ("bool" === t) return 1; throw new Error("Unknown dtype " + t) } function V(t) { if (null == t) return 0; var e = 0; return t.forEach(function (t) { return e += t.length }), e } function G(t) { return "string" == typeof t || t instanceof String } function H(t) { return "boolean" == typeof t } function q(t) { return "number" == typeof t } function j(t) { return Array.isArray(t) ? j(t[0]) : t instanceof Float32Array ? "float32" : t instanceof Int32Array || t instanceof Uint8Array ? "int32" : q(t) ? "float32" : G(t) ? "string" : H(t) ? "bool" : "float32" } function K(t) { return !!(t && t.constructor && t.call && t.apply) } function X(t, e) { for (var n = e; n < t; ++n)if (t % n == 0) return n; return t } function Y(t) { var e = t.length; if (e < 2) return []; var n = new Array(e - 1); n[e - 2] = t[e - 1]; for (var r = e - 3; 0 <= r; --r)n[r] = n[r + 1] * t[r + 1]; return n } function $(t, e, n) { if ("string" === e) throw new Error("Cannot convert a string[] to a TypedArray"); if (Array.isArray(t) && (t = b(t)), n && M(t, e), t instanceof Float32Array && "float32" === e || t instanceof Int32Array && "int32" === e || t instanceof Uint8Array && "bool" === e) return t; if (null == e || "float32" === e || "complex64" === e) return new Float32Array(t); if ("int32" === e) return new Int32Array(t); if ("bool" !== e) throw new Error("Unknown data type " + e); for (var r = new Uint8Array(t.length), o = 0; o < r.length; ++o)0 !== Math.round(t[o]) && (r[o] = 1); return r } function J(t, e) { if (0 === t.length) return e[0]; var n = t.reduce(function (t, e) { return t * e }); if (0 === n) return []; if (n !== e.length) throw new Error("[" + t + "] does not match the input size."); return function t(e, n, r) { var o = new Array; if (1 === n.length) for (var i = n[0], a = 0; a < i; a++)o[a] = r[e + a]; else { i = n[0]; var s = n.slice(1), u = s.reduce(function (t, e) { return t * e }); for (a = 0; a < i; a++)o[a] = t(e + a * u, s, r) } return o }(0, t, e) } function Q(t, e) { for (var n = Z(t, e), r = 0; r < n.length; r++)n[r] = 1; return n } function Z(t, e) { if (null == e || "float32" === e || "complex64" === e) return new Float32Array(t); if ("int32" === e) return new Int32Array(t); if ("bool" === e) return new Uint8Array(t); throw new Error("Unknown data type " + e) } function tt() { return _().platform.now() } function et(e) { e.forEach(function (t) { P(Number.isInteger(t) && 0 <= t, function () { return "Tensor must have a shape comprised of positive integers but got shape [" + e + "]." }) }) } function nt(t, e) { return void 0 === e && (e = "utf-8"), e = e || "utf-8", _().platform.encode(t, e) } function rt(t, e) { return void 0 === e && (e = "utf-8"), e = e || "utf-8", _().platform.decode(t, e) } function ot(t, e, n) { if (0 === e) return 0; if (1 === e) return t[0]; for (var r = t[t.length - 1], o = 0; o < t.length - 1; ++o)r += n[o] * t[o]; return r } function it(t, e, n) { if (0 === e) return []; if (1 === e) return [t]; for (var r = new Array(e), o = 0; o < r.length - 1; ++o)r[o] = Math.floor(t / n[o]), t -= r[o] * n[o]; return r[r.length - 1] = t, r } var at = Object.freeze({ shuffle: p, clamp: d, nearestLargerEven: E, sum: v, randUniform: function (t, e) { var n = Math.random(); return e * n + (1 - n) * t }, distSquared: function (t, e) { for (var n = 0, r = 0; r < t.length; r++) { var o = Number(t[r]) - Number(e[r]); n += o * o } return n }, assert: P, assertShapesMatch: x, assertNonNull: m, flatten: b, sizeFromShape: L, isScalarShape: function (t) { return 0 === t.length }, arraysEqual: A, isInt: B, tanh: w, sizeToSquarishShape: C, createShuffledIndices: function (t) { for (var e = new Uint32Array(t), n = 0; n < t; ++n)e[n] = n; return p(e), e }, rightPad: I, repeatedTry: k, inferFromImplicitShape: S, parseAxisParam: D, squeezeShape: T, getTypedArrayFromDType: N, getArrayFromDType: F, checkConversionForErrors: M, isValidDtype: O, hasEncodingLoss: W, isTypedArray: z, bytesPerElement: U, bytesFromStringArray: V, isString: G, isBoolean: H, isNumber: q, inferDtype: j, isFunction: K, nearestDivisor: X, computeStrides: Y, toTypedArray: $, toNestedArray: J, makeOnesTypedArray: Q, makeZerosTypedArray: Z, now: tt, assertNonNegativeIntegerDimensions: et, fetch: function (t, e) { return _().platform.fetch(t, e) }, encodeString: nt, decodeString: rt, locToIndex: ot, indexToLoc: it }), st = (ut.prototype.profileKernel = function (o, i, t) { var e, a = this, s = this.backendTimer.time(function () { e = t() }); return e.forEach(function (r) { r.data().then(function (n) { !function (t, e, n) { if ("float32" === e) for (var r = 0; r < t.length; r++) { var o = t[r]; if (isNaN(o) || !isFinite(o)) return console.warn("Found " + o + " in the result of '" + n + "'") } }(n, r.dtype, o), s.then(function (t) { var e = ""; null != t.getExtraProfileInfo && (e = t.getExtraProfileInfo()), a.logger.logKernelProfile(o, r, n, t.kernelMs, i, e) }) }) }), e }, ut); function ut(t, e) { this.backendTimer = t, null == (this.logger = e) && (this.logger = new ct) } var ct = (lt.prototype.logKernelProfile = function (t, e, n, r, o, i) { var a = "number" == typeof r ? I(r + "ms", 9) : r.error, s = I(t, 25), u = e.rank, c = e.size, l = I(e.shape.toString(), 14), h = ""; for (var f in o) { var p = o[f].shape || e.shape, d = p.length; h += f + ": " + d + "D " + (0 < d ? p : "") + " " } console.log("%c" + s + "\t%c" + a + "\t%c" + u + "D " + l + "\t%c" + c + "\t%c" + h + "\t%c" + i, "font-weight:bold", "color:red", "color:blue", "color: orange", "color: green", "color: steelblue") }, lt); function lt() { } var ht = 7; function ft(t, e, n) { return I(Array.isArray(t) ? parseFloat(t[0].toFixed(ht)) + " + " + parseFloat(t[1].toFixed(ht)) + "j" : G(t) ? "'" + t + "'" : "bool" === n ? pt(t) : parseFloat(t.toFixed(ht)).toString(), e) } function pt(t) { return 0 === t ? "false" : "true" } function dt(t) { for (var e = [], n = 0; n < t.length; n += 2)e.push([t[n], t[n + 1]]); return e } var vt = (xt.prototype.set = function (t) { for (var e = this, n = [], r = 1; r < arguments.length; r++)n[r - 1] = arguments[r]; 0 === n.length && (n = [0]), P(n.length === this.rank, function () { return "The number of provided coordinates (" + n.length + ") must match the rank (" + e.rank + ")" }); var o = this.locToIndex(n); this.values[o] = t }, xt.prototype.get = function () { for (var t = [], e = 0; e < arguments.length; e++)t[e] = arguments[e]; 0 === t.length && (t = [0]); for (var n = 0, r = 0, o = t; r < o.length; r++) { var i = o[r]; if (i < 0 || i >= this.shape[n]) { var a = "Requested out of range element at " + t + ".   Buffer shape=" + this.shape; throw new Error(a) } n++ } for (var s = t[t.length - 1], u = 0; u < t.length - 1; ++u)s += this.strides[u] * t[u]; return this.values[s] }, xt.prototype.locToIndex = function (t) { if (0 === this.rank) return 0; if (1 === this.rank) return t[0]; for (var e = t[t.length - 1], n = 0; n < t.length - 1; ++n)e += this.strides[n] * t[n]; return e }, xt.prototype.indexToLoc = function (t) { if (0 === this.rank) return []; if (1 === this.rank) return [t]; for (var e = new Array(this.shape.length), n = 0; n < e.length - 1; ++n)e[n] = Math.floor(t / this.strides[n]), t -= e[n] * this.strides[n]; return e[e.length - 1] = t, e }, Object.defineProperty(xt.prototype, "rank", { get: function () { return this.shape.length }, enumerable: !0, configurable: !0 }), xt.prototype.toTensor = function () { return mt().makeTensor(this.values, this.shape, this.dtype) }, xt), mt = null, gt = null, yt = null; function xt(t, e, n) { var r = this; if (this.dtype = e, this.shape = t.slice(), this.size = L(t), null != n) { var o = n.length; P(o === this.size, function () { return "Length of values '" + o + "' does not match the size inferred by the shape '" + r.size + "'." }) } if ("complex64" === e) 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 || F(e, this.size), this.strides = Y(t) } var bt = (wt.prototype.flatten = function () { return this.throwIfDisposed(), this.as1D() }, wt.prototype.asScalar = function () { return this.throwIfDisposed(), P(1 === this.size, function () { return "The array must have only 1 element." }), this.reshape([]) }, wt.prototype.as1D = function () { return this.throwIfDisposed(), this.reshape([this.size]) }, wt.prototype.as2D = function (t, e) { return this.throwIfDisposed(), this.reshape([t, e]) }, wt.prototype.as3D = function (t, e, n) { return this.throwIfDisposed(), this.reshape([t, e, n]) }, wt.prototype.as4D = function (t, e, n, r) { return this.throwIfDisposed(), this.reshape([t, e, n, r]) }, wt.prototype.as5D = function (t, e, n, r, o) { return this.throwIfDisposed(), this.reshape([t, e, n, r, o]) }, wt.prototype.asType = function (t) { return this.throwIfDisposed(), gt.cast(this, t) }, Object.defineProperty(wt.prototype, "rank", { get: function () { return this.shape.length }, enumerable: !0, configurable: !0 }), wt.prototype.buffer = function () { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return [4, this.data()]; case 1: return e = t.sent(), [2, gt.buffer(this.shape, this.dtype, e)] } }) }) }, wt.prototype.bufferSync = function () { return gt.buffer(this.shape, this.dtype, this.dataSync()) }, wt.prototype.array = function () { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return [4, this.data()]; case 1: return e = t.sent(), [2, J(this.shape, e)] } }) }) }, wt.prototype.arraySync = function () { return J(this.shape, this.dataSync()) }, wt.prototype.data = function () { return y(this, void 0, void 0, function () { var e, n; return R(this, function (t) { switch (t.label) { case 0: return this.throwIfDisposed(), e = mt().read(this.dataId), "string" !== this.dtype ? [3, 2] : [4, e]; case 1: n = t.sent(); try { return [2, n.map(function (t) { return rt(t) })] } catch (t) { throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().") } t.label = 2; case 2: return [2, e] } }) }) }, wt.prototype.dataSync = function () { this.throwIfDisposed(); var t = mt().readSync(this.dataId); if ("string" === this.dtype) try { return t.map(function (t) { return rt(t) }) } catch (t) { throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().") } return t }, wt.prototype.bytes = function () { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return this.throwIfDisposed(), [4, mt().read(this.dataId)]; case 1: return e = t.sent(), "string" === this.dtype ? [2, e] : [2, new Uint8Array(e.buffer)] } }) }) }, wt.prototype.dispose = function () { this.isDisposed || (mt().disposeTensor(this), this.isDisposedInternal = !0) }, Object.defineProperty(wt.prototype, "isDisposed", { get: function () { return this.isDisposedInternal }, enumerable: !0, configurable: !0 }), wt.prototype.throwIfDisposed = function () { if (this.isDisposed) throw new Error("Tensor is disposed.") }, wt.prototype.toFloat = function () { return this.asType("float32") }, wt.prototype.toInt = function () { return this.asType("int32") }, wt.prototype.toBool = function () { return this.asType("bool") }, wt.prototype.print = function (t) { return void 0 === t && (t = !1), gt.print(this, t) }, wt.prototype.reshape = function (t) { return this.throwIfDisposed(), gt.reshape(this, t) }, wt.prototype.reshapeAs = function (t) { return this.throwIfDisposed(), this.reshape(t.shape) }, wt.prototype.expandDims = function (t) { return void 0 === t && (t = 0), gt.expandDims(this, t) }, wt.prototype.cumsum = function (t, e, n) { return void 0 === t && (t = 0), void 0 === e && (e = !1), void 0 === n && (n = !1), gt.cumsum(this, t, e, n) }, wt.prototype.squeeze = function (t) { return this.throwIfDisposed(), gt.squeeze(this, t) }, wt.prototype.clone = function () { return this.throwIfDisposed(), gt.clone(this) }, wt.prototype.oneHot = function (t, e, n) { return this.throwIfDisposed(), gt.oneHot(this, t, e, n) }, wt.prototype.toString = function (t) { return void 0 === t && (t = !1), function (t, e, n, r) { var o = Y(e), i = function (t, e, n, r) { var o = L(e), i = r[r.length - 1], a = new Array(i).fill(0), s = e.length, u = "complex64" === n ? dt(t) : t; if (1 < s) for (var c = 0; c < o / i; c++)for (var l = c * i, h = 0; h < i; h++)a[h] = Math.max(a[h], ft(u[l + h], 0, n).length); return a }(t, e, n, o), a = e.length, s = function t(e, n, r, o, i, a) { void 0 === a && (a = !0); var s = "complex64" === r ? 2 : 1, u = n[0], c = n.length; if (0 === c) return "complex64" === r ? [ft(dt(e)[0], 0, r)] : "bool" === r ? [pt(e[0])] : [e[0].toString()]; if (1 === c) { if (20 < u) { var l = 3 * s, h = Array.from(e.slice(0, l)), f = Array.from(e.slice((u - 3) * s, u * s)); return "complex64" === r && (h = dt(h), f = dt(f)), ["[" + h.map(function (t, e) { return ft(t, i[e], r) }).join(", ") + ", ..., " + f.map(function (t, e) { return ft(t, i[u - 3 + e], r) }).join(", ") + "]"] } return ["[" + ("complex64" === r ? dt(e) : Array.from(e)).map(function (t, e) { return ft(t, i[e], r) }).join(", ") + "]"] } var p = n.slice(1), d = o.slice(1), v = o[0] * s, m = []; if (20 < u) { for (var g = 0; g < 3; g++) { var y = (x = g * v) + v; m.push.apply(m, t(e.slice(x, y), p, r, d, i, !1)) } for (m.push("..."), g = u - 3; g < u; g++)y = (x = g * v) + v, m.push.apply(m, t(e.slice(x, y), p, r, d, i, g === u - 1)) } else for (g = 0; g < u; g++) { var x; y = (x = g * v) + v, m.push.apply(m, t(e.slice(x, y), p, r, d, i, g === u - 1)) } var b = 2 === c ? "," : ""; for (m[0] = "[" + m[0] + b, g = 1; g < m.length - 1; g++)m[g] = " " + m[g] + b; var w = ",\n"; for (g = 2; g < c; g++)w += "\n"; return m[m.length - 1] = " " + m[m.length - 1] + "]" + (a ? "" : w), m }(t, e, n, o, i), u = ["Tensor"]; return r && (u.push("  dtype: " + n), u.push("  rank: " + a), u.push("  shape: [" + e + "]"), u.push("  values:")), u.push(s.map(function (t) { return "    " + t }).join("\n")), u.join("\n") }(this.dataSync(), this.shape, this.dtype, t) }, wt.prototype.tile = function (t) { return this.throwIfDisposed(), gt.tile(this, t) }, wt.prototype.gather = function (t, e) { return void 0 === e && (e = 0), this.throwIfDisposed(), gt.gather(this, t, e) }, wt.prototype.matMul = function (t, e, n) { return void 0 === e && (e = !1), void 0 === n && (n = !1), this.throwIfDisposed(), gt.matMul(this, t, e, n) }, wt.prototype.dot = function (t) { return this.throwIfDisposed(), gt.dot(this, t) }, wt.prototype.norm = function (t, e, n) { return void 0 === t && (t = "euclidean"), void 0 === e && (e = null), void 0 === n && (n = !1), this.throwIfDisposed(), gt.norm(this, t, e, n) }, wt.prototype.slice = function (t, e) { return this.throwIfDisposed(), gt.slice(this, t, e) }, wt.prototype.reverse = function (t) { return this.throwIfDisposed(), gt.reverse(this, t) }, wt.prototype.concat = function (t, e) { return void 0 === e && (e = 0), this.throwIfDisposed(), t instanceof wt && (t = [t]), gt.concat([this].concat(t), e) }, wt.prototype.split = function (t, e) { return void 0 === e && (e = 0), this.throwIfDisposed(), gt.split(this, t, e) }, wt.prototype.stack = function (t, e) { return void 0 === e && (e = 0), gt.stack([this, t], e) }, wt.prototype.unstack = function (t) { return void 0 === t && (t = 0), gt.unstack(this, t) }, wt.prototype.pad = function (t, e) { return void 0 === e && (e = 0), gt.pad(this, t, e) }, wt.prototype.batchNormalization = function (t, e, n, r, o) { return void 0 === n && (n = .001), yt("tf.batchNormalization() is going away. Use tf.batchNorm() instead, and note the positional argument change of scale, offset, and varianceEpsilon"), this.batchNorm(t, e, o, r, n) }, wt.prototype.batchNorm = function (t, e, n, r, o) { return void 0 === o && (o = .001), this.throwIfDisposed(), gt.batchNorm(this, t, e, n, r, o) }, wt.prototype.all = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.all(this, t, e) }, wt.prototype.any = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.any(this, t, e) }, wt.prototype.logSumExp = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.logSumExp(this, t, e) }, wt.prototype.sum = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.sum(this, t, e) }, wt.prototype.prod = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.prod(this, t, e) }, wt.prototype.mean = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.mean(this, t, e) }, wt.prototype.min = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.min(this, t, e) }, wt.prototype.max = function (t, e) { return void 0 === t && (t = null), void 0 === e && (e = !1), this.throwIfDisposed(), gt.max(this, t, e) }, wt.prototype.argMin = function (t) { return void 0 === t && (t = null), this.throwIfDisposed(), gt.argMin(this, t) }, wt.prototype.argMax = function (t) { return void 0 === t && (t = null), this.throwIfDisposed(), gt.argMax(this, t) }, wt.prototype.cast = function (t) { return this.throwIfDisposed(), gt.cast(this, t) }, wt.prototype.add = function (t) { return this.throwIfDisposed(), gt.add(this, t) }, wt.prototype.addStrict = function (t) { return this.throwIfDisposed(), gt.addStrict(this, t) }, wt.prototype.atan2 = function (t) { return this.throwIfDisposed(), gt.atan2(this, t) }, wt.prototype.sub = function (t) { return this.throwIfDisposed(), gt.sub(this, t) }, wt.prototype.subStrict = function (t) { return this.throwIfDisposed(), gt.subStrict(this, t) }, wt.prototype.pow = function (t) { return this.throwIfDisposed(), gt.pow(this, t) }, wt.prototype.powStrict = function (t) { return this.throwIfDisposed(), gt.powStrict(this, t) }, wt.prototype.mul = function (t) { return this.throwIfDisposed(), gt.mul(this, t) }, wt.prototype.mulStrict = function (t) { return this.throwIfDisposed(), gt.mulStrict(this, t) }, wt.prototype.div = function (t) { return this.throwIfDisposed(), gt.div(this, t) }, wt.prototype.divNoNan = function (t) { return this.throwIfDisposed(), gt.divNoNan(this, t) }, wt.prototype.floorDiv = function (t) { return this.throwIfDisposed(), gt.floorDiv(this, t) }, wt.prototype.divStrict = function (t) { return this.throwIfDisposed(), gt.divStrict(this, t) }, wt.prototype.minimum = function (t) { return this.throwIfDisposed(), gt.minimum(this, t) }, wt.prototype.minimumStrict = function (t) { return this.throwIfDisposed(), gt.minimumStrict(this, t) }, wt.prototype.maximum = function (t) { return this.throwIfDisposed(), gt.maximum(this, t) }, wt.prototype.maximumStrict = function (t) { return this.throwIfDisposed(), gt.maximumStrict(this, t) }, wt.prototype.mod = function (t) { return this.throwIfDisposed(), gt.mod(this, t) }, wt.prototype.modStrict = function (t) { return this.throwIfDisposed(), gt.modStrict(this, t) }, wt.prototype.squaredDifferenceStrict = function (t) { return this.throwIfDisposed(), gt.squaredDifferenceStrict(this, t) }, wt.prototype.transpose = function (t) { return this.throwIfDisposed(), gt.transpose(this, t) }, wt.prototype.notEqual = function (t) { return this.throwIfDisposed(), gt.notEqual(this, t) }, wt.prototype.notEqualStrict = function (t) { return this.throwIfDisposed(), gt.notEqualStrict(this, t) }, wt.prototype.less = function (t) { return this.throwIfDisposed(), gt.less(this, t) }, wt.prototype.lessStrict = function (t) { return this.throwIfDisposed(), gt.lessStrict(this, t) }, wt.prototype.equal = function (t) { return this.throwIfDisposed(), gt.equal(this, t) }, wt.prototype.equalStrict = function (t) { return this.throwIfDisposed(), gt.equalStrict(this, t) }, wt.prototype.lessEqual = function (t) { return this.throwIfDisposed(), gt.lessEqual(this, t) }, wt.prototype.lessEqualStrict = function (t) { return this.throwIfDisposed(), gt.lessEqualStrict(this, t) }, wt.prototype.greater = function (t) { return this.throwIfDisposed(), gt.greater(this, t) }, wt.prototype.greaterStrict = function (t) { return this.throwIfDisposed(), gt.greaterStrict(this, t) }, wt.prototype.greaterEqual = function (t) { return this.throwIfDisposed(), gt.greaterEqual(this, t) }, wt.prototype.greaterEqualStrict = function (t) { return this.throwIfDisposed(), gt.greaterEqualStrict(this, t) }, wt.prototype.logicalAnd = function (t) { return this.throwIfDisposed(), gt.logicalAnd(this, t) }, wt.prototype.logicalOr = function (t) { return this.throwIfDisposed(), gt.logicalOr(this, t) }, wt.prototype.logicalNot = function () { return this.throwIfDisposed(), gt.logicalNot(this) }, wt.prototype.logicalXor = function (t) { return this.throwIfDisposed(), gt.logicalXor(this, t) }, wt.prototype.where = function (t, e) { return this.throwIfDisposed(), gt.where(t, this, e) }, wt.prototype.neg = function () { return this.throwIfDisposed(), gt.neg(this) }, wt.prototype.ceil = function () { return this.throwIfDisposed(), gt.ceil(this) }, wt.prototype.floor = function () { return this.throwIfDisposed(), gt.floor(this) }, wt.prototype.sign = function () { return this.throwIfDisposed(), gt.sign(this) }, wt.prototype.isNaN = function () { return this.throwIfDisposed(), gt.isNaN(this) }, wt.prototype.isInf = function () { return this.throwIfDisposed(), gt.isInf(this) }, wt.prototype.isFinite = function () { return this.throwIfDisposed(), gt.isFinite(this) }, wt.prototype.exp = function () { return this.throwIfDisposed(), gt.exp(this) }, wt.prototype.expm1 = function () { return this.throwIfDisposed(), gt.expm1(this) }, wt.prototype.log = function () { return this.throwIfDisposed(), gt.log(this) }, wt.prototype.log1p = function () { return this.throwIfDisposed(), gt.log1p(this) }, wt.prototype.sqrt = function () { return this.throwIfDisposed(), gt.sqrt(this) }, wt.prototype.rsqrt = function () { return this.throwIfDisposed(), gt.rsqrt(this) }, wt.prototype.square = function () { return this.throwIfDisposed(), gt.square(this) }, wt.prototype.reciprocal = function () { return this.throwIfDisposed(), gt.reciprocal(this) }, wt.prototype.abs = function () { return this.throwIfDisposed(), gt.abs(this) }, wt.prototype.clipByValue = function (t, e) { return this.throwIfDisposed(), gt.clipByValue(this, t, e) }, wt.prototype.relu = function () { return this.throwIfDisposed(), gt.relu(this) }, wt.prototype.relu6 = function () { return this.throwIfDisposed(), gt.relu6(this) }, wt.prototype.elu = function () { return this.throwIfDisposed(), gt.elu(this) }, wt.prototype.selu = function () { return this.throwIfDisposed(), gt.selu(this) }, wt.prototype.leakyRelu = function (t) { return void 0 === t && (t = .2), this.throwIfDisposed(), gt.leakyRelu(this, t) }, wt.prototype.prelu = function (t) { return this.throwIfDisposed(), gt.prelu(this, t) }, wt.prototype.sigmoid = function () { return this.throwIfDisposed(), gt.sigmoid(this) }, wt.prototype.logSigmoid = function () { return this.throwIfDisposed(), gt.logSigmoid(this) }, wt.prototype.softplus = function () { return this.throwIfDisposed(), gt.softplus(this) }, wt.prototype.zerosLike = function () { return this.throwIfDisposed(), gt.zerosLike(this) }, wt.prototype.onesLike = function () { return this.throwIfDisposed(), gt.onesLike(this) }, wt.prototype.sin = function () { return this.throwIfDisposed(), gt.sin(this) }, wt.prototype.cos = function () { return this.throwIfDisposed(), gt.cos(this) }, wt.prototype.tan = function () { return this.throwIfDisposed(), gt.tan(this) }, wt.prototype.asin = function () { return this.throwIfDisposed(), gt.asin(this) }, wt.prototype.acos = function () { return this.throwIfDisposed(), gt.acos(this) }, wt.prototype.atan = function () { return this.throwIfDisposed(), gt.atan(this) }, wt.prototype.sinh = function () { return this.throwIfDisposed(), gt.sinh(this) }, wt.prototype.cosh = function () { return this.throwIfDisposed(), gt.cosh(this) }, wt.prototype.tanh = function () { return this.throwIfDisposed(), gt.tanh(this) }, wt.prototype.asinh = function () { return this.throwIfDisposed(), gt.asinh(this) }, wt.prototype.acosh = function () { return this.throwIfDisposed(), gt.acosh(this) }, wt.prototype.atanh = function () { return this.throwIfDisposed(), gt.atanh(this) }, wt.prototype.erf = function () { return this.throwIfDisposed(), gt.erf(this) }, wt.prototype.round = function () { return this.throwIfDisposed(), gt.round(this) }, wt.prototype.step = function (t) { return void 0 === t && (t = 0), this.throwIfDisposed(), gt.step(this, t) }, wt.prototype.softmax = function (t) { return void 0 === t && (t = -1), this.throwIfDisposed(), gt.softmax(this, t) }, wt.prototype.logSoftmax = function (t) { return void 0 === t && (t = -1), this.throwIfDisposed(), gt.logSoftmax(this, t) }, wt.prototype.resizeBilinear = function (t, e) { return void 0 === e && (e = !1), this.throwIfDisposed(), gt.image.resizeBilinear(this, t, e) }, wt.prototype.resizeNearestNeighbor = function (t, e) { return void 0 === e && (e = !1), this.throwIfDisposed(), gt.image.resizeNearestNeighbor(this, t, e) }, wt.prototype.conv1d = function (t, e, n, r, o, i) { return void 0 === r && (r = "NWC"), void 0 === o && (o = 1), this.throwIfDisposed(), gt.conv1d(this, t, e, n, r, o, i) }, wt.prototype.conv2d = function (t, e, n, r, o, i) { return void 0 === r && (r = "NHWC"), void 0 === o && (o = [1, 1]), this.throwIfDisposed(), gt.conv2d(this, t, e, n, r, o, i) }, wt.prototype.conv2dTranspose = function (t, e, n, r, o) { return this.throwIfDisposed(), gt.conv2dTranspose(this, t, e, n, r, o) }, wt.prototype.depthwiseConv2D = function (t, e, n, r, o, i) { return void 0 === r && (r = "NHWC"), void 0 === o && (o = [1, 1]), this.throwIfDisposed(), gt.depthwiseConv2d(this, t, e, n, r, o, i) }, wt.prototype.separableConv2d = function (t, e, n, r, o, i) { return void 0 === o && (o = [1, 1]), void 0 === i && (i = "NHWC"), this.throwIfDisposed(), gt.separableConv2d(this, t, e, n, r, o, i) }, wt.prototype.avgPool = function (t, e, n, r) { return this.throwIfDisposed(), gt.avgPool(this, t, e, n, r) }, wt.prototype.maxPool = function (t, e, n, r) { return this.throwIfDisposed(), gt.maxPool(this, t, e, n, r) }, wt.prototype.localResponseNormalization = function (t, e, n, r) { return void 0 === t && (t = 5), void 0 === e && (e = 1), void 0 === n && (n = 1), void 0 === r && (r = .5), gt.localResponseNormalization(this, t, e, n, r) }, wt.prototype.pool = function (t, e, n, r, o) { return this.throwIfDisposed(), gt.pool(this, t, e, n, r, o) }, wt.prototype.variable = function (t, e, n) { return void 0 === t && (t = !0), this.throwIfDisposed(), mt().makeVariable(this, t, e, n) }, wt.prototype.unsortedSegmentSum = function (t, e) { return this.throwIfDisposed(), gt.unsortedSegmentSum(this, t, e) }, wt.prototype.batchToSpaceND = function (t, e) { return this.throwIfDisposed(), gt.batchToSpaceND(this, t, e) }, wt.prototype.spaceToBatchND = function (t, e) { return this.throwIfDisposed(), gt.spaceToBatchND(this, t, e) }, wt.prototype.topk = function (t, e) { return void 0 === t && (t = 1), void 0 === e && (e = !0), this.throwIfDisposed(), gt.topk(this, t, e) }, wt.prototype.stridedSlice = function (t, e, n, r, o, i, a, s) { return void 0 === r && (r = 0), void 0 === o && (o = 0), void 0 === i && (i = 0), void 0 === a && (a = 0), void 0 === s && (s = 0), this.throwIfDisposed(), gt.stridedSlice(this, t, e, n, r, o, i, a, s) }, wt.prototype.depthToSpace = function (t, e) { return this.throwIfDisposed(), gt.depthToSpace(this, t, e) }, wt.prototype.fft = function () { return this.throwIfDisposed(), gt.spectral.fft(this) }, wt.prototype.ifft = function () { return this.throwIfDisposed(), gt.spectral.ifft(this) }, wt.prototype.rfft = function () { return this.throwIfDisposed(), gt.spectral.rfft(this) }, wt.prototype.irfft = function () { return this.throwIfDisposed(), gt.spectral.irfft(this) }, wt); function wt(t, e, n, r) { this.kept = !1, this.isDisposedInternal = !1, this.shape = t.slice(), this.dtype = e || "float32", this.size = L(t), this.strides = Y(t), this.dataId = n, this.id = r, this.rankType = this.rank < 5 ? this.rank.toString() : "higher" } Object.defineProperty(bt, Symbol.hasInstance, { value: function (t) { return !!t && null != t.dataId && null != t.shape && null != t.dtype } }); var Ct, Et, _t, It, Rt, kt, St, Dt, At, Tt, Nt, Ft = (t(Mt, kt = bt), Mt.prototype.assign = function (t) { if (t.dtype !== this.dtype) throw new Error("dtype of the new value (" + t.dtype + ") and previous value (" + this.dtype + ") must match"); if (!A(t.shape, this.shape)) throw new Error("shape of the new value (" + t.shape + ") and previous value (" + this.shape + ") must match"); mt().disposeTensor(this), this.dataId = t.dataId, mt().incRef(this, null) }, Mt.prototype.dispose = function () { mt().disposeVariable(this), this.isDisposedInternal = !0 }, Mt); function Mt(t, e, n, r) { var o = kt.call(this, t.shape, t.dtype, t.dataId, r) || this; return o.trainable = e, o.name = n, o } Object.defineProperty(Ft, Symbol.hasInstance, { value: function (t) { return t instanceof bt && null != t.assign && t.assign instanceof Function } }), (Nt = Ct = Ct || {}).R0 = "R0", Nt.R1 = "R1", Nt.R2 = "R2", Nt.R3 = "R3", Nt.R4 = "R4", Nt.R5 = "R5", Nt.R6 = "R6", (Tt = Et = Et || {}).float32 = "float32", Tt.int32 = "int32", Tt.bool = "int32", Tt.complex64 = "complex64", (At = _t = _t || {}).float32 = "float32", At.int32 = "int32", At.bool = "bool", At.complex64 = "complex64", (Dt = It = It || {}).float32 = "float32", Dt.int32 = "float32", Dt.bool = "float32", Dt.complex64 = "complex64", (St = Rt = Rt || {}).float32 = "complex64", St.int32 = "complex64", St.bool = "complex64", St.complex64 = "complex64"; var Ot = { float32: It, int32: Et, bool: _t, complex64: Rt }; function Pt(t, e) { if ("string" !== t && "string" !== e) return Ot[t][e]; if ("string" === t && "string" === e) return "string"; throw new Error("Can not upcast " + t + " with " + e) } function Bt(t) { return Pt(t, "int32") } function Lt(t, e) { if (t.dtype === e.dtype) return [t, e]; var n = Pt(t.dtype, e.dtype); return [t.cast(n), e.cast(n)] } function Wt(t, e) { P(t.dtype === e.dtype, function () { return "The dtypes of the first(" + t.dtype + ") and second(" + e.dtype + ") input must match" }) } function zt(t) { var e = []; return function t(e, n, r) { if (null != e) if (e instanceof bt) n.push(e); else if (o = e, Array.isArray(o) || "object" == typeof o) { var o, i = e; for (var a in i) { var s = i[a]; r.has(s) || (r.add(s), t(s, n, r)) } } }(t, e, new Set), e } var Ut, Vt = Object.freeze({ makeTypesMatch: Lt, assertTypesMatch: Wt, isTensorInList: function (e, t) { return t.some(function (t) { return t.id === e.id }) }, getTensorsInContainer: zt }), Gt = (jt.prototype.dispose = function () { for (var t in this.registeredVariables) this.registeredVariables[t].dispose() }, jt), Ht = (qt.prototype.ready = function () { return y(this, void 0, void 0, function () { var e, n, r; return R(this, function (t) { switch (t.label) { case 0: if (null != this.pendingBackendInit) return [2, this.pendingBackendInit.then(function () { })]; if (null != this.backendInstance) return [2]; e = this.getSortedBackends(), n = 0, t.label = 1; case 1: return n < e.length ? (r = e[n], [4, this.initializeBackend(r).success]) : [3, 5]; case 2: return t.sent() ? [4, this.setBackend(r)] : [3, 4]; case 3: return t.sent(), [2]; case 4: return n++, [3, 1]; case 5: throw new Error("Could not initialize any backends, all backend initializations failed.") } }) }) }, Object.defineProperty(qt.prototype, "backend", { get: function () { if (null != this.pendingBackendInit) throw new Error("Backend '" + this.backendName + "' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods"); if (null == this.backendInstance) { var t = this.initializeBackendsAndReturnBest(), e = t.name; if (t.asyncInit) throw new Error("The highest priority backend '" + e + "' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods"); this.setBackend(e) } return this.backendInstance }, enumerable: !0, configurable: !0 }), qt.prototype.backendNames = function () { return Object.keys(this.registryFactory) }, qt.prototype.findBackend = function (t) { if (!(t in this.registry)) { if (!(t in this.registryFactory)) return null; if (this.initializeBackend(t).asyncInit) return null } return this.registry[t] }, qt.prototype.findBackendFactory = function (t) { return t in this.registryFactory ? this.registryFactory[t].factory : null }, qt.prototype.registerBackend = function (t, e, n) { return void 0 === n && (n = 1), t in this.registryFactory ? (console.warn(t + " backend was already registered. Reusing existing backend factory."), !1) : (this.registryFactory[t] = { factory: e, priority: n }, !0) }, qt.prototype.setBackend = function (o) { return y(this, void 0, void 0, function () { var e, n, r; return R(this, function (t) { switch (t.label) { case 0: if (null == this.registryFactory[o]) throw new Error("Backend name '" + o + "' not found in registry"); return this.backendName = o, null != this.registry[o] ? [3, 4] : (this.backendInstance = null, e = this.initializeBackend(o), n = e.success, e.asyncInit ? [4, n] : [3, 2]); case 1: return r = t.sent(), [3, 3]; case 2: r = n, t.label = 3; case 3: if (!r) return [2, !1]; t.label = 4; case 4: return this.backendInstance = this.registry[o], this.setupRegisteredKernels(), this.profiler = new st(this.backendInstance), [2, !0] } }) }) }, qt.prototype.setupRegisteredKernels = function () { var e = this; a(this.backendName).forEach(function (t) { null != t.setupFunc && t.setupFunc(e.backendInstance) }) }, qt.prototype.disposeRegisteredKernels = function (e) { var n = this; a(e).forEach(function (t) { null != t.disposeFunc && t.disposeFunc(n.registry[e]) }) }, qt.prototype.initializeBackend = function (e) { var n = this, t = this.registryFactory[e]; if (null == t) throw new Error("Cannot initialize backend " + e + ", no registration found."); try { var r = t.factory(); if (Promise.resolve(r) !== r) return this.registry[e] = r, { success: !0, asyncInit: !1 }; var o = ++this.pendingBackendInitId, i = r.then(function (t) { return !(o < n.pendingBackendInitId || (n.registry[e] = t, n.pendingBackendInit = null)) }).catch(function (t) { return !(o < n.pendingBackendInitId || (n.pendingBackendInit = null, console.warn("Initialization of backend " + e + " failed"), console.warn(t.stack || t.message), 1)) }); return { success: this.pendingBackendInit = i, asyncInit: !0 } } catch (n) { return console.warn("Initialization of backend " + e + " failed"), console.warn(n.stack || n.message), { success: !1, asyncInit: !1 } } }, qt.prototype.removeBackend = function (t) { if (!(t in this.registryFactory)) throw new Error(t + " backend not found in registry"); this.backendName === t && null != this.pendingBackendInit && this.pendingBackendInitId++, t in this.registry && (this.disposeRegisteredKernels(t), this.registry[t].dispose(), delete this.registry[t]), delete this.registryFactory[t], this.backendName === t && (this.pendingBackendInit = null, this.backendName = null, this.backendInstance = null) }, qt.prototype.getSortedBackends = function () { var n = this; if (0 === Object.keys(this.registryFactory).length) throw new Error("No backend found in registry."); return Object.keys(this.registryFactory).sort(function (t, e) { return n.registryFactory[e].priority - n.registryFactory[t].priority }) }, qt.prototype.initializeBackendsAndReturnBest = function () { for (var t = this.getSortedBackends(), e = 0; e < t.length; e++) { var n = t[e], r = this.initializeBackend(n), o = r.success, i = r.asyncInit; if (i || o) return { name: n, asyncInit: i } } throw new Error("Could not initialize any backends, all backend initializations failed.") }, qt.prototype.moveData = function (t, e) { var n = this.state.tensorInfo.get(e), r = n.backend, o = this.readSync(e); r.disposeData(e), (n.backend = t).move(e, o, n.shape, n.dtype), this.shouldCheckForMemLeaks() && this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1]++ }, qt.prototype.tidy = function (t, e) { var n, r = this, o = null; if (null == e) { if ("function" != typeof t) throw new Error("Please provide a function to tidy()"); e = t } else { if ("string" != typeof t && !(t instanceof String)) throw new Error("When calling with two arguments, the first argument to tidy() must be a string"); if ("function" != typeof e) throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function"); o = t } return this.scopedRun(function () { return r.startScope(o) }, function () { return r.endScope(n) }, function () { return (n = e()) instanceof Promise && console.error("Cannot return a Promise inside of tidy."), n }) }, qt.prototype.scopedRun = function (t, e, n) { t(); try { var r = n(); return e(), r } catch (t) { throw e(), t } }, qt.prototype.nextTensorId = function () { return qt.nextTensorId++ }, qt.prototype.nextVariableId = function () { return qt.nextVariableId++ }, qt.prototype.clone = function (t) { var e = this.makeTensorFromDataId(t.dataId, t.shape, t.dtype), n = { x: t }; return this.addTapeNode(this.state.activeScope.name, n, [e], function (t) { return { x: function () { return t.toFloat() } } }, []), e }, qt.prototype.runKernel = function (t, e, n, r, o) { return this.runKernelFunc(null, e, null, t, n, r, o) }, qt.prototype.shouldCheckForMemLeaks = function () { return this.ENV.getBool("IS_TEST") }, qt.prototype.checkKernelForMemLeak = function (t, e, n) { var r = this.backend.numDataIds(), o = 0; n.forEach(function (t) { o += "complex64" === t.dtype ? 3 : 1 }); var i = this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1], a = r - e - o - i; if (0 < a) throw new Error("Backend '" + this.backendName + "' has an internal memory leak (" + a + " data ids) after running '" + t + "'") }, qt.prototype.runKernelFunc = function (n, o, t, i, a, s, u) { var e, c = this; void 0 === s && (s = []), void 0 === u && (u = []); var r = [], l = this.isTapeOn(); function h(t) { l && (r = t.map(function (t) { return c.keep(c.clone(t)) })) } null == i && (i = null != this.state.activeScope ? this.state.activeScope.name : ""); var f, p = this.state.numBytes, d = this.state.numTensors; this.shouldCheckForMemLeaks() && this.state.numDataMovesStack.push(0); var v, m = g(i, this.backendName); return f = null != m ? function () { var t = c.backend.numDataIds(); v = m.kernelFunc({ inputs: o, attrs: a, backend: c.backend }); var e = Array.isArray(v) ? v : [v]; c.shouldCheckForMemLeaks() && c.checkKernelForMemLeak(i, t, e); var n = e.map(function (t) { var e = t.dataId, n = t.shape, r = t.dtype; return c.makeTensorFromDataId(e, n, r) }), r = n.filter(function (t, e) { return u[e] }); return h((s || []).slice().concat(r)), n } : function () { var t = c.backend.numDataIds(); v = c.tidy(function () { return n(c.backend, h) }); var e = Array.isArray(v) ? v : [v]; return c.shouldCheckForMemLeaks() && c.checkKernelForMemLeak(i, t, e), e }, this.scopedRun(function () { return c.state.kernelDepth++ }, function () { return c.state.kernelDepth-- }, function () { e = c.ENV.getBool("DEBUG") ? c.profiler.profileKernel(i, o, function () { return f() }) : f() }), l && this.addTapeNode(i, o, e, t, r), this.state.profiling && this.state.activeProfile.kernels.push({ name: i, bytesAdded: this.state.numBytes - p, totalBytesSnapshot: this.state.numBytes, tensorsAdded: this.state.numTensors - d, totalTensorsSnapshot: this.state.numTensors, inputShapes: Object.keys(o).map(function (t) { return o[t].shape }), outputShapes: e.map(function (t) { return t.shape }) }), Array.isArray(v) ? e : e[0] }, qt.prototype.makeTensor = function (t, e, n, r) { if (null == t) throw new Error("Values passed to engine.makeTensor() are null"); n = n || "float32", r = r || this.backend; var o = t; "string" === n && G(t[0]) && (o = t.map(function (t) { return nt(t) })); var i = r.write(o, e, n), a = new bt(e, n, i, this.nextTensorId()); if (this.incRef(a, r), "string" === n) { var s = this.state.tensorInfo.get(i), u = V(o); this.state.numBytes += u - s.bytes, s.bytes = u } return a }, qt.prototype.makeTensorFromDataId = function (t, e, n, r) { var o = new bt(e, n = n || "float32", t, this.nextTensorId()); return this.incRef(o, r), o }, qt.prototype.makeVariable = function (t, e, n, r) { void 0 === e && (e = !0), n = n || this.nextVariableId().toString(), null != r && r !== t.dtype && (t = t.asType(r)); var o = new Ft(t, e, n, this.nextTensorId()); if (null != this.state.registeredVariables[o.name]) throw new Error("Variable with name " + o.name + " was already registered"); return this.state.registeredVariables[o.name] = o, this.incRef(o, this.backend), o }, qt.prototype.incRef = function (t, e) { var n = this.state.tensorInfo.has(t.dataId) ? this.state.tensorInfo.get(t.dataId).refCount : 0; if (this.state.numTensors++, "string" === t.dtype && this.state.numStringTensors++, 0 === n) { this.state.numDataBuffers++; var r = 0; "complex64" !== t.dtype && "string" !== t.dtype && (r = t.size * U(t.dtype)), this.state.tensorInfo.set(t.dataId, { backend: e || this.backend, dtype: t.dtype, shape: t.shape, bytes: r, refCount: 0 }), this.state.numBytes += r } this.state.tensorInfo.get(t.dataId).refCount++, t instanceof Ft || this.track(t) }, qt.prototype.disposeTensor = function (t) { if (this.state.tensorInfo.has(t.dataId)) { this.state.numTensors--, "string" === t.dtype && this.state.numStringTensors--; var e = this.state.tensorInfo.get(t.dataId); e.refCount <= 1 ? ("complex64" !== t.dtype && (this.state.numBytes -= e.bytes), this.state.numDataBuffers--, e.backend.disposeData(t.dataId), this.state.tensorInfo.delete(t.dataId)) : this.state.tensorInfo.get(t.dataId).refCount-- } }, qt.prototype.disposeVariables = function () { for (var t in this.state.registeredVariables) { var e = this.state.registeredVariables[t]; this.disposeVariable(e) } }, qt.prototype.disposeVariable = function (t) { this.disposeTensor(t), null != this.state.registeredVariables[t.name] && delete this.state.registeredVariables[t.name] }, qt.prototype.memory = function () { var t = this.backend.memory(); return t.numTensors = this.state.numTensors, t.numDataBuffers = this.state.numDataBuffers, t.numBytes = this.state.numBytes, 0 < this.state.numStringTensors && (t.unreliable = !0, null == t.reasons && (t.reasons = []), t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")), t }, qt.prototype.profile = function (r) { return y(this, void 0, void 0, function () { var e, n; return R(this, function (t) { return this.state.profiling = !0, e = this.state.numBytes, n = this.state.numTensors, this.state.activeProfile.kernels = [], this.state.activeProfile.result = r(), this.state.profiling = !1, this.state.activeProfile.peakBytes = Math.max.apply(Math, this.state.activeProfile.kernels.map(function (t) { return t.totalBytesSnapshot })), this.state.activeProfile.newBytes = this.state.numBytes - e, this.state.activeProfile.newTensors = this.state.numTensors - n, [2, this.state.activeProfile] }) }) }, qt.prototype.isTapeOn = function () { return 0 < this.state.gradientDepth && 0 === this.state.kernelDepth }, qt.prototype.addTapeNode = function (t, e, o, n, r) { var i = this, a = { id: this.state.nextTapeNodeId++, kernelName: t, inputs: e, outputs: o, saved: r }, s = l(t); null != s && (n = s.gradFunc), null != n && (a.gradient = function (t) { return t = t.map(function (t, e) { if (null != t) return t; var n = o[e], r = Z(n.size, n.dtype); return i.makeTensor(r, n.shape, n.dtype) }), n(1 < t.length ? t : t[0], r) }), this.state.activeTape.push(a) }, qt.prototype.keep = function (t) { return t.kept = !0, t }, qt.prototype.startTape = function () { 0 === this.state.gradientDepth && (this.state.activeTape = []), this.state.gradientDepth++ }, qt.prototype.endTape = function () { this.state.gradientDepth-- }, qt.prototype.startScope = function (t) { var e = { track: [], name: "unnamed scope", id: this.state.nextScopeId++ }; t && (e.name = t), this.state.scopeStack.push(e), this.state.activeScope = e }, qt.prototype.endScope = function (t) { for (var e = this, n = zt(t), r = new Set(n.map(function (t) { return t.id })), o = 0; o < this.state.activeScope.track.length; o++) { var i = this.state.activeScope.track[o]; i.kept || r.has(i.id) || i.dispose() } var a = this.state.scopeStack.pop(); this.state.activeScope = 0 === this.state.scopeStack.length ? null : this.state.scopeStack[this.state.scopeStack.length - 1], n.forEach(function (t) { t.kept || t.scopeId !== a.id || e.track(t) }) }, qt.prototype.gradients = function (t, o, i, e) { var u = this; if (void 0 === e && (e = !1), P(0 < o.length, function () { return "gradients() received an empty list of xs." }), null != i && "float32" !== i.dtype) throw new Error("dy must have 'float32' dtype, but has '" + i.dtype + "'"); var a = this.scopedRun(function () { return u.startTape() }, function () { return u.endTape() }, function () { return u.tidy("forward", t) }); P(a instanceof bt, function () { return "The result y returned by f() must be a tensor." }); var s = function (t, e, n) { for (var r = {}, o = {}, i = 0; i < e.length; i++)r[e[i].id] = !0; for (i = 0; i < t.length; i++) { var a = (d = t[i]).inputs; for (var s in a) { for (var u = a[s], c = !1, l = 0; l < e.length; l++)if (r[u.id]) { d.outputs.forEach(function (t) { return r[t.id] = !0 }), c = !0, o[d.id] = !0; break } if (c) break } } var h = {}; h[n.id] = !0; var f = {}; for (i = t.length - 1; 0 <= i; i--)for (a = (d = t[i]).inputs, l = 0; l < d.outputs.length; l++)if (h[d.outputs[l].id]) { for (var s in a) h[a[s].id] = !0, f[d.id] = !0; break } var p = []; for (i = 0; i < t.length; i++) { var d; if (o[(d = t[i]).id] && f[d.id]) { var v = {}; for (var s in d.inputs) { var m = d.inputs[s]; r[m.id] && (v[s] = m) } var g = Object.assign({}, d); g.inputs = v, g.outputs = d.outputs, p.push(g) } } return p }(this.state.activeTape, o, a); if (!e && 0 === s.length && 0 < o.length) 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", function () { var t, e, n = {}; n[a.id] = null == i ? (e = Q(L(t = a.shape), "float32"), Kt.makeTensor(e, t, "float32")) : i, function (a, s) { for (var t = function (t) { var o = s[t], n = []; if (o.outputs.forEach(function (t) { var e = a[t.id]; null != e ? n.push(e) : n.push(null) }), null == o.gradient) throw new Error("Cannot compute gradient: gradient function not found for " + o.kernelName + "."); function e(t) { if (!(t in i)) throw new Error("Cannot backprop through input " + t + ". Available gradients found: " + Object.keys(i) + "."); var e = function (t) { return u.tidy(t) }(function () { return i[t]() }); if ("float32" !== e.dtype) throw new Error("Error in gradient for op " + o.kernelName + ". The gradient of input " + t + " must have 'float32' dtype, but has '" + e.dtype + "'"); var n = o.inputs[t]; if (!A(e.shape, n.shape)) throw new Error("Error in gradient for op " + o.kernelName + ". The gradient of input '" + t + "' has shape '" + e.shape + "', which does not match the shape of the input '" + n.shape + "'"); if (null == a[n.id]) a[n.id] = e; else { var r = a[n.id]; a[n.id] = r.add(e), r.dispose() } } var i = o.gradient(n); for (var r in o.inputs) e(r) }, e = s.length - 1; 0 <= e; e--)t(e) }(n, s); var r = o.map(function (t) { return n[t.id] }); return 0 === u.state.gradientDepth && (u.state.activeTape.forEach(function (t) { for (var e = 0, n = t.saved; e < n.length; e++)n[e].dispose() }), u.state.activeTape = null), { value: a, grads: r } }) }, qt.prototype.customGrad = function (r) { var e = this; return P(K(r), function () { return "The f passed in customGrad(f) must be a function." }), function () { for (var i, a = [], t = 0; t < arguments.length; t++)a[t] = arguments[t]; P(a.every(function (t) { return t instanceof bt }), function () { return "The args passed in customGrad(f)(x1, x2,...) must all be tensors" }); var n = {}; return a.forEach(function (t, e) { n[e] = t }), e.runKernelFunc(function (t, e) { return P((i = r.apply(void 0, a.concat([e]))).value instanceof bt, function () { return "The function f passed in customGrad(f) must return an object where `obj.value` is a tensor" }), P(K(i.gradFunc), function () { return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function." }), i.value }, n, function (t, e) { var n = i.gradFunc(t, e), r = Array.isArray(n) ? n : [n]; P(r.length === a.length, function () { return "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(...)." }), P(r.every(function (t) { return t instanceof bt }), function () { return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors." }); var o = {}; return r.forEach(function (t, e) { o[e] = function () { return t } }), o }) } }, qt.prototype.readSync = function (t) { return this.state.tensorInfo.get(t).backend.readSync(t) }, qt.prototype.read = function (t) { return this.state.tensorInfo.get(t).backend.read(t) }, qt.prototype.time = function (r) { return y(this, void 0, void 0, function () { var e, n; return R(this, function (t) { switch (t.label) { case 0: return e = tt(), [4, this.backend.time(r)]; case 1: return (n = t.sent()).wallMs = tt() - e, [2, n] } }) }) }, qt.prototype.track = function (t) { return null != this.state.activeScope && (t.scopeId = this.state.activeScope.id, this.state.activeScope.track.push(t)), t }, Object.defineProperty(qt.prototype, "registeredVariables", { get: function () { return this.state.registeredVariables }, enumerable: !0, configurable: !0 }), qt.prototype.reset = function () { for (var t in this.pendingBackendInitId++, this.state.dispose(), this.ENV.reset(), this.state = new Gt, this.registry) this.disposeRegisteredKernels(t), this.registry[t].dispose(), delete this.registry[t]; this.backendName = null, this.backendInstance = null, this.pendingBackendInit = null }, qt.nextTensorId = 0, qt.nextVariableId = 0, qt); function qt(t) { this.ENV = t, this.registry = {}, this.registryFactory = {}, this.pendingBackendInitId = 0, this.state = new Gt } function jt() { 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 } } var Kt = function () { var t, e = function () { if (null == Ut) { var t = void 0; if ("undefined" != typeof window) t = window; else if ("undefined" != typeof global) t = global; else if ("undefined" != typeof process) t = process; else { if ("undefined" == typeof self) throw new Error("Could not find a global object"); t = self } Ut = t } return Ut }(); if (null == e._tfengine) { var n = new o(e); e._tfengine = new Ht(n) } return t = e._tfengine.ENV, i = t, mt = function () { return e._tfengine }, e._tfengine }(); function Xt() { return "undefined" != typeof window && null != window.document || "undefined" != typeof WorkerGlobalScope } var Yt = _(); Yt.registerFlag("DEBUG", function () { return !1 }, function (t) { t && 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.") }), Yt.registerFlag("IS_BROWSER", function () { return Xt() }), Yt.registerFlag("IS_NODE", function () { return "undefined" != typeof process && void 0 !== process.versions && void 0 !== process.versions.node }), Yt.registerFlag("IS_CHROME", function () { return "undefined" != typeof navigator && null != navigator && null != navigator.userAgent && /Chrome/.test(navigator.userAgent) && /Google Inc/.test(navigator.vendor) }), Yt.registerFlag("PROD", function () { return !1 }), Yt.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY", function () { return Yt.getBool("DEBUG") }), Yt.registerFlag("DEPRECATION_WARNINGS_ENABLED", function () { return !0 }), Yt.registerFlag("IS_TEST", function () { return !1 }); var $t, Jt, Qt, Zt, te, ee, ne = {}, re = { alpha: !1, antialias: !1, premultipliedAlpha: !1, preserveDrawingBuffer: !1, depth: !1, stencil: !1, failIfMajorPerformanceCaveat: !0 }; function oe(t, e) { ne[t] = e } function ie(t) { t in ne || (ne[t] = function (e) { if (1 !== e && 2 !== e) throw new Error("Cannot get WebGL rendering context, WebGL is disabled."); var t = function () { if ("undefined" != typeof OffscreenCanvas && 2 === e) return new OffscreenCanvas(300, 150); if ("undefined" != typeof document) return document.createElement("canvas"); throw new Error("Cannot create a canvas in this context") }(); return t.addEventListener("webglcontextlost", function (t) { t.preventDefault(), delete ne[e] }, !1), 1 === e ? t.getContext("webgl", re) || t.getContext("experimental-webgl", re) : t.getContext("webgl2", re) }(t)); var e = ne[t]; return e.isContextLost() ? (delete ne[t], ie(t)) : (e.disable(e.DEPTH_TEST), e.disable(e.STENCIL_TEST), e.disable(e.BLEND), e.disable(e.DITHER), e.disable(e.POLYGON_OFFSET_FILL), e.disable(e.SAMPLE_COVERAGE), e.enable(e.SCISSOR_TEST), e.enable(e.CULL_FACE), e.cullFace(e.BACK), ne[t]) } function ae(t, e) { return [e, t] } function se(t) { var e = L(t); return C(Math.ceil(e / 4)) } function ue(t, e) { return [Math.max(1, Math.ceil(e / 2)), Math.max(1, Math.ceil(t / 2))] } function ce(t, e) { var n, r, o, i, a, s, u, c, l, h = t; return l = 2 === _().getNumber("WEBGL_VERSION") ? (n = h.R32F, r = h.R16F, o = h.RGBA16F, i = h.RGBA32F, a = h.RED, s = 4, u = 1, c = h.HALF_FLOAT, h.FLOAT) : (n = t.RGBA, r = t.RGBA, o = t.RGBA, i = h.RGBA, a = t.RGBA, u = s = 4, c = null != e ? e.HALF_FLOAT_OES : null, t.FLOAT), { internalFormatFloat: n, internalFormatHalfFloat: r, internalFormatPackedHalfFloat: o, internalFormatPackedFloat: i, textureFormatFloat: a, downloadTextureFormat: t.RGBA, downloadUnpackNumChannels: s, defaultNumChannels: u, textureTypeHalfFloat: c, textureTypeFloat: l } } function le(t, e, n) { var r = n(); return e && function (t) { var e = t.getError(); if (e !== t.NO_ERROR) throw new Error("WebGL Error: " + fe(t, e)) }(t), r } (ee = $t = $t || {})[ee.DENSE = 0] = "DENSE", ee[ee.SHARED_BATCH = 1] = "SHARED_BATCH", (te = Jt = Jt || {})[te.RENDER = 0] = "RENDER", te[te.UPLOAD = 1] = "UPLOAD", te[te.PIXELS = 2] = "PIXELS", te[te.DOWNLOAD = 3] = "DOWNLOAD", (Zt = Qt = Qt || {})[Zt.UNPACKED_FLOAT16 = 0] = "UNPACKED_FLOAT16", Zt[Zt.UNPACKED_FLOAT32 = 1] = "UNPACKED_FLOAT32", Zt[Zt.PACKED_4X1_UNSIGNED_BYTE = 2] = "PACKED_4X1_UNSIGNED_BYTE", Zt[Zt.PACKED_2X2_FLOAT32 = 3] = "PACKED_2X2_FLOAT32", Zt[Zt.PACKED_2X2_FLOAT16 = 4] = "PACKED_2X2_FLOAT16"; function he(t) { return !!(_().getBool("WEBGL_RENDER_FLOAT32_ENABLED") || 0 === t || 5.96e-8 < Math.abs(t) && Math.abs(t) < 65504) } function fe(t, e) { switch (e) { case t.NO_ERROR: return "NO_ERROR"; case t.INVALID_ENUM: return "INVALID_ENUM"; case t.INVALID_VALUE: return "INVALID_VALUE"; case t.INVALID_OPERATION: return "INVALID_OPERATION"; case t.INVALID_FRAMEBUFFER_OPERATION: return "INVALID_FRAMEBUFFER_OPERATION"; case t.OUT_OF_MEMORY: return "OUT_OF_MEMORY"; case t.CONTEXT_LOST_WEBGL: return "CONTEXT_LOST_WEBGL"; default: return "Unknown error code " + e } } function pe(t, e, n) { return Pe(t, e, function () { return t.getExtension(n) }, 'Extension "' + n + '" not supported on this browser.') } function de(t, e, n) { var r = Pe(t, e, function () { return t.createShader(t.VERTEX_SHADER) }, "Unable to create vertex WebGLShader."); if (le(t, e, function () { return t.shaderSource(r, n) }), le(t, e, function () { return t.compileShader(r) }), !1 === t.getShaderParameter(r, t.COMPILE_STATUS)) throw console.log(t.getShaderInfoLog(r)), new Error("Failed to compile vertex shader."); return r } function ve(t, e, n) { var r = Pe(t, e, function () { return t.createShader(t.FRAGMENT_SHADER) }, "Unable to create fragment WebGLShader."); if (le(t, e, function () { return t.shaderSource(r, n) }), le(t, e, function () { return t.compileShader(r) }), !1 === t.getShaderParameter(r, t.COMPILE_STATUS)) throw function (t, e) { var n = ye.exec(e); if (null == n) return console.log("Couldn't parse line number in error: " + e), console.log(t); for (var r = +n[1], o = t.split("\n"), i = o.length.toString().length + 2, a = o.map(function (t, e) { return I((e + 1).toString(), i) + t }), s = 0, u = 0; u < a.length; u++)s = Math.max(a[u].length, s); var c = a.slice(0, r - 1), l = a.slice(r - 1, r), h = a.slice(r); console.log(c.join("\n")), console.log(e.split("\n")[0]), console.log("%c " + I(l[0], s), "border:1px solid red; background-color:#e3d2d2; color:#a61717"), console.log(h.join("\n")) }(n, t.getShaderInfoLog(r)), new Error("Failed to compile fragment shader."); return r } var me, ge, ye = /ERROR: [0-9]+:([0-9]+):/g; function xe(t, e) { return Pe(t, e, function () { return t.createProgram() }, "Unable to create WebGLProgram.") } function be(t, e, n) { if (le(t, e, function () { return t.linkProgram(n) }), !1 === t.getProgramParameter(n, t.LINK_STATUS)) throw console.log(t.getProgramInfoLog(n)), new Error("Failed to link vertex and fragment shaders.") } function we(t, e, n) { if (le(t, e, function () { return t.validateProgram(n) }), !1 === t.getProgramParameter(n, t.VALIDATE_STATUS)) throw console.log(t.getProgramInfoLog(n)), new Error("Shader program validation failed.") } function Ce(t, e, n) { var r = Pe(t, e, function () { return t.createBuffer() }, "Unable to create WebGLBuffer"); return le(t, e, function () { return t.bindBuffer(t.ARRAY_BUFFER, r) }), le(t, e, function () { return t.bufferData(t.ARRAY_BUFFER, n, t.STATIC_DRAW) }), r } function Ee(t, e, n) { var r = Pe(t, e, function () { return t.createBuffer() }, "Unable to create WebGLBuffer"); return le(t, e, function () { return t.bindBuffer(t.ELEMENT_ARRAY_BUFFER, r) }), le(t, e, function () { return t.bufferData(t.ELEMENT_ARRAY_BUFFER, n, t.STATIC_DRAW) }), r } function _e(t, e) { return Pe(t, e, function () { return t.createTexture() }, "Unable to create WebGLTexture.") } function Ie(t, e) { var n = _().getNumber("WEBGL_MAX_TEXTURE_SIZE"); if (t <= 0 || e <= 0) { var r = "[" + t + "x" + e + "]"; throw new Error("Requested texture size " + r + " is invalid.") } if (n < t || n < e) throw r = "[" + t + "x" + e + "]", new Error("Requested texture size " + r + " greater than WebGL maximum on this browser / GPU [" + n + "x" + n + "].") } function Re(t, e) { return Pe(t, e, function () { return t.createFramebuffer() }, "Unable to create WebGLFramebuffer.") } function ke(t, e, n, r, o, i, a, s) { var u = t.getAttribLocation(n, r); return -1 !== u && (le(t, e, function () { return t.bindBuffer(t.ARRAY_BUFFER, o) }), le(t, e, function () { return t.vertexAttribPointer(u, i, t.FLOAT, !1, a, s) }), le(t, e, function () { return t.enableVertexAttribArray(u) }), !0) } function Se(t, e, n, r) { Be(t, r), le(t, e, function () { return t.activeTexture(t.TEXTURE0 + r) }), le(t, e, function () { return t.bindTexture(t.TEXTURE_2D, n) }) } function De(t, e, n, r) { return Pe(t, e, function () { return t.getUniformLocation(n, r) }, 'uniform "' + r + '" not present in program.') } function Ae(t, e, n) { return t.getUniformLocation(e, n) } function Te(t, e, n, r, o, i) { le(t, e, function () { return Se(t, e, r, i) }), le(t, e, function () { return t.uniform1i(o, i) }) } function Ne(t, e, n, r) { le(t, e, function () { return t.bindFramebuffer(t.FRAMEBUFFER, r) }), le(t, e, function () { return t.framebufferTexture2D(t.FRAMEBUFFER, t.COLOR_ATTACHMENT0, t.TEXTURE_2D, n, 0) }) } function Fe(t, e, n) { le(t, e, function () { return t.bindFramebuffer(t.FRAMEBUFFER, n) }), le(t, e, function () { return t.framebufferTexture2D(t.FRAMEBUFFER, t.COLOR_ATTACHMENT0, t.TEXTURE_2D, null, 0) }) } function Me(t) { var e = t.checkFramebufferStatus(t.FRAMEBUFFER); if (e !== t.FRAMEBUFFER_COMPLETE) throw new Error("Error binding framebuffer: " + Oe(t, e)) } function Oe(t, e) { switch (e) { case t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT: return "FRAMEBUFFER_INCOMPLETE_ATTACHMENT"; case t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT: return "FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT"; case t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS: return "FRAMEBUFFER_INCOMPLETE_DIMENSIONS"; case t.FRAMEBUFFER_UNSUPPORTED: return "FRAMEBUFFER_UNSUPPORTED"; default: return "unknown error " + e } } function Pe(t, e, n, r) { var o = le(t, e, function () { return n() }); if (null == o) throw new Error(r); return o } function Be(t, e) { var n = t.MAX_COMBINED_TEXTURE_IMAGE_UNITS - 1, r = e + t.TEXTURE0; if (r < t.TEXTURE0 || n < r) throw new Error("textureUnit must be in [gl.TEXTURE0, gl.TEXTURE" + n + "].") } function Le(t, e) { return void 0 === e && (e = 2), L(t.slice(0, t.length - e)) } function We(t) { if (0 === t.length) throw Error("Cannot get rows and columns of an empty shape array."); return [1 < t.length ? t[t.length - 2] : 1, t[t.length - 1]] } function ze(t) { var e = [1, 1, 1]; return 0 === t.length || 1 === t.length && 1 === t[0] || (e = [Le(t)].concat(We(t))), e } function Ue(n, t) { var e; void 0 === t && (t = !1); var r = _().getNumber("WEBGL_MAX_TEXTURE_SIZE"); if (t && (r *= 2, 1 === (n = n.map(function (t, e) { return e >= n.length - 2 ? E(n[e]) : n[e] })).length && (n = [2, n[0]])), 2 !== n.length) { var o = T(n); n = o.newShape } var i = L(n); if (n.length <= 1 && i <= r) return [1, i]; if (2 === n.length && n[0] <= r && n[1] <= r) return n; if (3 === n.length && n[0] * n[1] <= r && n[2] <= r) return [n[0] * n[1], n[2]]; if (3 === n.length && n[0] <= r && n[1] * n[2] <= r) return [n[0], n[1] * n[2]]; if (4 === n.length && n[0] * n[1] * n[2] <= r && n[3] <= r) return [n[0] * n[1] * n[2], n[3]]; if (4 === n.length && n[0] <= r && n[1] * n[2] * n[3] <= r) return [n[0], n[1] * n[2] * n[3]]; if (t) { var a = Le(n), s = 2, u = 2; return n.length && (s = (e = We(n))[0], u = e[1]), C(i = a * (s / 2) * (u / 2)).map(function (t) { return 2 * t }) } return C(i) } function Ve(t) { return t % 2 == 0 } function Ge(t, e) { if (A(t = t.slice(-2), e = e.slice(-2))) return !0; if (!t.length || !e.length) return !0; if (0 === t[0] || 0 === t[1] || 0 === e[0] || 0 === e[1]) return !0; if (t.length !== e.length) { var n = t.slice(-1)[0], r = e.slice(-1)[0]; if (n === r) return !0; if (Ve(n) && Ve(r) && (1 === t[0] || 1 === e[0])) return !0 } return t[1] === e[1] && Ve(t[0]) && Ve(e[0]) } function He(t) { if (null == me) { var e = ie(t); me = e.getParameter(e.MAX_TEXTURE_SIZE) } return me } function qe(t) { if (null == ge) { var e = ie(t); ge = e.getParameter(e.MAX_TEXTURE_IMAGE_UNITS) } return Math.min(16, ge) } function je(t) { if (0 === t) return 0; var e = ie(t); return Ke(e, "EXT_disjoint_timer_query_webgl2") && 2 === t ? 2 : Ke(e, "EXT_disjoint_timer_query") ? 1 : 0 } function Ke(t, e) { return null != t.getExtension(e) } function Xe(t) { try { if (null != ie(t)) return !0 } catch (t) { return !1 } return !1 } function Ye(t) { if (0 === t) return !1; var e = ie(t); if (1 === t) { if (!Ke(e, "OES_texture_float")) return !1 } else if (!Ke(e, "EXT_color_buffer_float")) return !1; return Je(e) } function $e(t) { if (0 === t) return !1; var e = ie(t); if (1 === t) return !!Ke(e, "OES_texture_float") && !!Ke(e, "WEBGL_color_buffer_float") && Je(e); if (Ke(e, "EXT_color_buffer_float")) return Je(e); if (Ke(e, "EXT_color_buffer_half_float")) { var i = e.getExtension("EXT_color_buffer_half_float"); return function (t) { var e = ce(t, i), n = t.createTexture(); t.bindTexture(t.TEXTURE_2D, n), t.texImage2D(t.TEXTURE_2D, 0, e.internalFormatHalfFloat, 1, 1, 0, e.textureFormatFloat, e.textureTypeHalfFloat, null); var r = t.createFramebuffer(); t.bindFramebuffer(t.FRAMEBUFFER, r), t.framebufferTexture2D(t.FRAMEBUFFER, t.COLOR_ATTACHMENT0, t.TEXTURE_2D, n, 0); var o = t.checkFramebufferStatus(t.FRAMEBUFFER) === t.FRAMEBUFFER_COMPLETE; return t.bindTexture(t.TEXTURE_2D, null), t.bindFramebuffer(t.FRAMEBUFFER, null), t.deleteTexture(n), t.deleteFramebuffer(r), o }(e) } return !1 } function Je(t) { var e = ce(t), n = t.createTexture(); t.bindTexture(t.TEXTURE_2D, n), t.texImage2D(t.TEXTURE_2D, 0, e.internalFormatFloat, 1, 1, 0, e.textureFormatFloat, e.textureTypeFloat, null); var r = t.createFramebuffer(); t.bindFramebuffer(t.FRAMEBUFFER, r), t.framebufferTexture2D(t.FRAMEBUFFER, t.COLOR_ATTACHMENT0, t.TEXTURE_2D, n, 0); var o = t.checkFramebufferStatus(t.FRAMEBUFFER) === t.FRAMEBUFFER_COMPLETE; return t.bindTexture(t.TEXTURE_2D, null), t.bindFramebuffer(t.FRAMEBUFFER, null), t.deleteTexture(n), t.deleteFramebuffer(r), o } function Qe(t) { return 2 === t && null != ie(t).fenceSync } var Ze = Object.freeze({ callAndCheck: le, canBeRepresented: he, getWebGLErrorMessage: fe, getExtensionOrThrow: pe, createVertexShader: de, createFragmentShader: ve, createProgram: xe, linkProgram: be, validateProgram: we, createStaticVertexBuffer: Ce, createStaticIndexBuffer: Ee, getNumChannels: function () { return 2 === _().getNumber("WEBGL_VERSION") ? 1 : 4 }, createTexture: _e, validateTextureSize: Ie, createFramebuffer: Re, bindVertexBufferToProgramAttribute: ke, bindTextureUnit: Se, unbindTextureUnit: function (t, e, n) { Be(t, n), le(t, e, function () { return t.activeTexture(t.TEXTURE0 + n) }), le(t, e, function () { return t.bindTexture(t.TEXTURE_2D, null) }) }, getProgramUniformLocationOrThrow: De, getProgramUniformLocation: Ae, bindTextureToProgramUniformSampler: Te, bindCanvasToFramebuffer: function (t, e) { le(t, e, function () { return t.bindFramebuffer(t.FRAMEBUFFER, null) }), le(t, e, function () { return t.viewport(0, 0, t.canvas.width, t.canvas.height) }), le(t, e, function () { return t.scissor(0, 0, t.canvas.width, t.canvas.height) }) }, bindColorTextureToFramebuffer: Ne, unbindColorTextureFromFramebuffer: Fe, validateFramebuffer: Me, getFramebufferErrorMessage: Oe, getBatchDim: Le, getRowsCols: We, getShapeAs3D: ze, getTextureShapeFromLogicalShape: Ue, isReshapeFree: Ge, getWebGLMaxTextureSize: He, resetMaxTextureSize: function () { me = null }, resetMaxTexturesInShader: function () { ge = null }, getMaxTexturesInShader: qe, getWebGLDisjointQueryTimerVersion: je, hasExtension: Ke, isWebGLVersionEnabled: Xe, isCapableOfRenderingToFloatTexture: Ye, isDownloadFloatTextureEnabled: $e, isWebGLFenceEnabled: Qe }), tn = _(); function en(t) { _().getBool("DEPRECATION_WARNINGS_ENABLED") && console.warn(t + " You can disable deprecation warnings with tf.disableDeprecationWarnings().") } function nn(t, e) { return Kt.tidy(t, e) } function rn(t) { zt(t).forEach(function (t) { return t.dispose() }) } function on(t) { return Kt.keep(t) } function an() { for (var t = [], e = 0; e < arguments.length; e++)t[e] = arguments[e]; _().getBool("IS_TEST") || console.warn.apply(console, t) } function sn(t, e) { var n = t; if (z(t)) return "string" === e ? [] : [t.length]; if (!Array.isArray(t)) return []; for (var r = []; Array.isArray(n) || z(n) && "string" !== e;)r.push(n.length), n = n[0]; return Array.isArray(t) && _().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY") && function t(e, n, r) { if (r = r || [], Array.isArray(e) || z(e)) { P(0 < n.length, function () { return "Element arr[" + r.join("][") + "] should be a primitive, but is an array of " + e.length + " elements" }), P(e.length === n[0], function () { return "Element arr[" + r.join("][") + "] should have " + n[0] + " elements, but has " + e.length + " elements" }); for (var o = n.slice(1), i = 0; i < e.length; ++i)t(e[i], o, r.concat(i)) } else P(0 === n.length, function () { return "Element arr[" + r.join("][") + "] is a primitive, but should be an array/TypedArray of " + n[0] + " elements" }) }(t, r, []), r } function un(t, e, n, r) { if (null != t && ("numeric" !== t && t !== e || "numeric" === t && "string" === e)) throw new Error("Argument '" + n + "' passed to '" + r + "' must be " + t + " tensor, but got " + e + " tensor") } function cn(t, e, n, r) { if (void 0 === r && (r = "numeric"), t instanceof bt) return un(r, t.dtype, e, n), t; var o = j(t); if ("string" !== o && 0 <= ["bool", "int32", "float32"].indexOf(r) && (o = r), un(r, o, e, n), null == t || !z(t) && !Array.isArray(t) && "number" != typeof t && "boolean" != typeof t && "string" != typeof t) { var i = null == t ? "null" : t.constructor.name; throw new Error("Argument '" + e + "' passed to '" + n + "' must be a Tensor or TensorLike, but got '" + i + "'") } var a = sn(t, o); z(t) || Array.isArray(t) || (t = [t]); var s = "string" !== o ? $(t, o, _().getBool("DEBUG")) : b(t, [], !0); return Kt.makeTensor(s, a, o) } function ln(t, n, r, e) { if (void 0 === e && (e = "numeric"), !Array.isArray(t)) throw new Error("Argument " + n + " passed to " + r + " must be a `Tensor[]` or `TensorLike[]`"); return t.map(function (t, e) { return cn(t, n + "[" + e + "]", r) }, e) } function hn(t, e) { for (var n = 0; n < t.length; ++n)if (t[t.length - n - 1] !== e - 1 - n) return !1; return !0 } function fn(t, e, n) { for (var r = t.length + e.length, o = [], i = 0, a = 0, s = 0; s < r; s++)-1 === n.indexOf(s) ? o.push(t[i++]) : o.push(e[a++]); return o } function pn(e, t) { for (var n = [], r = e.length, o = 0; o < r; o++)-1 === t.indexOf(o) && n.push(e[o]); return [n, t.map(function (t) { return e[t] })] } function dn(t, e) { return fn(t, e.map(function (t) { return 1 }), e) } function vn(t, e, n) { P(hn(e, n), function () { return t + " supports only inner-most axes for now. Got axes " + e + " and rank-" + n + " input." }) } function mn(t, e) { if (hn(t, e)) return null; for (var n = [], r = 0; r < e; ++r)-1 === t.indexOf(r) && n.push(r); return t.forEach(function (t) { return n.push(t) }), n } function gn(t) { return t.map(function (t, e) { return [e, t] }).sort(function (t, e) { return t[1] - e[1] }).map(function (t) { return t[0] }) } function yn(t, e) { for (var n = [], r = e - t; r < e; ++r)n.push(r); return n } function xn(t, r) { var o = t[0].length; t.forEach(function (t, e) { P(t.length === o, function () { return "Error in concat" + o + "D: rank of tensors[" + e + "] must be the same as the rank of the rest (" + o + ")" }) }), P(0 <= r && r < o, function () { return "Error in concat" + o + "D: axis must be between 0 and " + (o - 1) + "." }); var i = t[0]; t.forEach(function (t, e) { for (var n = 0; n < o; n++)P(n === r || t[n] === i[n], function () { return "Error in concat" + o + "D: Shape of tensors[" + e + "] (" + t + ") does not match the shape of the rest (" + i + ") along the non-concatenated axis " + e + "." }) }) } function bn(t, e) { for (var n = t[0].slice(), r = 1; r < t.length; r++)n[e] += t[r][e]; return n } function wn(t) { var e = Object.keys(t); if (1 !== e.length) throw new Error("Please provide an object with a single key (operation name) mapping to a function. Got an object with " + e.length + " keys."); var r = e[0], o = t[r]; r.endsWith("_") && (r = r.substring(0, r.length - 1)); function n() { for (var t = [], e = 0; e < arguments.length; e++)t[e] = arguments[e]; Kt.startScope(r); try { var n = o.apply(void 0, t); return n instanceof Promise && console.error("Cannot return a Promise inside of tidy."), Kt.endScope(n), n } catch (t) { throw Kt.endScope(null), t } } return Object.defineProperty(n, "name", { value: r, configurable: !0 }), n } tn.registerFlag("HAS_WEBGL", function () { return 0 < tn.getNumber("WEBGL_VERSION") }), tn.registerFlag("WEBGL_VERSION", function () { return Xe(2) ? 2 : Xe(1) ? 1 : 0 }), tn.registerFlag("WEBGL_BUFFER_SUPPORTED", function () { return 2 === tn.get("WEBGL_VERSION") }), tn.registerFlag("WEBGL_CPU_FORWARD", function () { return !0 }), tn.registerFlag("WEBGL_FORCE_F16_TEXTURES", function () { return !1 }), tn.registerFlag("WEBGL_PACK", function () { return tn.getBool("HAS_WEBGL") }), tn.registerFlag("WEBGL_PACK_NORMALIZATION", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_PACK_CLIP", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_PACK_DEPTHWISECONV", function () { return !1 }), tn.registerFlag("WEBGL_PACK_BINARY_OPERATIONS", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_PACK_UNARY_OPERATIONS", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_PACK_REDUCE", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_LAZILY_UNPACK", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_CONV_IM2COL", function () { return tn.getBool("WEBGL_PACK") }), tn.registerFlag("WEBGL_MAX_TEXTURE_SIZE", function () { return He(tn.getNumber("WEBGL_VERSION")) }), tn.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER", function () { return qe(tn.getNumber("WEBGL_VERSION")) }), tn.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION", function () { var t = tn.getNumber("WEBGL_VERSION"); return 0 === t ? 0 : je(t) }), tn.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE", function () { return 0 < tn.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") && (t = navigator.userAgent || navigator.vendor || window.opera, !(/(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)))); var t }), tn.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE", function () { return Ye(tn.getNumber("WEBGL_VERSION")) }), tn.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED", function () { return !tn.getBool("WEBGL_FORCE_F16_TEXTURES") && tn.getBool("WEBGL_RENDER_FLOAT32_CAPABLE") }), tn.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED", function () { return $e(tn.getNumber("WEBGL_VERSION")) }), tn.registerFlag("WEBGL_FENCE_API_ENABLED", function () { return Qe(tn.getNumber("WEBGL_VERSION")) }), tn.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM", function () { return tn.getBool("WEBGL_RENDER_FLOAT32_ENABLED") ? 4 : 0 }), yt = en; var Cn = wn({ complex_: function (t, e) { var n = cn(t, "real", "complex"), r = cn(e, "imag", "complex"); return x(n.shape, r.shape, "real and imag shapes, " + n.shape + " and " + r.shape + ", must match in call to tf.complex()."), Kt.runKernelFunc(function (t) { return t.complex(n, r) }, { $real: n, $imag: r }) } }), En = wn({ real_: function (t) { var e = cn(t, "input", "real"); return Kt.runKernelFunc(function (t) { return t.real(e) }, { $input: e }) } }), _n = wn({ imag_: function (t) { var e = cn(t, "input", "imag"); return Kt.runKernelFunc(function (t) { return t.imag(e) }, { $input: e }) } }); function In(t, e, n) { return Rn(t, e, sn(t, n), n) } function Rn(t, e, n, r) { if (null == r && (r = j(t)), "complex64" === r) throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag)."); if (!z(t) && !Array.isArray(t) && "number" != typeof t && "boolean" != typeof t && "string" != typeof t) 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 != e) { et(e); var o = L(e), i = L(n); P(o === i, function () { return "Based on the provided shape, [" + e + "], the tensor should have " + o + " values but has " + i }); for (var a = 0; a < n.length; ++a) { var s = n[a], u = a !== n.length - 1 || s !== L(e.slice(a)); P(n[a] === e[a] || !u, function () { return "Error creating a new Tensor. Inferred shape (" + n + ") does not match the provided shape (" + e + "). " }) } } return z(t) || Array.isArray(t) || (t = [t]), e = e || n, t = "string" !== r ? $(t, r, _().getBool("DEBUG")) : b(t, [], !0), Kt.makeTensor(t, e, r) } function kn(t, e) { if ((z(t) && "string" !== e || Array.isArray(t)) && "complex64" !== e) throw new Error("Error creating a new Scalar: value must be a primitive (number|boolean|string)"); if ("string" === e && z(t) && !(t instanceof Uint8Array)) throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`."); return Rn(t, [], [], e) } function Sn(t, e) { m(t); var n = sn(t, e); if (1 !== n.length) throw new Error("tensor1d() requires values to be a flat/TypedArray"); return Rn(t, null, n, e) } function Dn(t, e, n) { if (m(t), null != e && 2 !== e.length) throw new Error("tensor2d() requires shape to have two numbers"); var r = sn(t, n); if (2 !== r.length && 1 !== r.length) throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray"); if (1 === r.length && null == e) throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray"); return Rn(t, e, r, n) } function An(t, e, n) { if (m(t), null != e && 3 !== e.length) throw new Error("tensor3d() requires shape to have three numbers"); var r = sn(t, n); if (3 !== r.length && 1 !== r.length) throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray"); if (1 === r.length && null == e) throw new Error("tensor3d() requires shape to be provided when `values` are a flat array"); return Rn(t, e, r, n) } function Tn(t, e, n) { if (m(t), null != e && 4 !== e.length) throw new Error("tensor4d() requires shape to have four numbers"); var r = sn(t, n); if (4 !== r.length && 1 !== r.length) throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray"); if (1 === r.length && null == e) throw new Error("tensor4d() requires shape to be provided when `values` are a flat array"); return Rn(t, e, r, n) } function Nn(t, e, n) { if (m(t), null != e && 5 !== e.length) throw new Error("tensor5d() requires shape to have five numbers"); var r = sn(t, n); if (5 !== r.length && 1 !== r.length) throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray"); if (1 === r.length && null == e) throw new Error("tensor5d() requires shape to be provided when `values` are a flat array"); return Rn(t, e, r, n) } function Fn(t, e, n) { if (m(t), null != e && 6 !== e.length) throw new Error("tensor6d() requires shape to have six numbers"); var r = sn(t, n); if (6 !== r.length && 1 !== r.length) throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray"); if (1 === r.length && null == e) throw new Error("tensor6d() requires shape to be provided when `values` are a flat array"); return Rn(t, e = e || r, r, n) } function Mn(t, e, n, r) { return void 0 === e && (e = !0), Kt.makeVariable(t, e, n, r) } function On(t, e) { if (void 0 === e && (e = "float32"), "complex64" === e) { var n = On(t, "float32"), r = Pn(t, "float32"); return Cn(n, r) } var o = Q(L(t), e); return Kt.makeTensor(o, t, e) } function Pn(t, e) { if (void 0 === e && (e = "float32"), "complex64" === e) { var n = Pn(t, "float32"), r = Pn(t, "float32"); return Cn(n, r) } var o = Z(L(t), e); return Kt.makeTensor(o, t, e) } function Bn(e, n, r) { return Kt.runKernelFunc(function (t) { return t.fill(e, n, r) }, {}) } function Ln(e, n, r) { if (r <= 0) throw new Error("The number of values should be positive."); return Kt.runKernelFunc(function (t) { return t.linspace(e, n, r) }, {}) } function Wn(t, e, n, r) { if (void 0 === n && (n = 1), void 0 === r && (r = "float32"), 0 === n) throw new Error("Cannot have a step of zero"); if (t === e || t < e && n < 0 || e < t && 1 < n) return Pn([0], r); var o = Z(Math.abs(Math.ceil((e - t) / n)), r); e < t && 1 === n && (n = -1), o[0] = t; for (var i = 1; i < o.length; i++)o[i] = o[i - 1] + n; return Sn(o, r) } var zn = wn({ onesLike_: function (t) { var e = cn(t, "x", "onesLike"); if ("complex64" !== e.dtype) return Kt.runKernelFunc(function (t) { return t.onesLike(e) }, { $x: e }, function (t, e) { return { $x: function () { return Un(t) } } }); var n = zn(En(e)), r = Un(_n(e)); return Cn(n, r) } }), Un = wn({ zerosLike_: function (t) { var e = cn(t, "x", "zerosLike"); return Kt.runKernelFunc(function (t) { return t.zerosLike(e) }, { $x: e }, function (t, e) { return { $x: function () { return Un(t) } } }) } }), Vn = wn({ concat_: function (t, n) { void 0 === n && (n = 0), P(1 <= t.length, function () { return "Pass at least one tensor to concat" }); var e = ln(t, "tensors", "concat"); "complex64" === e[0].dtype && e.forEach(function (t) { if ("complex64" !== t.dtype) throw new Error("Cannot concatenate complex64 tensors with a tensor\n          with dtype " + t.dtype + ". ") }), n = D(n, e[0].shape)[0]; var r = bn(e.map(function (t) { return t.shape }), n); if (0 === L(r)) return In([], r); if (1 === (e = e.filter(function (t) { return 0 < t.size })).length) return e[0]; var o = e.map(function (t) { return t.shape }); xn(o, n); var i = e, a = { axis: n }; return Kt.runKernelFunc(function (t) { return t.concat(e, n) }, i, function (t) { var e = o.map(function (t) { return t[n] }); return Kn(t, e, n).map(function (t) { return function () { return t } }) }, "Concat", a) } }), Gn = wn({ concat1d_: function (t) { return Vn(t, 0) } }), Hn = wn({ concat2d_: function (t, e) { return Vn(t, e) } }), qn = wn({ concat3d_: function (t, e) { return Vn(t, e) } }), jn = wn({ concat4d_: function (t, e) { return Vn(t, e) } }), Kn = wn({ split_: function (t, e, n) { void 0 === n && (n = 0); var r, o = cn(t, "x", "split"); return n = D(n, o.shape)[0], r = "number" == typeof e ? (P(o.shape[n] % e == 0, function () { return "Number of splits must evenly divide the axis." }), new Array(e).fill(o.shape[n] / e)) : (P(o.shape[n] === e.reduce(function (t, e) { return t + e }), function () { return "The sum of sizes must match the size of the axis dimension." }), e), Kt.runKernelFunc(function (t) { return t.split(o, r, n) }, { $x: o }, function (t) { return { $x: function () { return Vn(t, n) } } }) } }); function Xn(t, e) { return t(e = { exports: {} }, e.exports), e.exports } var Yn = Xn(function (t) { !function (t, e) { function i(t) { var r, e = this, n = (r = 4022871197, function (t) { t = t.toString(); for (var e = 0; e < t.length; e++) { var n = .02519603282416938 * (r += t.charCodeAt(e)); n -= r = n >>> 0, r = (n *= r) >>> 0, r += 4294967296 * (n -= r) } return 2.3283064365386963e-10 * (r >>> 0) }); e.next = function () { var t = 2091639 * e.s0 + 2.3283064365386963e-10 * e.c; return e.s0 = e.s1, e.s1 = e.s2, e.s2 = t - (e.c = 0 | t) }, e.c = 1, e.s0 = n(" "), e.s1 = n(" "), e.s2 = n(" "), e.s0 -= n(t), e.s0 < 0 && (e.s0 += 1), e.s1 -= n(t), e.s1 < 0 && (e.s1 += 1), e.s2 -= n(t), e.s2 < 0 && (e.s2 += 1), n = null } function a(t, e) { return e.c = t.c, e.s0 = t.s0, e.s1 = t.s1, e.s2 = t.s2, e } function n(t, e) { var n = new i(t), r = e && e.state, o = n.next; return o.int32 = function () { return 4294967296 * n.next() | 0 }, o.double = function () { return o() + 11102230246251565e-32 * (2097152 * o() | 0) }, o.quick = o, r && ("object" == typeof r && a(r, n), o.state = function () { return a(n, {}) }), o } e && e.exports ? e.exports = n : this.alea = n }(0, t) }), $n = Xn(function (t) { !function (t, e) { function i(t) { var e = this, n = ""; e.x = 0, e.y = 0, e.z = 0, e.w = 0, e.next = function () { var t = e.x ^ e.x << 11; return e.x = e.y, e.y = e.z, e.z = e.w, e.w ^= e.w >>> 19 ^ t ^ t >>> 8 }, t === (0 | t) ? e.x = t : n += t; for (var r = 0; r < n.length + 64; r++)e.x ^= 0 | n.charCodeAt(r), e.next() } function a(t, e) { return e.x = t.x, e.y = t.y, e.z = t.z, e.w = t.w, e } function n(t, e) { function n() { return (r.next() >>> 0) / 4294967296 } var r = new i(t), o = e && e.state; return n.double = function () { do { var t = ((r.next() >>> 11) + (r.next() >>> 0) / 4294967296) / (1 << 21) } while (0 === t); return t }, n.int32 = r.next, n.quick = n, o && ("object" == typeof o && a(o, r), n.state = function () { return a(r, {}) }), n } e && e.exports ? e.exports = n : this.xor128 = n }(0, t) }), Jn = Xn(function (t) { !function (t, e) { function i(t) { var e = this, n = ""; e.next = function () { var t = e.x ^ e.x >>> 2; return e.x = e.y, e.y = e.z, e.z = e.w, e.w = e.v, (e.d = e.d + 362437 | 0) + (e.v = e.v ^ e.v << 4 ^ t ^ t << 1) | 0 }, e.x = 0, e.y = 0, e.z = 0, e.w = 0, t === ((e.v = 0) | t) ? e.x = t : n += t; for (var r = 0; r < n.length + 64; r++)e.x ^= 0 | n.charCodeAt(r), r == n.length && (e.d = e.x << 10 ^ e.x >>> 4), e.next() } function a(t, e) { return e.x = t.x, e.y = t.y, e.z = t.z, e.w = t.w, e.v = t.v, e.d = t.d, e } function n(t, e) { function n() { return (r.next() >>> 0) / 4294967296 } var r = new i(t), o = e && e.state; return n.double = function () { do { var t = ((r.next() >>> 11) + (r.next() >>> 0) / 4294967296) / (1 << 21) } while (0 === t); return t }, n.int32 = r.next, n.quick = n, o && ("object" == typeof o && a(o, r), n.state = function () { return a(r, {}) }), n } e && e.exports ? e.exports = n : this.xorwow = n }(0, t) }), Qn = Xn(function (t) { !function (t, e) { function i(t) { var o = this; o.next = function () { var t, e, n = o.x, r = o.i; return t = n[r], e = (t ^= t >>> 7) ^ t << 24, e ^= (t = n[r + 1 & 7]) ^ t >>> 10, e ^= (t = n[r + 3 & 7]) ^ t >>> 3, e ^= (t = n[r + 4 & 7]) ^ t << 7, t = n[r + 7 & 7], e ^= (t ^= t << 13) ^ t << 9, n[r] = e, o.i = r + 1 & 7, e }, function (t, e) { var n, r = []; if (e === (0 | e)) r[0] = e; else for (e = "" + e, n = 0; n < e.length; ++n)r[7 & n] = r[7 & n] << 15 ^ e.charCodeAt(n) + r[n + 1 & 7] << 13; for (; r.length < 8;)r.push(0); for (n = 0; n < 8 && 0 === r[n]; ++n); for (8 == n ? r[7] = -1 : r[n], t.x = r, t.i = 0, n = 256; 0 < n; --n)t.next() }(o, t) } function a(t, e) { return e.x = t.x.slice(), e.i = t.i, e } function n(t, e) { null == t && (t = +new Date); function n() { return (r.next() >>> 0) / 4294967296 } var r = new i(t), o = e && e.state; return n.double = function () { do { var t = ((r.next() >>> 11) + (r.next() >>> 0) / 4294967296) / (1 << 21) } while (0 === t); return t }, n.int32 = r.next, n.quick = n, o && (o.x && a(o, r), n.state = function () { return a(r, {}) }), n } e && e.exports ? e.exports = n : this.xorshift7 = n }(0, t) }), Zn = Xn(function (t) { !function (t, e) { function i(t) { var i = this; i.next = function () { var t, e, n = i.w, r = i.X, o = i.i; return i.w = n = n + 1640531527 | 0, e = r[o + 34 & 127], t = r[o = o + 1 & 127], e ^= e << 13, t ^= t << 17, e ^= e >>> 15, t ^= t >>> 12, e = r[o] = e ^ t, i.i = o, e + (n ^ n >>> 16) | 0 }, function (t, e) { var n, r, o, i, a, s = [], u = 128; for (e === (0 | e) ? (r = e, e = null) : (e += "\0", r = 0, u = Math.max(u, e.length)), o = 0, i = -32; i < u; ++i)e && (r ^= e.charCodeAt((i + 32) % e.length)), 0 === i && (a = r), r ^= r << 10, r ^= r >>> 15, r ^= r << 4, r ^= r >>> 13, 0 <= i && (a = a + 1640531527 | 0, o = 0 == (n = s[127 & i] ^= r + a) ? o + 1 : 0); for (128 <= o && (s[127 & (e && e.length || 0)] = -1), o = 127, i = 512; 0 < i; --i)r = s[o + 34 & 127], n = s[o = o + 1 & 127], r ^= r << 13, n ^= n << 17, r ^= r >>> 15, n ^= n >>> 12, s[o] = r ^ n; t.w = a, t.X = s, t.i = o }(i, t) } function a(t, e) { return e.i = t.i, e.w = t.w, e.X = t.X.slice(), e } function n(t, e) { null == t && (t = +new Date); function n() { return (r.next() >>> 0) / 4294967296 } var r = new i(t), o = e && e.state; return n.double = function () { do { var t = ((r.next() >>> 11) + (r.next() >>> 0) / 4294967296) / (1 << 21) } while (0 === t); return t }, n.int32 = r.next, n.quick = n, o && (o.X && a(o, r), n.state = function () { return a(r, {}) }), n } e && e.exports ? e.exports = n : this.xor4096 = n }(0, t) }), tr = Xn(function (t) { !function (t, e) { function i(t) { var o = this, e = ""; o.next = function () { var t = o.b, e = o.c, n = o.d, r = o.a; return t = t << 25 ^ t >>> 7 ^ e, e = e - n | 0, n = n << 24 ^ n >>> 8 ^ r, r = r - t | 0, o.b = t = t << 20 ^ t >>> 12 ^ e, o.c = e = e - n | 0, o.d = n << 16 ^ e >>> 16 ^ r, o.a = r - t | 0 }, o.a = 0, o.b = 0, o.c = -1640531527, o.d = 1367130551, t === Math.floor(t) ? (o.a = t / 4294967296 | 0, o.b = 0 | t) : e += t; for (var n = 0; n < e.length + 20; n++)o.b ^= 0 | e.charCodeAt(n), o.next() } function a(t, e) { return e.a = t.a, e.b = t.b, e.c = t.c, e.d = t.d, e } function n(t, e) { function n() { return (r.next() >>> 0) / 4294967296 } var r = new i(t), o = e && e.state; return n.double = function () { do { var t = ((r.next() >>> 11) + (r.next() >>> 0) / 4294967296) / (1 << 21) } while (0 === t); return t }, n.int32 = r.next, n.quick = n, o && ("object" == typeof o && a(o, r), n.state = function () { return a(r, {}) }), n } e && e.exports ? e.exports = n : this.tychei = n }(0, t) }), er = Xn(function (e) { !function (s, u) { var c, l = this, h = 256, f = 6, p = "random", d = u.pow(h, f), v = u.pow(2, 52), m = 2 * v, g = h - 1; function t(t, e, n) { function r() { for (var t = a.g(f), e = d, n = 0; t < v;)t = (t + n) * h, e *= h, n = a.g(1); for (; m <= t;)t /= 2, e /= 2, n >>>= 1; return (t + n) / e } var o = [], i = b(function t(e, n) { var r, o = [], i = typeof e; if (n && "object" == i) for (r in e) try { o.push(t(e[r], n - 1)) } catch (t) { } return o.length ? o : "string" == i ? e : e + "\0" }((e = 1 == e ? { entropy: !0 } : e || {}).entropy ? [t, w(s)] : null == t ? function () { try { var t; return c && (t = c.randomBytes) ? t = t(h) : (t = new Uint8Array(h), (l.crypto || l.msCrypto).getRandomValues(t)), w(t) } catch (t) { var e = l.navigator, n = e && e.plugins; return [+new Date, l, n, l.screen, w(s)] } }() : t, 3), o), a = new y(o); return r.int32 = function () { return 0 | a.g(4) }, r.quick = function () { return a.g(4) / 4294967296 }, r.double = r, b(w(a.S), s), (e.pass || n || function (t, e, n, r) { return r && (r.S && x(r, a), t.state = function () { return x(a, {}) }), n ? (u[p] = t, e) : t })(r, i, "global" in e ? e.global : this == u, e.state) } function y(t) { var e, n = t.length, a = this, r = 0, o = a.i = a.j = 0, i = a.S = []; for (n || (t = [n++]); r < h;)i[r] = r++; for (r = 0; r < h; r++)i[r] = i[o = g & o + t[r % n] + (e = i[r])], i[o] = e; (a.g = function (t) { for (var e, n = 0, r = a.i, o = a.j, i = a.S; t--;)e = i[r = g & r + 1], n = n * h + i[g & (i[r] = i[o = g & o + e]) + (i[o] = e)]; return a.i = r, a.j = o, n })(h) } function x(t, e) { return e.i = t.i, e.j = t.j, e.S = t.S.slice(), e } function b(t, e) { for (var n, r = t + "", o = 0; o < r.length;)e[g & o] = g & (n ^= 19 * e[g & o]) + r.charCodeAt(o++); return w(e) } function w(t) { return String.fromCharCode.apply(0, t) } if (u["seed" + p] = t, b(u.random(), s), e.exports) { e.exports = t; try { c = require("crypto") } catch (t) { } } }([], Math) }); er.alea = Yn, er.xor128 = $n, er.xorwow = Jn, er.xorshift7 = Qn, er.xor4096 = Zn, er.tychei = tr; var nr = er.alea, rr = (ur.prototype.nextValue = function () { if (!isNaN(this.nextVal)) { var t = this.nextVal; return this.nextVal = NaN, t } for (var e, n, r = !1; !r;) { for (var o = void 0, i = void 0, a = void 0; 1 <= (a = (o = 2 * this.random() - 1) * o + (i = 2 * this.random() - 1) * i) || 0 === a;); var s = Math.sqrt(-2 * Math.log(a) / a); e = this.mean + this.stdDev * o * s, n = this.mean + this.stdDev * i * s, this.truncated && !this.isValidTruncated(e) || (r = !0) } return this.truncated && !this.isValidTruncated(n) || (this.nextVal = this.convertValue(n)), this.convertValue(e) }, ur.prototype.convertValue = function (t) { return null == this.dtype || "float32" === this.dtype ? t : Math.round(t) }, ur.prototype.isValidTruncated = function (t) { return t <= this.upper && t >= this.lower }, ur), or = (sr.prototype.nextValue = function () { for (var t, e, n, r, o, i; ;) { for (; r = this.randn.nextValue(), (i = 1 + this.c * r) <= 0;); if (i *= i * i, e = 1 - .331 * (t = r * r) * t, n = .5 * t + this.d * (1 - i + Math.log(i)), (o = this.randu()) < e || Math.log(o) < n) break } return i = 1 / this.beta * this.d * i, this.alpha < 1 && (i *= Math.pow(this.randu(), 1 / this.alpha)), this.convertValue(i) }, sr.prototype.convertValue = function (t) { return "float32" === this.dtype ? t : Math.round(t) }, sr), ir = (ar.prototype.convertValue = function (t) { return this.canReturnFloat() ? t : Math.round(t) }, ar.prototype.nextValue = function () { return this.convertValue(this.min + this.range * this.random()) }, ar); function ar(t, e, n, r) { var o = this; if (void 0 === t && (t = 0), void 0 === e && (e = 1), this.canReturnFloat = function () { return null == o.dtype || "float32" === o.dtype }, this.min = t, this.range = e - t, this.dtype = n, null == r && (r = Math.random()), "number" == typeof r && (r = r.toString()), !this.canReturnFloat() && this.range <= 1) throw new Error("The difference between " + t + " - " + e + " <= 1 and dtype is not float"); this.random = nr(r) } function sr(t, e, n, r) { this.alpha = t, this.beta = 1 / e, this.dtype = n; var o = r || Math.random(); this.randu = nr(o.toString()), this.randn = new rr(0, 1, n, !1, this.randu()), this.d = t < 1 ? t + 2 / 3 : t - 1 / 3, this.c = 1 / Math.sqrt(9 * this.d) } function ur(t, e, n, r, o) { this.mean = t, this.stdDev = e, this.dtype = n, this.nextVal = NaN, this.truncated = r, this.truncated && (this.upper = this.mean + 2 * this.stdDev, this.lower = this.mean - 2 * this.stdDev); var i = o || Math.random(); this.random = nr(i.toString()) } function cr(t, e, n) { return void 0 === e && (e = "float32"), e = e || "float32", et(t), new vt(t, e, n) } function lr(t, e) { void 0 === e && (e = !1), console.log(t.toString(e)) } function hr(h, f) { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l; return R(this, function (t) { switch (t.label) { case 0: return e = cn(h, "x", "setdiff1d"), n = cn(f, "y", "setdiff1d"), P(e.dtype === n.dtype, function () { return "x and y should have the same dtype, but got x (" + e.dtype + ") and y (" + n.dtype + ")." }), P(1 === e.rank, function () { return "x should be 1D tensor, but got x (" + e.shape + ")." }), P(1 === n.rank, function () { return "y should be 1D tensor, but got y (" + n.shape + ")." }), [4, e.data()]; case 1: return r = t.sent(), [4, n.data()]; case 2: for (o = t.sent(), i = new Set(o), c = a = 0; c < r.length; c++)i.has(r[c]) || a++; for (s = new vt([a], e.dtype), u = new vt([a], "int32"), l = c = 0; c < r.length; c++)i.has(r[c]) || (s.values[l] = r[c], u.values[l] = c, l++); return [2, [s.toTensor(), u.toTensor()]] } }) }) } var fr = wn({ batchToSpaceND_: function (t, e, n) { var r = cn(t, "x", "batchToSpaceND"), o = e.reduce(function (t, e) { return t * e }); return P(r.rank >= 1 + e.length, function () { return "input rank is " + r.rank + " but should be > than blockShape.length " + e.length }), P(n.length === e.length, function () { return "crops.length is " + n.length + " but should be equal to blockShape.length  " + e.length }), P(r.shape[0] % o == 0, function () { return "input tensor batch is " + r.shape[0] + " but is not divisible by the product of the elements of blockShape " + e.join(" * ") + " === " + o }), Kt.runKernelFunc(function (t) { return t.batchToSpaceND(r, e, n) }, { $x: r }, function (t) { return { $x: function () { return t.spaceToBatchND(e, n) } } }) } }), pr = wn({ broadcastTo_: function (t, e) { var n = cn(t, "broadcastTo", "x"), r = n.shape; if (e.some(function (t) { return !(0 < t) || t % 1 != 0 })) throw new Error("broadcastTo(): Invalid broadcast shape [" + e + "]."); if (e.length < n.rank) throw new Error("broadcastTo(): shape.length=" + e.length + " < input.rank=" + n.rank + "."); if (e.length > n.rank) { for (var o = n.shape.slice(); o.length < e.length;)o.unshift(1); n = n.reshape(o) } for (var i = Array.from(e), a = e.length - 1; 0 <= a; a--)if (n.shape[a] === e[a]) i[a] = 1; else if (1 !== n.shape[a]) throw new Error("broadcastTo(): [" + r + "] cannot be broadcast to [" + e + "]."); var s = i.map(function (t, e) { return 1 < t ? e : -1 }).filter(function (t) { return 0 <= t }); return 0 === s.length ? n.clone() : Kt.runKernelFunc(function (t) { return t.tile(n, i) }, { input: n }, function (t) { return { input: function () { return t.sum(s, !0) } } }) } }), dr = wn({ cast_: function (t, e) { var n = cn(t, "x", "cast"); if (!O(e)) throw new Error("Failed to cast to unknown dtype " + e); if ("string" === e && "string" !== n.dtype || "string" !== e && "string" === n.dtype) throw new Error("Only strings can be casted to strings"); var r = { dtype: e }; return Kt.runKernelFunc(function (t) { return t.cast(n, e) }, { x: n }, function (t) { return { x: function () { return t.clone() } } }, "Cast", r) } }), vr = wn({ clone_: function (t) { var e = cn(t, "x", "clone", null); return Kt.runKernelFunc(function () { return Kt.makeTensorFromDataId(e.dataId, e.shape, e.dtype) }, { $x: e }, function (t) { return { $x: function () { return t.toFloat() } } }) } }), mr = wn({ cumsum_: function (t, e, n, r) { void 0 === e && (e = 0), void 0 === n && (n = !1), void 0 === r && (r = !1); var o = cn(t, "x", "cumsum"), i = mn([e |= 0], o.rank), a = o; null != i && (a = o.transpose(i)); var s = yn(1, o.rank)[0], u = Kt.runKernelFunc(function (t) { return t.cumsum(a, s, n, r) }, { permutedX: a }, function (t) { return { permutedX: function () { return t.cumsum(e, n, !r) } } }); return null != i && (u = u.transpose(i)), u } }), gr = wn({ depthToSpace_: function (t, e, n) { void 0 === n && (n = "NHWC"); var r = cn(t, "x", "depthToSpace"), o = "NHWC" === n ? r.shape[1] : r.shape[2], i = "NHWC" === n ? r.shape[2] : r.shape[3], a = "NHWC" === n ? r.shape[3] : r.shape[1]; return P(0 <= o * e, function () { return "Negative dimension size caused by overflow when multiplying\n      " + o + " and " + e + "  for depthToSpace with input shape\n      " + r.shape }), P(0 <= i * e, function () { return "Negative dimension size caused by overflow when multiplying\n      " + i + " and " + e + " for depthToSpace with input shape\n          " + r.shape }), P(a % (e * e) == 0, function () { return "Dimension size must be evenly divisible by " + e * e + " but is " + a + " for depthToSpace with input shape " + r.shape }), Kt.runKernelFunc(function (t) { return t.depthToSpace(r, e, n) }, { $x: r }) } }), yr = wn({ expandDims_: function (t, e) { void 0 === e && (e = 0); var n = cn(t, "x", "expandDims", null); P(e <= n.rank, function () { return "Axis must be <= rank of the tensor" }); var r = n.shape.slice(); return e < 0 && (P(-(n.rank + 1) <= e, function () { return "Axis must be in the interval [" + -(n.rank + 1) + ", " + n.rank + "]" }), e = n.rank + e + 1), r.splice(e, 0, 1), Tr(n, r) } }), xr = wn({ eye_: function (t, e, n, r) { void 0 === r && (r = "float32"), null == e && (e = t); for (var o = cr([t, e], r), i = t <= e ? t : e, a = 0; a < i; ++a)o.set(1, a, a); var s = o.toTensor().as2D(t, e); if (null == n) return s; if (1 === n.length) return Or(yr(s, 0), [n[0], 1, 1]); if (2 === n.length) return Or(yr(yr(s, 0), 0), [n[0], n[1], 1, 1]); if (3 === n.length) return Or(yr(yr(yr(s, 0), 0), 0), [n[0], n[1], n[2], 1, 1]); throw new Error("eye() currently supports only 1D and 2D batchShapes, but received " + n.length + "D.") } }), br = wn({ multinomial_: function (t, e, n, r) { void 0 === r && (r = !1); var o = cn(t, "logits", "multinomial"), i = o.size, a = o.rank; if (i < 2) throw new Error("Error in multinomial: you need at least 2 outcomes, but got " + i + "."); if (2 < a) throw new Error("Rank of probabilities must be 1 or 2, but is " + a); n = n || Math.random(); var s = 1 === a ? o.as2D(1, -1) : o, u = Kt.runKernelFunc(function (t) { return t.multinomial(s, r, e, n) }, { logits2D: s }); return 1 === a ? u.as1D() : u } }), wr = wn({ oneHot_: function (t, e, n, r) { if (void 0 === n && (n = 1), void 0 === r && (r = 0), e < 2) throw new Error("Error in oneHot: depth must be >=2, but it is " + e); var o = cn(t, "indices", "oneHot", "int32"), i = o.shape.concat([e]); return o = o.flatten(), Kt.runKernelFunc(function (t) { return t.oneHot(o, e, n, r) }, { $indices: o }, function (t) { return { $indices: function () { return Pn(o.shape, "float32") } } }).reshape(i) } }), Cr = wn({ pad_: function (t, n, e) { void 0 === e && (e = 0); var r = cn(t, "x", "pad"); if (0 === r.rank) throw new Error("pad(scalar) is not defined. Pass non-scalar to pad"); var o = { paddings: n, constantValue: e }; return Kt.runKernelFunc(function (t) { return t.pad(r, n, e) }, { x: r }, function (t) { var e = n.map(function (t) { return t[0] }); return { x: function () { return t.slice(e, r.shape) } } }, "PadV2", o) } }), Er = wn({ pad1d_: function (t, e, n) { return void 0 === n && (n = 0), P(2 === e.length, function () { return "Invalid number of paddings. Must be length of 2." }), Cr(t, [e], n) } }), _r = wn({ pad2d_: function (t, e, n) { return void 0 === n && (n = 0), P(2 === e.length && 2 === e[0].length && 2 === e[1].length, function () { return "Invalid number of paddings. Must be length of 2 each." }), Cr(t, e, n) } }), Ir = wn({ pad3d_: function (t, e, n) { return void 0 === n && (n = 0), P(3 === e.length && 2 === e[0].length && 2 === e[1].length && 2 === e[2].length, function () { return "Invalid number of paddings. Must be length of 2 each." }), Cr(t, e, n) } }), Rr = wn({ pad4d_: function (t, e, n) { return void 0 === n && (n = 0), P(4 === e.length && 2 === e[0].length && 2 === e[1].length && 2 === e[2].length && 2 === e[3].length, function () { return "Invalid number of paddings. Must be length of 2 each." }), Cr(t, e, n) } }), kr = wn({ rand_: function (t, e, n) { var r = L(t), o = null; if (null == n || "float32" === n) o = new Float32Array(r); else if ("int32" === n) o = new Int32Array(r); else { if ("bool" !== n) throw new Error("Unknown data type " + n); o = new Uint8Array(r) } for (var i = 0; i < r; i++)o[i] = e(); return Kt.makeTensor(o, t, n) } }), Sr = wn({ randomNormal_: function (t, e, n, r, o) { if (void 0 === e && (e = 0), void 0 === n && (n = 1), null != r && "bool" === r) throw new Error("Unsupported data type " + r); for (var i = new rr(e, n, r, !1, o), a = cr(t, r), s = 0; s < a.values.length; s++)a.values[s] = i.nextValue(); return a.toTensor() } }), Dr = wn({ randomGamma_: function (t, e, n, r, o) { if (void 0 === n && (n = 1), void 0 === r && (r = "float32"), null == n && (n = 1), null == r && (r = "float32"), "float32" !== r && "int32" !== r) throw new Error("Unsupported data type " + r); for (var i = new or(e, n, r, o), a = cr(t, r), s = 0; s < a.values.length; s++)a.values[s] = i.nextValue(); return a.toTensor() } }), Ar = wn({ randomUniform_: function (t, e, n, r, o) { void 0 === e && (e = 0), void 0 === n && (n = 1), void 0 === r && (r = "float32"); for (var i = cr(t, r), a = new ir(e, n, null, o), s = 0; s < i.values.length; s++)i.values[s] = a.nextValue(); return i.toTensor() } }), Tr = wn({ reshape_: function (t, e) { var n = cn(t, "x", "reshape", null); e = S(e, n.size), P(n.size === L(e), function () { return "new shape and old shape must have the same number of elements." }); var r = { shape: e }; return Kt.runKernelFunc(function (t) { return t.reshape(n, e) }, { x: n }, function (t) { return { x: function () { return t.reshape(n.shape) } } }, "Reshape", r) } }), Nr = wn({ spaceToBatchND_: function (t, r, o) { var e = cn(t, "x", "spaceToBatchND"); return P(e.rank >= 1 + r.length, function () { return "input rank " + e.rank + " should be > than [blockShape] " + r.length }), P(o.length === r.length, function () { return "paddings.shape[0] " + o.length + " must be equal to [blockShape] " + r.length }), P(e.shape.reduce(function (t, e, n) { return 0 < n && n <= r.length ? t && (e + o[n - 1][0] + o[n - 1][1]) % r[n - 1] == 0 : t }, !0), function () { return "input spatial dimensions " + e.shape.slice(1) + " with paddings " + o.toString() + " must be divisible by blockShapes " + r.toString() }), Kt.runKernelFunc(function (t) { return t.spaceToBatchND(e, r, o) }, { $x: e }, function (t) { return { $x: function () { return t.batchToSpaceND(r, o) } } }) } }), Fr = wn({ squeeze_: function (t, e) { var n = cn(t, "x", "squeeze"); return Tr(n, T(n.shape, e).newShape) } }), Mr = wn({ stack_: function (t, e) { void 0 === e && (e = 0); var n = ln(t, "tensors", "stack"); if (P(1 <= n.length, function () { return "Pass at least one tensor to tf.stack" }), 1 === n.length) return n[0].expandDims(e); var r = n[0].rank, o = n[0].shape, i = n[0].dtype; P(e <= r, function () { return "Axis must be <= rank of the tensor" }), n.forEach(function (t) { x(o, t.shape, "All tensors passed to stack must have matching shapes") }), n.forEach(function (t) { P(i === t.dtype, function () { return "All tensors passed to stack must have matching dtypes" }) }); var a = n.map(function (t) { return t.expandDims(e) }); return Vn(a, e) } }), Or = wn({ tile_: function (t, s) { var r = cn(t, "x", "tile", null); P(r.rank === s.length, function () { return "Error in transpose: rank of input " + r.rank + " must match length of reps " + s + "." }); var e = [r], n = { reps: s }; return Kt.runKernelFunc(function (t, e) { var n = t.tile(r, s); return e([r]), n }, { x: r }, function (i, t) { var a = t[0]; return { x: function () { var t = Un(a); if (1 === a.rank) for (var e = 0; e < s[0]; ++e)t = t.add(i.slice([e * a.shape[0]], [a.shape[0]])); else if (2 === a.rank) for (e = 0; e < s[0]; ++e)for (var n = 0; n < s[1]; ++n)t = t.add(i.slice([e * a.shape[0], n * a.shape[1]], [a.shape[0], a.shape[1]])); else if (3 === a.rank) for (e = 0; e < s[0]; ++e)for (n = 0; n < s[1]; ++n)for (var r = 0; r < s[2]; ++r)t = t.add(i.slice([e * a.shape[0], n * a.shape[1], r * a.shape[2]], [a.shape[0], a.shape[1], a.shape[2]])); else { if (4 !== a.rank) throw new Error("Gradient for tile operation is not implemented for rank-" + a.rank + " tensors yet."); for (e = 0; e < s[0]; ++e)for (n = 0; n < s[1]; ++n)for (r = 0; r < s[2]; ++r)for (var o = 0; o < s[3]; ++o)t = t.add(i.slice([e * a.shape[0], n * a.shape[1], r * a.shape[2], o * a.shape[3]], [a.shape[0], a.shape[1], a.shape[2], a.shape[3]])) } return t } } }, "Tile", n, e) } }), Pr = wn({ truncatedNormal_: function (t, e, n, r, o) { if (void 0 === e && (e = 0), void 0 === n && (n = 1), null != r && "bool" === r) throw new Error("Unsupported data type " + r); for (var i = new rr(e, n, r, !0, o), a = cr(t, r), s = 0; s < a.values.length; s++)a.values[s] = i.nextValue(); return a.toTensor() } }), Br = wn({ unstack_: function (t, e) { void 0 === e && (e = 0), e = e || 0; var n = cn(t, "x", "unstack"); P(e >= -n.shape.length && e < n.shape.length, function () { return "Axis = " + e + " is not in [-" + n.shape.length + ", " + n.shape.length + ")" }), e < 0 && (e += n.shape.length); var r = { axis: e }; return Kt.runKernelFunc(function (t) { return t.unstack(n, e) }, { x: n }, function (t) { return { x: function () { return Mr(t, e) } } }, "Unpack", r) } }); function Lr(t, e, n, r) { void 0 === r && (r = !0); var o = []; if (r) (o = o.concat(e.slice(0))).push(t[0] / n), o = o.concat(t.slice(1)); else { o = o.concat(t[0]); for (var i = e.length, a = 0; a < i; ++a)o = o.concat([t[a + 1] / e[a], e[a]]); o = o.concat(t.slice(i + 1)) } return o } function Wr(t, e, n) { void 0 === n && (n = !0); var r = []; if (n) { r.push(e); for (var o = e + 1; o < t; ++o)o <= 2 * e ? (r.push(o), r.push(o - (e + 1))) : r.push(o) } else { var i = [], a = []; for (o = 1; o < t; ++o)2 * e + 1 <= o || o % 2 == 1 ? a.push(o) : i.push(o); r.push.apply(r, i), r.push(0), r.push.apply(r, a) } return r } function zr(t, e, n, r) { void 0 === r && (r = !0); var o = []; r ? o.push(t[0] / n) : o.push(t[0] * n); for (var i = 1; i < t.length; ++i)i <= e.length ? r ? o.push(e[i - 1] * t[i]) : o.push(t[i] / e[i - 1]) : o.push(t[i]); return o } function Ur(t, e) { for (var n = [0], r = 0; r < e; ++r)n.push(t[r][0]); return n } function Vr(t, e, n) { for (var r = t.slice(0, 1), o = 0; o < n; ++o)r.push(t[o + 1] - e[o][0] - e[o][1]); return r } function Gr(t, e) { if (t.rank < 1) throw new Error("tf.gatherND() expects the input to be rank 1 or higher, but the rank was " + t.rank + "."); if (e.rank < 1) throw new Error("tf.gatherND() expects the indices to be rank 1 or higher, but the rank was " + e.rank + "."); if ("int32" !== e.dtype) throw new Error("tf.gatherND() expects the indices to be int32 type, but the dtype was " + e.dtype + "."); if (e.shape[e.rank - 1] > t.rank) throw new Error("index innermost dimension length must be <= tensor rank; saw: " + e.shape[e.rank - 1] + " vs. " + t.rank); if (0 === t.size) throw new Error("Requested more than 0 entries, but input is empty. Input shape: " + t.shape + "."); for (var n = e.shape, r = n[n.length - 1], o = 1, i = 0; i < n.length - 1; ++i)o *= n[i]; var a = t.shape, s = n.slice(); s.pop(); var u = 1; for (i = r; i < t.rank; ++i)u *= a[i], s.push(a[i]); var c = Y(t.shape).map(function (t) { return t / u }).concat([1]).slice(0, r); return [s, o, u, c] } var Hr = Object.freeze({ prepareAndValidate: Gr }); function qr(t) { return t <= 30 ? t : X(t, Math.floor(Math.sqrt(t))) } function jr(t, e, n) { var r = 1 < e.rank ? e.shape[e.rank - 1] : 1, o = 1 < e.rank ? e.rank - 1 : 1, i = "Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: " + n.shape + ", indices.shape: " + e.shape + ", shape: " + t + ", sliceDim: " + r + ", and batchDim: " + o + "."; if (n.rank < o) throw new Error(i + " update.rank < " + o + ". "); if (t.length < r + (n.rank - o)) throw new Error(i + " Output shape length < " + (r + (n.rank - o))); if (n.rank !== o + t.length - r) throw new Error(i + " update.rank != " + (o + t.length - r)); for (var a = 0; a < o; ++a)if (n.shape[a] !== e.shape[a]) throw new Error(i + " updates.shape[" + a + "] (" + n.shape[a] + ") != indices.shape[" + a + "] (" + e.shape[a] + ")."); for (a = 0; a < n.rank - o; ++a)if (n.shape[a + o] !== t[a + r]) throw new Error(i + " updates.shape[" + (a + o) + "] (" + n.shape[a + o] + ") != shape[" + (a + o) + "] (" + t[a + o] + ")") } function Kr(t, e, n) { if (e.rank < 1) throw new Error("tf.scatterND() expects the indices to be rank 1 or higher, but the rank was " + e.rank + "."); if (t.rank < 1) throw new Error("tf.scatterND() expects the updates to be rank 1 or higher, but the rank was " + t.rank + "."); if ("int32" !== e.dtype) throw new Error("The dtype of 'indices' should be int32, but got dtype: " + e.dtype); if (n.length < 1) throw new Error("Output rank must be greater or equal to 1, but got shape: " + n); if (0 === n.length) { if (0 === e.size) throw new Error("Indices specified for empty output. indices shape: " + e.shape); if (0 === t.size) throw new Error("Updates specified for empty output. updates shape: " + t.shape) } jr(n, e, t) } function Xr(t, e, n) { for (var r = e.shape.length, o = 1 < r ? e.shape[r - 1] : 1, i = n.length, a = 1, s = o; s < i; ++s)a *= n[s]; var u = o < 1 ? 1 : o; return { sliceRank: o, numUpdates: L(e.shape) / u, sliceSize: a, strides: Y(n.slice(0, o)).concat([1]), outputSize: L(n) } } var Yr = Object.freeze({ validateUpdateShape: jr, validateInput: Kr, calculateShapes: Xr }); function $r(e, n, r) { P(e.rank === n.length, function () { return "Error in slice" + e.rank + "D: Length of begin " + n + " must match the rank of the array (" + e.rank + ")." }), P(e.rank === r.length, function () { return "Error in slice" + e.rank + "D: Length of size " + r + " must match the rank of the array (" + e.rank + ")." }); for (var t = function (t) { P(n[t] + r[t] <= e.shape[t], function () { return "Error in slice" + e.rank + "D: begin[" + t + "] + size[" + t + "] (" + (n[t] + r[t]) + ") would overflow input.shape[" + t + "] (" + e.shape[t] + ")" }) }, o = 0; o < e.rank; ++o)t(o) } function Jr(t) { for (var e = [], n = 0; 0 < t;)1 & t && e.push(n), t /= 2, n++; return e } function Qr(t, e, n) { for (var r = [], o = 0; o < t.length; o++)r[o] = Math.ceil((e[o] - t[o]) / n[o]); return r } function Zr(t, e, n, r, o) { var i = e[o], a = n[o] || 1; (t & 1 << o || null == i) && (i = 0 < a ? Number.MIN_SAFE_INTEGER : Number.MAX_SAFE_INTEGER); var s = r[o]; return i < 0 && (i += s), d(0, i, s - 1) } function to(t, e, n, r, o) { var i = e[o], a = n[o] || 1; (t & 1 << o || null == i) && (i = 0 < a ? Number.MAX_SAFE_INTEGER : Number.MIN_SAFE_INTEGER); var s = r[o]; return i < 0 && (i += s), 0 < a ? d(0, i, s) : d(-1, i, s - 1) } function eo(t, e, n) { for (var r = n.length, o = 0; o < n.length; o++)if (1 < n[o]) { r = o; break } for (o = r + 1; o < n.length; o++)if (0 < e[o] || n[o] !== t[o]) return !1; return !0 } function no(t, e) { for (var n = 0 < t.length ? t[t.length - 1] : 1, r = 0; r < t.length - 1; r++)n += t[r] * e[r]; return n } var ro = Object.freeze({ assertParamsValid: $r, maskToAxes: Jr, computeOutShape: Qr, startForAxis: Zr, stopForAxis: to, isSliceContinous: eo, computeFlatOffset: no }); function oo(t, e) { P(K(t), function () { return "The f passed in variableGrads(f) must be a function" }), P(null == e || Array.isArray(e) && e.every(function (t) { return t instanceof Ft }), function () { return "The varList passed in variableGrads(f, varList) must be an array of variables" }); var n = null != e; if (!n) for (var r in e = [], Kt.registeredVariables) e.push(Kt.registeredVariables[r]); var o = n ? e.filter(function (t) { return !t.trainable }) : null, i = e.length; P(0 < (e = e.filter(function (t) { return t.trainable })).length, function () { return "variableGrads() expects at least one of the input variables to be trainable, but none of the " + i + " variables is trainable." }); var a = Kt.gradients(t, e, null, !0), s = a.value, u = a.grads; P(u.some(function (t) { return null != t }), function () { return "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()." }), P(0 === s.rank, function () { return "The f passed in variableGrads(f) must return a scalar, but it returned a rank-" + s.rank + " tensor" }); var c = {}; return e.forEach(function (t, e) { null != u[e] && (c[t.name] = u[e]) }), null != o && o.forEach(function (t) { return c[t.name] = null }), { value: s, grads: c } } function io(t) { return Kt.customGrad(t) } function ao(t) { if (0 < t.filter(function (t) { return null == t }).length) throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that\n    the f you passed encloses all operations that lead from x to y.") } var so = wn({ softmax_: function (t, o) { void 0 === o && (o = -1); var r = cn(t, "logits", "softmax", "float32"); if (-1 === o && (o = r.rank - 1), o !== r.rank - 1) throw Error("Softmax along a non-last dimension is not yet supported. Logits was rank " + r.rank + " and dim was " + o); return Kt.runKernelFunc(function (t, e) { var n = t.softmax(r, o); return e([n]), n }, { logits: r }, function (t, e) { var n = e[0], r = t.mul(n); return { logits: function () { return r.sub(r.sum([o], !0).mul(n)) } } }, "Softmax", { dim: o }, [], [!0]) } }), uo = wn({ logSoftmax_: function (t, i) { void 0 === i && (i = -1); var e = cn(t, "logits", "logSoftmax"); if (-1 === i && (i = e.rank - 1), i !== e.rank - 1) throw Error("Log Softmax along a non-last dimension is not yet supported. Logits was rank " + e.rank + " and axis was " + i); return io(function (t, e) { var n = t.max(i, !0), r = t.sub(n), o = r.toFloat().sub(r.exp().sum(i, !0).log()); return e([o]), { value: o, gradFunc: function (t, e) { var n = e[0].exp(); return t.sub(t.sum(i, !0).mul(n)) } } })(e) } }), co = (fo.prototype.get = function (t) { return this.data.has(t) || this.dataMover.moveData(this.backend, t), this.data.get(t) }, fo.prototype.set = function (t, e) { this.dataIdsCount++, this.data.set(t, e) }, fo.prototype.has = function (t) { return this.data.has(t) }, fo.prototype.delete = function (t) { return this.dataIdsCount--, this.data.delete(t) }, fo.prototype.numDataIds = function () { return this.dataIdsCount }, fo), lo = (ho.prototype.time = function (t) { return po("time") }, ho.prototype.read = function (t) { return po("read") }, ho.prototype.readSync = function (t) { return po("readSync") }, ho.prototype.numDataIds = function () { return po("numDataIds") }, ho.prototype.disposeData = function (t) { return po("disposeData") }, ho.prototype.write = function (t, e, n) { return po("write") }, ho.prototype.move = function (t, e, n, r) { return po("move") }, ho.prototype.memory = function () { return po("memory") }, ho.prototype.floatPrecision = function () { return po("floatPrecision") }, ho.prototype.epsilon = function () { return 32 === this.floatPrecision() ? 1e-7 : 1e-4 }, ho.prototype.batchMatMul = function (t, e, n, r) { return po("batchMatMul") }, ho.prototype.fusedBatchMatMul = function (t) { return t.a, t.b, t.transposeA, t.transposeB, t.bias, t.activation, t.preluActivationWeights, po("fusedBatchMatMul") }, ho.prototype.slice = function (t, e, n) { return po("slice") }, ho.prototype.stridedSlice = function (t, e, n, r) { return po("stridedSlice") }, ho.prototype.unstack = function (t, e) { return po("unstack") }, ho.prototype.reverse = function (t, e) { return po("reverse") }, ho.prototype.concat = function (t, e) { return po("concat") }, ho.prototype.neg = function (t) { return po("neg") }, ho.prototype.add = function (t, e) { return po("add") }, ho.prototype.addN = function (t) { return po("addN") }, ho.prototype.subtract = function (t, e) { return po("subtract") }, ho.prototype.multiply = function (t, e) { return po("multiply") }, ho.prototype.realDivide = function (t, e) { return po("realDivide") }, ho.prototype.floorDiv = function (t, e) { return po("floorDiv") }, ho.prototype.sum = function (t, e) { return po("sum") }, ho.prototype.prod = function (t, e) { return po("prod") }, ho.prototype.unsortedSegmentSum = function (t, e, n) { return po("unsortedSegmentSum") }, ho.prototype.argMin = function (t, e) { return po("argMin") }, ho.prototype.argMax = function (t, e) { return po("argMax") }, ho.prototype.equal = function (t, e) { return po("equal") }, ho.prototype.notEqual = function (t, e) { return po("notEqual") }, ho.prototype.less = function (t, e) { return po("less") }, ho.prototype.lessEqual = function (t, e) { return po("lessEqual") }, ho.prototype.greater = function (t, e) { return po("greater") }, ho.prototype.greaterEqual = function (t, e) { return po("greaterEqual") }, ho.prototype.logicalNot = function (t) { return po("logicalNot") }, ho.prototype.logicalAnd = function (t, e) { return po("logicalAnd") }, ho.prototype.logicalOr = function (t, e) { return po("logicalOr") }, ho.prototype.where = function (t) { return po("where") }, ho.prototype.select = function (t, e, n) { return po("select") }, ho.prototype.topk = function (t, e, n) { return po("topk") }, ho.prototype.min = function (t, e) { return po("min") }, ho.prototype.minimum = function (t, e) { return po("minimum") }, ho.prototype.mod = function (t, e) { return po("mod") }, ho.prototype.max = function (t, e) { return po("max") }, ho.prototype.maximum = function (t, e) { return po("maximum") }, ho.prototype.all = function (t, e) { return po("all") }, ho.prototype.any = function (t, e) { return po("any") }, ho.prototype.squaredDifference = function (t, e) { return po("squaredDifference") }, ho.prototype.ceil = function (t) { return po("ceil") }, ho.prototype.floor = function (t) { return po("floor") }, ho.prototype.round = function (t) { return po("round") }, ho.prototype.sign = function (t) { return po("sign") }, ho.prototype.isNaN = function (t) { return po("isNaN") }, ho.prototype.isInf = function (t) { return po("isInf") }, ho.prototype.isFinite = function (t) { return po("isFinite") }, ho.prototype.pow = function (t, e) { return po("pow") }, ho.prototype.exp = function (t) { return po("exp") }, ho.prototype.expm1 = function (t) { return po("expm1") }, ho.prototype.softmax = function (t, e) { return po("softmax") }, ho.prototype.log = function (t) { return po("log") }, ho.prototype.log1p = function (t) { return po("log1p") }, ho.prototype.sqrt = function (t) { return po("sqrt") }, ho.prototype.rsqrt = function (t) { return po("rsqrt") }, ho.prototype.square = function (t) { return po("square") }, ho.prototype.reciprocal = function (t) { return po("reciprocal") }, ho.prototype.relu = function (t) { return po("relu") }, ho.prototype.relu6 = function (t) { return po("relu6") }, ho.prototype.prelu = function (t, e) { return po("prelu") }, ho.prototype.elu = function (t) { return po("elu") }, ho.prototype.eluDer = function (t, e) { return po("eluDer") }, ho.prototype.selu = function (t) { return po("selu") }, ho.prototype.int = function (t) { return po("int") }, ho.prototype.clip = function (t, e, n) { return po("clip") }, ho.prototype.abs = function (t) { return po("abs") }, ho.prototype.complexAbs = function (t) { return po("complexAbs") }, ho.prototype.sigmoid = function (t) { return po("sigmoid") }, ho.prototype.softplus = function (t) { return po("softplus") }, ho.prototype.sin = function (t) { return po("sin") }, ho.prototype.cos = function (t) { return po("cos") }, ho.prototype.tan = function (t) { return po("tan") }, ho.prototype.asin = function (t) { return po("asin") }, ho.prototype.acos = function (t) { return po("acos") }, ho.prototype.atan = function (t) { return po("atan") }, ho.prototype.atan2 = function (t, e) { return po("atan2") }, ho.prototype.sinh = function (t) { return po("sinh") }, ho.prototype.cosh = function (t) { return po("cosh") }, ho.prototype.tanh = function (t) { return po("tanh") }, ho.prototype.asinh = function (t) { return po("asinh") }, ho.prototype.acosh = function (t) { return po("acosh") }, ho.prototype.atanh = function (t) { return po("atanh") }, ho.prototype.erf = function (t) { return po("erf") }, ho.prototype.step = function (t, e) { return po("step") }, ho.prototype.fusedConv2d = function (t) { return t.input, t.filter, t.convInfo, t.bias, t.activation, t.preluActivationWeights, po("fusedConv2d") }, ho.prototype.conv2d = function (t, e, n) { return po("conv2d") }, ho.prototype.conv2dDerInput = function (t, e, n) { return po("conv2dDerInput") }, ho.prototype.conv2dDerFilter = function (t, e, n) { return po("conv2dDerFilter") }, ho.prototype.fusedDepthwiseConv2D = function (t) { return t.input, t.filter, t.convInfo, t.bias, t.activation, t.preluActivationWeights, po("fusedDepthwiseConv2D") }, ho.prototype.depthwiseConv2D = function (t, e, n) { return po("depthwiseConv2D") }, ho.prototype.depthwiseConv2DDerInput = function (t, e, n) { return po("depthwiseConv2DDerInput") }, ho.prototype.depthwiseConv2DDerFilter = function (t, e, n) { return po("depthwiseConv2DDerFilter") }, ho.prototype.conv3d = function (t, e, n) { return po("conv3d") }, ho.prototype.conv3dDerInput = function (t, e, n) { return po("conv3dDerInput") }, ho.prototype.conv3dDerFilter = function (t, e, n) { return po("conv3dDerFilter") }, ho.prototype.maxPool = function (t, e) { return po("maxPool") }, ho.prototype.maxPoolBackprop = function (t, e, n, r) { return po("maxPoolBackprop") }, ho.prototype.avgPool = function (t, e) { return po("avgPool") }, ho.prototype.avgPoolBackprop = function (t, e, n) { return po("avgPoolBackprop") }, ho.prototype.avgPool3d = function (t, e) { return po("avgPool3d") }, ho.prototype.avgPool3dBackprop = function (t, e, n) { return po("avgPool3dBackprop") }, ho.prototype.maxPool3d = function (t, e) { return po("maxPool3d") }, ho.prototype.maxPool3dBackprop = function (t, e, n, r) { return po("maxPool3dBackprop") }, ho.prototype.reshape = function (t, e) { return po("reshape") }, ho.prototype.cast = function (t, e) { return po("cast") }, ho.prototype.tile = function (t, e) { return po("tile") }, ho.prototype.pad = function (t, e, n) { return po("pad") }, ho.prototype.transpose = function (t, e) { return po("transpose") }, ho.prototype.gather = function (t, e, n) { return po("gather") }, ho.prototype.gatherND = function (t, e) { return po("gatherND") }, ho.prototype.scatterND = function (t, e, n) { return po("scatterND") }, ho.prototype.batchToSpaceND = function (t, e, n) { return po("batchToSpaceND") }, ho.prototype.spaceToBatchND = function (t, e, n) { return po("spaceToBatchND") }, ho.prototype.resizeBilinear = function (t, e, n, r) { return po("resizeBilinear") }, ho.prototype.resizeBilinearBackprop = function (t, e, n) { return po("resizeBilinearBackprop") }, ho.prototype.resizeNearestNeighbor = function (t, e, n, r) { return po("resizeNearestNeighbor") }, ho.prototype.resizeNearestNeighborBackprop = function (t, e, n) { return po("resizeNearestNeighborBackprop") }, ho.prototype.batchNormalization = function (t, e, n, r, o, i) { return po("batchNormalization") }, ho.prototype.localResponseNormalization4D = function (t, e, n, r, o) { return po("localResponseNormalization4D") }, ho.prototype.LRNGrad = function (t, e, n, r, o, i, a) { return po("LRNGrad") }, ho.prototype.multinomial = function (t, e, n, r) { return po("multinomial") }, ho.prototype.oneHot = function (t, e, n, r) { return po("oneHot") }, ho.prototype.cumsum = function (t, e, n, r) { return po("cumsum") }, ho.prototype.nonMaxSuppression = function (t, e, n, r, o) { return po("nonMaxSuppression") }, ho.prototype.fft = function (t) { return po("fft") }, ho.prototype.ifft = function (t) { return po("ifft") }, ho.prototype.complex = function (t, e) { return po("complex") }, ho.prototype.real = function (t) { return po("real") }, ho.prototype.imag = function (t) { return po("imag") }, ho.prototype.cropAndResize = function (t, e, n, r, o, i) { return po("cropAndResize") }, ho.prototype.depthToSpace = function (t, e, n) { return po("depthToSpace") }, ho.prototype.split = function (t, e, n) { return po("split") }, ho.prototype.sparseToDense = function (t, e, n, r) { return po("sparseToDense") }, ho.prototype.diag = function (t) { return po("diag") }, ho.prototype.fill = function (t, e, n) { return po("fill") }, ho.prototype.onesLike = function (t) { return po("onesLike") }, ho.prototype.zerosLike = function (t) { return po("zerosLike") }, ho.prototype.linspace = function (t, e, n) { return po("linspace") }, ho.prototype.dispose = function () { return po("dispose") }, ho); function ho() { } function fo(t, e) { this.backend = t, this.dataMover = e, this.data = new WeakMap, this.dataIdsCount = 0 } function po(t) { throw new Error("'" + t + "' not yet implemented or not found in the registry. Did you forget to import the kernel?") } function vo(t, e) { for (var n = t.length, r = [], o = 0; o < n; o++) { var i = n - 1 - o, a = t[i] || 1; 1 < (e[e.length - 1 - o] || 1) && 1 === a && r.unshift(i) } return r } function mo(t, e) { for (var n = [], r = 0; r < e.length; r++) { var o = t[t.length - r - 1], i = e.length - r - 1, a = e[i]; (null == o || 1 === o && 1 < a) && n.unshift(i) } return n } function go(t, e) { for (var n = [], r = Math.max(t.length, e.length), o = 0; o < r; o++) { var i = t[t.length - o - 1]; null == i && (i = 1); var a = e[e.length - o - 1]; if (null == a && (a = 1), 1 === i) n.unshift(a); else if (1 === a) n.unshift(i); else { if (i !== a) throw Error("Operands could not be broadcast together with shapes " + t + " and " + e + "."); n.unshift(i) } } return n } function yo(t, e, n, r, o, i, a) { void 0 === a && (a = "channelsLast"); var s, u = Eo(e), c = u[0], l = u[1]; if ("channelsLast" === a) s = [c, l, t[3], t[3]]; else { if ("channelsFirst" !== a) throw new Error("Unknown dataFormat " + a); s = [c, l, t[1], t[1]] } return bo(t, s, n, r, o, i, !1, a) } function xo(t, e, n, r, o, i, a) { void 0 === a && (a = "NDHWC"); var s, u, c = _o(e), l = c[0], h = c[1], f = c[2]; if ("NDHWC" === a) u = "channelsLast", s = [l, h, f, t[4], t[4]]; else { if ("NCDHW" !== a) throw new Error("Unknown dataFormat " + a); u = "channelsFirst", s = [l, h, f, t[1], t[1]] } return wo(t, s, n, r, o, !1, u, i) } function bo(t, e, n, r, o, m, i, a) { void 0 === i && (i = !1), void 0 === a && (a = "channelsLast"); var s = [-1, -1, -1, -1], u = s[0], c = s[1], l = s[2], h = s[3]; if ("channelsLast" === a) u = t[0], c = t[1], l = t[2], h = t[3]; else { if ("channelsFirst" !== a) throw new Error("Unknown dataFormat " + a); u = t[0], h = t[1], c = t[2], l = t[3] } var f, p = e[0], d = e[1], v = e[3], g = Eo(n), y = g[0], x = g[1], b = Eo(r), w = b[0], C = b[1], E = Io(p, w), _ = Io(d, C), I = function (t, e, n, r, o, i, a) { var s, u, c; if ("number" == typeof t) { s = { top: t, bottom: t, left: t, right: t, type: 0 === t ? "VALID" : "NUMBER" }; var l = function (t, e, n, r, o) { null == r && (r = Co(t, e, n)); var i = t[1], a = Ro((t[0] - e + 2 * r) / n + 1, o); P(B(a), function () { return "The output # of rows (" + a + ") must be an integer. Change the stride and/or zero pad parameters" }); var s = Ro((i - e + 2 * r) / n + 1, o); return P(B(s), function () { return "The output # of columns (" + s + ") must be an integer. Change the stride and/or zero pad parameters" }), [a, s] }([e, n], i, r, t, m); u = l[0], c = l[1] } else if ("same" === t) { u = Math.ceil(e / r), c = Math.ceil(n / o); var h = Math.max(0, (u - 1) * r + i - e), f = Math.max(0, (c - 1) * o + a - n), p = Math.floor(h / 2), d = h - p, v = Math.floor(f / 2); s = { top: p, bottom: d, left: v, right: f - v, type: "SAME" } } else { if ("valid" !== t) throw Error("Unknown padding parameter: " + t); s = { top: 0, bottom: 0, left: 0, right: 0, type: "VALID" }, u = Math.ceil((e - i + 1) / r), c = Math.ceil((n - a + 1) / o) } return { padInfo: s, outHeight: u, outWidth: c } }(o, c, l, y, x, E, _), R = I.padInfo, k = I.outHeight, S = I.outWidth, D = i ? v * h : v; return "channelsFirst" === a ? f = [u, D, k, S] : "channelsLast" === a && (f = [u, k, S, D]), { batchSize: u, dataFormat: a, inHeight: c, inWidth: l, inChannels: h, outHeight: k, outWidth: S, outChannels: D, padInfo: R, strideHeight: y, strideWidth: x, filterHeight: p, filterWidth: d, effectiveFilterHeight: E, effectiveFilterWidth: _, dilationHeight: w, dilationWidth: C, inShape: t, outShape: f, filterShape: e } } function wo(t, e, n, r, o, i, a, E) { void 0 === i && (i = !1), void 0 === a && (a = "channelsLast"); var s = [-1, -1, -1, -1, -1], u = s[0], c = s[1], l = s[2], h = s[3], f = s[4]; if ("channelsLast" === a) u = t[0], c = t[1], l = t[2], h = t[3], f = t[4]; else { if ("channelsFirst" !== a) throw new Error("Unknown dataFormat " + a); u = t[0], f = t[1], c = t[2], l = t[3], h = t[4] } var p, d = e[0], v = e[1], m = e[2], g = e[4], y = _o(n), x = y[0], b = y[1], w = y[2], C = _o(r), _ = C[0], I = C[1], R = C[2], k = Io(d, _), S = Io(v, I), D = Io(m, R), A = function (t, e, n, r, o, i, a, s, u, c) { var l, h, f, p; if ("number" == typeof t) { l = { top: t, bottom: t, left: t, right: t, front: t, back: t, type: 0 === t ? "VALID" : "NUMBER" }; var d = function (t, e, n, r, o, i) { null == o && (o = Co(t, e, r)); var a = t[1], s = t[2], u = Ro((t[0] - e + 2 * o) / r + 1, i); P(B(u), function () { return "The output # of depths (" + u + ") must be an integer. Change the stride and/or zero pad parameters" }); var c = Ro((a - e + 2 * o) / r + 1, i); P(B(c), function () { return "The output # of rows (" + c + ") must be an integer. Change the stride and/or zero pad parameters" }); var l = Ro((s - e + 2 * o) / r + 1, i); return P(B(l), function () { return "The output # of columns (" + l + ") must be an integer. Change the stride and/or zero pad parameters" }), [u, c, l, 1] }([e, n, r, 1], s, 0, o, t, E); h = d[0], f = d[1], p = d[2] } else if ("same" === t) { var v = ((h = Math.ceil(e / o)) - 1) * o + s - e, m = ((f = Math.ceil(n / i)) - 1) * i + u - n, g = ((p = Math.ceil(r / a)) - 1) * a + c - r, y = Math.floor(v / 2), x = v - y, b = Math.floor(m / 2), w = m - b, C = Math.floor(g / 2); l = { top: b, bottom: w, left: C, right: g - C, front: y, back: x, type: "SAME" } } else { if ("valid" !== t) throw Error("Unknown padding parameter: " + t); l = { top: 0, bottom: 0, left: 0, right: 0, front: 0, back: 0, type: "VALID" }, h = Math.ceil((e - s + 1) / o), f = Math.ceil((n - u + 1) / i), p = Math.ceil((r - c + 1) / a) } return { padInfo: l, outDepth: h, outHeight: f, outWidth: p } }(o, c, l, h, x, b, w, k, S, D), T = A.padInfo, N = A.outDepth, F = A.outHeight, M = A.outWidth, O = i ? g * f : g; return "channelsFirst" === a ? p = [u, O, N, F, M] : "channelsLast" === a && (p = [u, N, F, M, O]), { batchSize: u, dataFormat: a, inDepth: c, inHeight: l, inWidth: h, inChannels: f, outDepth: N, outHeight: F, outWidth: M, outChannels: O, padInfo: T, strideDepth: x, strideHeight: b, strideWidth: w, filterDepth: d, filterHeight: v, filterWidth: m, effectiveFilterDepth: k, effectiveFilterHeight: S, effectiveFilterWidth: D, dilationDepth: _, dilationHeight: I, dilationWidth: R, inShape: t, outShape: p, filterShape: e } } function Co(t, e, n, r) { void 0 === r && (r = 1); var o = Io(e, r); return Math.floor((t[0] * (n - 1) - n + o) / 2) } function Eo(t) { return "number" == typeof t ? [t, t, t] : 2 === t.length ? [t[0], t[1], 1] : t } function _o(t) { return "number" == typeof t ? [t, t, t] : t } function Io(t, e) { return e <= 1 ? t : t + (t - 1) * (e - 1) } function Ro(t, e) { if (!e) return t; switch (e) { case "round": return Math.round(t); case "ceil": return Math.ceil(t); case "floor": return Math.floor(t); default: throw new Error("Unknown roundingMode " + e) } } function ko(t) { var e = Eo(t), n = e[0], r = e[1], o = e[2]; return 1 === n && 1 === r && 1 === o } function So(t, e) { return ko(t) || ko(e) } function Do(t) { if ("NHWC" === t) return "channelsLast"; if ("NCHW" === t) return "channelsFirst"; throw new Error("Unknown dataFormat " + t) } function Ao(t, e, n) { if ("complex64" === e) { if ("complex64" === t.dtype) return t.clone(); var r = Pn(t.shape), o = t.toFloat(), i = n.complex(o, r); return r.dispose(), o.dispose(), i } if (!W(t.dtype, e)) return Kt.makeTensorFromDataId(t.dataId, t.shape, e); if ("complex64" === t.dtype) { var a = n.real(t); return i = a.cast(e), a.dispose(), i } if ("int32" === e) return n.int(t); if ("bool" !== e) throw new Error("Error in Cast: failed to cast " + t.dtype + " to " + e); var s = kn(0, t.dtype); return i = n.notEqual(t, s), s.dispose(), i } function To(t, e) { return Kt.makeTensorFromDataId(t.dataId, e, t.dtype) } function No(t, e, n) { var r = (e - t) / (n - 1), o = Z(n, "float32"); o[0] = t; for (var i = 1; i < o.length; i++)o[i] = o[i - 1] + r; return Sn(o, "float32") } var Fo = Object.freeze({ castTensor: Ao, reshapeTensor: To, linspaceImpl: No, upcastType: Pt, axesAreInnerMostDims: hn, combineLocations: fn, computeOutAndReduceShapes: pn, expandShapeToKeepDim: dn, assertAxesAreInnerMostDims: vn, getAxesPermutation: mn, getUndoAxesPermutation: gn, getInnerMostAxes: yn, getBroadcastDims: vo, getReductionAxes: mo, assertAndGetBroadcastShape: go, assertParamsConsistent: xn, computeOutShape: bn, computePool2DInfo: yo, computePool3DInfo: xo, computeConv2DInfo: bo, computeConv3DInfo: wo, computeDefaultPad: Co, tupleValuesAreOne: ko, eitherStridesOrDilationsAreOne: So, convertConv2DDataFormat: Do, PARALLELIZE_THRESHOLD: 30, computeOptimalWindowSize: qr }); function Mo(t, e) { if (t.length !== e.length) throw new Error("Cannot merge real and imag arrays of different lengths. real:" + t.length + ", imag: " + e.length + "."); for (var n = new Float32Array(2 * t.length), r = 0; r < n.length; r += 2)n[r] = t[r / 2], n[r + 1] = e[r / 2]; return n } function Oo(t, e) { return { real: t[2 * e], imag: t[2 * e + 1] } } function Po(t, e) { return e < t ? 1 : t < e ? -1 : 0 } function Bo(t, e, n, r, o) { return Wo(t, e, n, r, o, 0).selectedIndices } function Lo(t, e, n, r, o, i) { var a = Wo(t, e, n, r, o, i); return a.numValidOutputs.dispose(), { selectedIndices: a.selectedIndices, selectedScores: a.selectedScores } } function Wo(t, e, n, r, o, i, a, s) { void 0 === s && (s = !1); for (var u = Array.from(e).map(function (t, e) { return { score: t, boxIndex: e, suppressBeginIndex: 0 } }).filter(function (t) { return t.score > o }).sort(Uo), c = 0 < i ? -.5 / i : 0, l = [], h = []; l.length < n && 0 < u.length;) { var f = u.pop(), p = f.score, d = f.boxIndex, v = f.suppressBeginIndex; if (p < o) break; for (var m = !1, g = l.length - 1; v <= g; --g) { var y = zo(t, d, l[g]); if (r <= y) { m = !0; break } if (f.score = f.score * (E = r, _ = c, I = y, void 0, R = Math.exp(_ * I * I), I <= E ? R : 0), f.score <= o) break } f.suppressBeginIndex = l.length, m || (f.score === p ? (l.push(d), h.push(f.score)) : f.score > o && (void 0, w = function (t, e, n) { for (var r = 0, o = t.length, i = 0, a = !1; r < o;) { var s = n(e, t[i = r + (o - r >>> 1)]); 0 < s ? r = i + 1 : (o = i, a = !s) } return a ? r : -r - 1 }(x = u, b = f, Uo || Po), C = w < 0 ? -(w + 1) : w, x.splice(C, 0, b))) } var x, b, w, C, E, _, I, R, k = l.length; return s && (l.fill(0, k), h.fill(0, k)), { selectedIndices: Sn(l, "int32"), selectedScores: Sn(h, "float32"), numValidOutputs: kn(k, "int32") } } function zo(t, e, n) { var r = t.subarray(4 * e, 4 * e + 4), o = t.subarray(4 * n, 4 * n + 4), i = Math.min(r[0], r[2]), a = Math.min(r[1], r[3]), s = Math.max(r[0], r[2]), u = Math.max(r[1], r[3]), c = Math.min(o[0], o[2]), l = Math.min(o[1], o[3]), h = Math.max(o[0], o[2]), f = Math.max(o[1], o[3]), p = (s - i) * (u - a), d = (h - c) * (f - l); if (p <= 0 || d <= 0) return 0; var v = Math.max(i, c), m = Math.max(a, l), g = Math.min(s, h), y = Math.min(u, f), x = Math.max(g - v, 0) * Math.max(y - m, 0); return x / (p + d - x) } function Uo(t, e) { return t.score - e.score || t.score === e.score && e.boxIndex - t.boxIndex } function Vo(n, t, r) { var o = new Array(n.rank).fill(0), i = n.shape.slice(); return t.map(function (t) { i[r] = t; var e = n.slice(o, i); return o[r] += t, e }) } function Go(t, e) { for (var n = new Array(t.rank), r = 0; r < n.length; r++)n[r] = t.shape[r] * e[r]; var o = cr(n, t.dtype); for (r = 0; r < o.values.length; ++r) { for (var i = o.indexToLoc(r), a = new Array(t.rank), s = 0; s < a.length; s++)a[s] = i[s] % t.shape[s]; var u = t.locToIndex(a); o.values[r] = t.values[u] } return o.toTensor() } function Ho(t, e, n, r) { for (var o = e[e.length - 1], i = [t.length / o, o], a = i[0], s = i[1], u = N(n, a * r), c = N("int32", a * r), l = 0; l < a; l++) { for (var h = l * s, f = t.subarray(h, h + s), p = [], d = 0; d < f.length; d++)p.push({ value: f[d], index: d }); p.sort(function (t, e) { return e.value - t.value }); var v = l * r, m = u.subarray(v, v + r), g = c.subarray(v, v + r); for (d = 0; d < r; d++)m[d] = p[d].value, g[d] = p[d].index } var y = e.slice(); return y[y.length - 1] = r, [In(u, y, n), In(c, y, "int32")] } function qo(t, e) { for (var n = [], r = 0; r < e.length; r++)e[r] && n.push(r); var o = cr(t, "int32"), i = cr([n.length, t.length], "int32"); for (r = 0; r < n.length; r++) { var a = o.indexToLoc(n[r]), s = r * t.length; i.values.set(a, s) } return i.toTensor() } function jo(t, e) { this.outputShape = [], this.outputShape = t, this.variableNames = e.map(function (t, e) { return "T" + e }); var n = []; this.variableNames.forEach(function (t) { n.push("float v" + t + " = get" + t + "AtOutCoords();") }); var r = this.variableNames.map(function (t) { return "v" + t }).join(" + "); this.userCode = "\n      void main() {\n        " + n.join("\n        ") + "\n\n        float result = " + r + ";\n        setOutput(result);\n      }\n    " } function Ko(t, e) { this.outputShape = [], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t, this.variableNames = e.map(function (t, e) { return "T" + e }); var n = []; this.variableNames.forEach(function (t) { n.push("vec4 v" + t + " = get" + t + "AtOutCoords();") }); var r = this.variableNames.map(function (t) { return "v" + t }).join(" + "); this.userCode = "\n      void main() {\n        " + n.join("\n        ") + "\n\n        vec4 result = " + r + ";\n        setOutput(result);\n      }\n    " } function Xo(t, e, n) { this.variableNames = ["A"]; var r = t.windowSize, o = t.batchSize, i = t.inSize, a = Math.ceil(i / r); n || this.variableNames.push("bestIndicesA"), this.outputShape = [o, a]; var s = "max" === e ? ">" : "<", u = n ? "inOffset + i;" : "round(getBestIndicesA(batch, inOffset + i));"; this.userCode = "\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * " + r + ";\n\n        int bestIndex = inOffset;\n        float bestValue = getA(batch, bestIndex);\n\n        for (int i = 0; i < " + r + "; i++) {\n          int inIdx = " + u + ";\n          float candidate = getA(batch, inIdx);\n          if (candidate " + s + " bestValue) {\n            bestValue = candidate;\n            bestIndex = inIdx;\n          }\n        }\n        setOutput(float(bestIndex));\n      }\n    " } function Yo(e, t) { return ["x", "y", "z", "w", "u", "v"].slice(0, t).map(function (t) { return e + "." + t }) } function $o(t, e) { return 1 === e ? [t] : Yo(t, e) } function Jo() { var t, e, n, r, o, i, a, s, u, c; return c = 2 === _().getNumber("WEBGL_VERSION") ? (t = "#version 300 es", n = "out", r = e = "in", o = "texture", i = "outputColor", a = "out vec4 outputColor;", s = "\n      bool isnan_custom(float val) {\n        return (val > 0.0 || val < 0.0) ? false : val != 0.0;\n      }\n\n      bvec4 isnan_custom(vec4 val) {\n        return bvec4(isnan_custom(val.x),\n          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));\n      }\n\n      #define isnan(value) isnan_custom(value)\n    ", u = "", "\n      #define round(value) newRound(value)\n      int newRound(float value) {\n        return int(floor(value + 0.5));\n      }\n\n      ivec4 newRound(vec4 value) {\n        return ivec4(floor(value + vec4(0.5)));\n      }\n    ") : (e = "attribute", r = n = "varying", o = "texture2D", i = "gl_FragColor", a = t = "", s = "\n      #define isnan(value) isnan_custom(value)\n      bool isnan_custom(float val) {\n        return (val > 0. || val < 1. || val == 0.) ? false : true;\n      }\n      bvec4 isnan_custom(vec4 val) {\n        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));\n      }\n    ", u = "\n      uniform float INFINITY;\n\n      bool isinf(float val) {\n        return abs(val) == INFINITY;\n      }\n      bvec4 isinf(vec4 val) {\n        return equal(abs(val), vec4(INFINITY));\n      }\n    ", "\n      int round(float value) {\n        return int(floor(value + 0.5));\n      }\n\n      ivec4 round(vec4 value) {\n        return ivec4(floor(value + vec4(0.5)));\n      }\n    "), { version: t, attribute: e, varyingVs: n, varyingFs: r, texture2D: o, output: i, defineOutput: a, defineSpecialNaN: s, defineSpecialInf: u, defineRound: c } } function Qo(n, t, r) { void 0 === r && (r = "index"); var o = Y(t); return o.map(function (t, e) { return "int " + n[e] + " = " + r + " / " + t + "; " + (e === o.length - 1 ? "int " + n[e + 1] + " = " + r + " - " + n[e] + " * " + t : "index -= " + n[e] + " * " + t) + ";" }).join("") } function Zo(t) { var e = Y(t).map(function (t) { return t.toString() }); return "\n  int getFlatIndex(ivec3 coords) {\n    return coords.x * " + e[0] + " + coords.y * " + e[1] + " + coords.z;\n  }\n" } var ti = "\n  const float FLOAT_MAX = 1.70141184e38;\n  const float FLOAT_MIN = 1.17549435e-38;\n\n  lowp vec4 encode_float(highp float v) {\n    if (isnan(v)) {\n      return vec4(255, 255, 255, 255);\n    }\n\n    highp float av = abs(v);\n\n    if(av < FLOAT_MIN) {\n      return vec4(0.0, 0.0, 0.0, 0.0);\n    } else if(v > FLOAT_MAX) {\n      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\n    } else if(v < -FLOAT_MAX) {\n      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;\n    }\n\n    highp vec4 c = vec4(0,0,0,0);\n\n    highp float e = floor(log2(av));\n    highp float m = exp2(fract(log2(av))) - 1.0;\n\n    c[2] = floor(128.0 * m);\n    m -= c[2] / 128.0;\n    c[1] = floor(32768.0 * m);\n    m -= c[1] / 32768.0;\n    c[0] = floor(8388608.0 * m);\n\n    highp float ebias = e + 127.0;\n    c[3] = floor(ebias / 2.0);\n    ebias -= c[3] * 2.0;\n    c[2] += floor(ebias) * 128.0;\n\n    c[3] += 128.0 * step(0.0, -v);\n\n    return c / 255.0;\n  }\n"; function ei(t, e, n, r) { var o = []; t.forEach(function (t) { var e = L(t.shapeInfo.logicalShape); t.shapeInfo.isUniform ? o.push("uniform float " + t.name + (1 < e ? "[" + e + "]" : "") + ";") : (o.push("uniform sampler2D " + t.name + ";"), o.push("uniform int offset" + t.name + ";")) }); var i, a, s, u = o.join("\n"), c = t.map(function (t) { return function (t, e, n) { void 0 === n && (n = !1); var r = ""; r += n ? function p(t) { var e, n, r; switch (t.shapeInfo.logicalShape.length) { case 0: return e = t.name, n = "get" + e.charAt(0).toUpperCase() + e.slice(1), r = Jo(), "\n    vec4 " + n + "() {\n      return " + r.texture2D + "(" + e + ", halfCR);\n    }\n  "; case 1: return function (t) { var e = t.name, n = "get" + e.charAt(0).toUpperCase() + e.slice(1), r = t.shapeInfo.texShape, o = [Math.ceil(r[0] / 2), Math.ceil(r[1] / 2)], i = Jo(); return "\n    vec4 " + n + "(int index) {\n      vec2 uv = packedUVfrom1D(\n        " + o[0] + ", " + o[1] + ", index);\n      return " + i.texture2D + "(" + e + ", uv);\n    }\n  " }(t); case 2: return function (t) { var e = t.shapeInfo.logicalShape, n = t.name, r = "get" + n.charAt(0).toUpperCase() + n.slice(1), o = t.shapeInfo.texShape, i = o[0], a = o[1], s = Jo(); if (null != o && A(e, o)) return "\n      vec4 " + r + "(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(" + a + ".0, " + i + ".0);\n\n        return " + s.texture2D + "(" + n + ", uv);\n      }\n    "; var u = [Math.ceil(o[0] / 2), Math.ceil(o[1] / 2)], c = Math.ceil(e[1] / 2); return "\n    vec4 " + r + "(int row, int col) {\n      vec2 uv = packedUVfrom2D(" + c + ", " + u[0] + ", " + u[1] + ", row, col);\n      return " + s.texture2D + "(" + n + ", uv);\n    }\n  " }(t); case 3: return function (t) { var e = t.shapeInfo.logicalShape, n = t.name, r = "get" + n.charAt(0).toUpperCase() + n.slice(1), o = t.shapeInfo.texShape, i = [Math.ceil(o[0] / 2), Math.ceil(o[1] / 2)]; if (1 === e[0]) { var a = e.slice(1), s = ii(t, a); return "\n        " + p(s) + "\n        vec4 " + r + "(int b, int row, int col) {\n          return " + r + "(" + ai(["b", "row", "col"], [1, 2]) + ");\n        }\n      " } var u = i[0], c = i[1], l = Math.ceil(e[2] / 2), h = l * Math.ceil(e[1] / 2), f = Jo(); return "\n    vec4 " + r + "(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        " + u + ", " + c + ", " + h + ", " + l + ", b, row, col);\n      return " + f.texture2D + "(" + n + ", uv);\n    }\n  " }(t); default: return function (t) { for (var e = t.shapeInfo.logicalShape, n = e.length, r = t.name, o = "get" + r.charAt(0).toUpperCase() + r.slice(1), i = t.shapeInfo.texShape, a = [Math.ceil(i[0] / 2), Math.ceil(i[1] / 2)], s = a[0], u = a[1], c = Math.ceil(e[n - 1] / 2), l = c * Math.ceil(e[n - 2] / 2), h = "int b, int row, int col", f = "b * " + l + " + (row / 2) * " + c + " + (col / 2)", p = 2; p < n - 1; p++)h = "int b" + p + ", " + h, l *= e[n - p - 1], f = "b" + p + " * " + l + " + " + f; var d = Jo(); return "\n    vec4 " + o + "(" + h + ") {\n      int index = " + f + ";\n      int texR = index / " + u + ";\n      int texC = index - texR * " + u + ";\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(" + u + ", " + s + ");\n      return " + d.texture2D + "(" + r + ", uv);\n    }\n  " }(t) } }(t) : function y(t) { var e = t.shapeInfo.logicalShape; switch (e.length) { case 0: return function (t) { var e = t.name, n = "get" + e.charAt(0).toUpperCase() + e.slice(1); if (t.shapeInfo.isUniform) return "float " + n + "() {return " + e + ";}"; var r = t.shapeInfo.texShape, o = r[0], i = r[1]; if (1 === o && 1 === i) return "\n      float " + n + "() {\n        return sampleTexture(" + e + ", halfCR);\n      }\n    "; var a = t.shapeInfo.texShape, s = a[0], u = a[1], c = ni(e); return "\n    float " + n + "() {\n      vec2 uv = uvFromFlat(" + s + ", " + u + ", " + c + ");\n      return sampleTexture(" + e + ", uv);\n    }\n  " }(t); case 1: return function (t) { var e = t.name, n = "get" + e.charAt(0).toUpperCase() + e.slice(1); if (t.shapeInfo.isUniform) return "\n      float " + n + "(int index) {\n        " + ri(t) + "\n      }\n    "; var r = t.shapeInfo.texShape, o = r[0], i = r[1]; if (1 === i && 1 === o) return "\n      float " + n + "(int index) {\n        return sampleTexture(" + e + ", halfCR);\n      }\n    "; var a = ni(e); return 1 === i ? "\n      float " + n + "(int index) {\n        vec2 uv = vec2(0.5, (float(index + " + a + ") + 0.5) / " + o + ".0);\n        return sampleTexture(" + e + ", uv);\n      }\n    " : 1 === o ? "\n      float " + n + "(int index) {\n        vec2 uv = vec2((float(index + " + a + ") + 0.5) / " + i + ".0, 0.5);\n        return sampleTexture(" + e + ", uv);\n      }\n    " : "\n    float " + n + "(int index) {\n      vec2 uv = uvFromFlat(" + o + ", " + i + ", index + " + a + ");\n      return sampleTexture(" + e + ", uv);\n    }\n  " }(t); case 2: return function (t) { var e = t.shapeInfo.logicalShape, n = t.name, r = "get" + n.charAt(0).toUpperCase() + n.slice(1), o = t.shapeInfo.texShape; if (null != o && A(e, o)) { var i = o[0], a = o[1]; return "\n    float " + r + "(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(" + a + ".0, " + i + ".0);\n      return sampleTexture(" + n + ", uv);\n    }\n  " } var s = T(e), u = s.newShape, c = s.keptDims, l = u; if (l.length < e.length) { var h = ii(t, l); return "\n      " + y(h) + "\n      float " + r + "(int row, int col) {\n        return " + r + "(" + ai(["row", "col"], c) + ");\n      }\n    " } if (t.shapeInfo.isUniform) return "\n      float " + r + "(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2(" + e[1] + ", 1)));\n        " + ri(t) + "\n      }\n    "; var f = o[0], p = o[1], d = ni(n); return 1 === p ? "\n    float " + r + "(int row, int col) {\n      float index = dot(vec3(row, col, " + d + "), vec3(" + e[1] + ", 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / " + f + ".0);\n      return sampleTexture(" + n + ", uv);\n    }\n  " : 1 === f ? "\n    float " + r + "(int row, int col) {\n      float index = dot(vec3(row, col, " + d + "), vec3(" + e[1] + ", 1, 1));\n      vec2 uv = vec2((index + 0.5) / " + p + ".0, 0.5);\n      return sampleTexture(" + n + ", uv);\n    }\n  " : "\n  float " + r + "(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * " + e[1] + " + col + " + d + ";\n    vec2 uv = uvFromFlat(" + f + ", " + p + ", index);\n    return sampleTexture(" + n + ", uv);\n  }\n" }(t); case 3: return function (t) { var e = t.shapeInfo.logicalShape, n = t.name, r = "get" + n.charAt(0).toUpperCase() + n.slice(1), o = e[1] * e[2], i = e[2], a = T(e), s = a.newShape, u = a.keptDims, c = s; if (c.length < e.length) { var l = ii(t, c); return "\n        " + y(l) + "\n        float " + r + "(int row, int col, int depth) {\n          return " + r + "(" + ai(["row", "col", "depth"], u) + ");\n        }\n      " } if (t.shapeInfo.isUniform) return "\n      float " + r + "(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3(" + o + ", " + i + ", 1)));\n        " + ri(t) + "\n      }\n    "; var h = t.shapeInfo.texShape, f = h[0], p = h[1], d = t.shapeInfo.flatOffset; if (p === o && null == d) return "\n        float " + r + "(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2(" + i + ", 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2(" + p + ".0, " + f + ".0);\n          return sampleTexture(" + n + ", uv);\n        }\n      "; if (p === i && null == d) return "\n    float " + r + "(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2(" + e[1] + ", 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(" + p + ".0, " + f + ".0);\n      return sampleTexture(" + n + ", uv);\n    }\n  "; var v = ni(n); return "\n      float " + r + "(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * " + o + " + col * " + i + " + depth + " + v + ";\n        vec2 uv = uvFromFlat(" + f + ", " + p + ", index);\n        return sampleTexture(" + n + ", uv);\n      }\n  " }(t); case 4: return function (t) { var e = t.shapeInfo.logicalShape, n = t.name, r = "get" + n.charAt(0).toUpperCase() + n.slice(1), o = e[3], i = e[2] * o, a = e[1] * i, s = T(e), u = s.newShape, c = s.keptDims; if (u.length < e.length) { var l = ii(t, u); return "\n      " + y(l) + "\n      float " + r + "(int row, int col, int depth, int depth2) {\n        return " + r + "(" + ai(["row", "col", "depth", "depth2"], c) + ");\n      }\n    " } if (t.shapeInfo.isUniform) return "\n      float " + r + "(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4(" + a + ", " + i + ", " + o + ", 1)));\n        " + ri(t) + "\n      }\n    "; var h = t.shapeInfo.flatOffset, f = t.shapeInfo.texShape, p = f[0], d = f[1]; if (d === a && null == h) return "\n      float " + r + "(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3(" + i + ", " + o + ", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(" + d + ".0, " + p + ".0);\n        return sampleTexture(" + n + ", uv);\n      }\n    "; if (d === o && null == h) return "\n      float " + r + "(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(" + e[1] * e[2] + ", " + e[2] + ", 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(" + d + ".0, " + p + ".0);\n        return sampleTexture(" + n + ", uv);\n      }\n    "; var v = ni(n); return "\n    float " + r + "(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * " + a + " + col * " + i + " +\n          depth * " + o + " + depth2;\n      vec2 uv = uvFromFlat(" + p + ", " + d + ", index + " + v + ");\n      return sampleTexture(" + n + ", uv);\n    }\n  " }(t); case 5: return function (t) { var e = t.shapeInfo.logicalShape, n = t.name, r = "get" + n.charAt(0).toUpperCase() + n.slice(1), o = e[4], i = e[3] * o, a = e[2] * i, s = e[1] * a, u = T(e), c = u.newShape, l = u.keptDims; if (c.length < e.length) { var h = ii(t, c); return "\n      " + y(h) + "\n      float " + r + "(int row, int col, int depth, int depth2, int depth3) {\n        return " + r + "(" + ai(["row", "col", "depth", "depth2", "depth3"], l) + ");\n      }\n    " } if (t.shapeInfo.isUniform) return "\n      float " + r + "(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4(" + s + ", " + a + ", " + i + ", " + o + ")) +\n          depth3;\n        " + ri(t) + "\n      }\n    "; var f = t.shapeInfo.flatOffset, p = t.shapeInfo.texShape, d = p[0], v = p[1]; if (v === s && null == f) return "\n      float " + r + "(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4(" + a + ", " + i + ", " + o + ", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(" + v + ".0, " + d + ".0);\n        return sampleTexture(" + n + ", uv);\n      }\n    "; if (v === o && null == f) return "\n      float " + r + "(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4(" + e[1] * e[2] * e[3] + ",\n               " + e[2] * e[3] + ", " + e[3] + ", 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(" + v + ".0, " + d + ".0);\n        return sampleTexture(" + n + ", uv);\n      }\n    "; var m = ni(n); return "\n    float " + r + "(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * " + s + " + col * " + a + " + depth * " + i + " +\n          depth2 * " + o + " + depth3 + " + m + ";\n      vec2 uv = uvFromFlat(" + d + ", " + v + ", index);\n      return sampleTexture(" + n + ", uv);\n    }\n  " }(t); case 6: return function (t) { var e = t.shapeInfo.logicalShape, n = t.name, r = "get" + n.charAt(0).toUpperCase() + n.slice(1), o = T(e), i = o.newShape, a = o.keptDims; if (i.length < e.length) { var s = ii(t, i); return "\n      " + y(s) + "\n      float " + r + "(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return " + r + "(" + ai(["row", "col", "depth", "depth2", "depth3", "depth4"], a) + ");\n      }\n    " } var u = e[5], c = e[4] * u, l = e[3] * c, h = e[2] * l, f = e[1] * h; if (t.shapeInfo.isUniform) return "\n      float " + r + "(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4(" + f + ", " + h + ", " + l + ", " + c + ")) +\n          dot(\n            vec2(depth3, depth4),\n            vec2(" + u + ", 1)));\n        " + ri(t) + "\n      }\n    "; var p = t.shapeInfo.flatOffset, d = t.shapeInfo.texShape, v = d[0], m = d[1]; if (m === f && null == p) return "\n      float " + r + "(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4(" + h + ", " + l + ", " + c + ", " + u + ")) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(" + m + ".0, " + v + ".0);\n        return sampleTexture(" + n + ", uv);\n      }\n    "; if (m === u && null == p) return "\n      float " + r + "(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4(" + e[1] * e[2] * e[3] * e[4] + ",\n               " + e[2] * e[3] * e[4] + ",\n               " + e[3] * e[4] + ",\n               " + e[4] + ")) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(" + m + ".0, " + v + ".0);\n        return sampleTexture(" + n + ", uv);\n      }\n    "; var g = ni(n); return "\n    float " + r + "(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * " + f + " + col * " + h + " + depth * " + l + " +\n          depth2 * " + c + " + depth3 * " + u + " + depth4 + " + g + ";\n      vec2 uv = uvFromFlat(" + v + ", " + m + ", index);\n      return sampleTexture(" + n + ", uv);\n    }\n  " }(t); default: throw new Error(e.length + "-D input sampling is not yet supported") } }(t); var o = t.shapeInfo.logicalShape, i = e.logicalShape; return o.length <= i.length && (r += n ? function (t, e) { var n, r = t.name, o = r.charAt(0).toUpperCase() + r.slice(1), i = "get" + o + "AtOutCoords", a = t.shapeInfo.logicalShape.length, s = e.logicalShape.length, u = vo(t.shapeInfo.logicalShape, e.logicalShape), c = oi(s), l = s - a, h = ["x", "y", "z", "w", "u", "v"]; n = 0 === a ? "" : s < 2 && 1 <= u.length ? "coords = 0;" : u.map(function (t) { return "coords." + h[t + l] + " = 0;" }).join("\n"); var f; f = s < 2 && 0 < a ? "coords" : t.shapeInfo.logicalShape.map(function (t, e) { return "coords." + h[e + l] }).join(", "); var p = "return outputValue;", d = 1 === L(t.shapeInfo.logicalShape), v = 1 === L(e.logicalShape); if (1 !== a || d || v) { if (d && !v) p = 1 === s ? "\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      " : "\n        return vec4(outputValue.x);\n      "; else if (u.length) { var m = a - 2, g = a - 1; -1 < u.indexOf(m) && -1 < u.indexOf(g) ? p = "return vec4(outputValue.x);" : -1 < u.indexOf(m) ? p = "return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);" : -1 < u.indexOf(g) && (p = "return vec4(outputValue.xx, outputValue.zz);") } } else p = "\n      return vec4(outputValue.xy, outputValue.xy);\n    "; return "\n    vec4 " + i + "() {\n      " + c + " coords = getOutputCoords();\n      " + n + "\n      vec4 outputValue = get" + o + "(" + f + ");\n      " + p + "\n    }\n  " }(t, e) : function (t, e) { var n = t.name, r = n.charAt(0).toUpperCase() + n.slice(1), o = "get" + r + "AtOutCoords", i = e.texShape, a = t.shapeInfo.texShape, s = t.shapeInfo.logicalShape.length, u = e.logicalShape.length; if (!t.shapeInfo.isUniform && s === u && null == t.shapeInfo.flatOffset && A(a, i)) return "\n      float " + o + "() {\n        return sampleTexture(" + n + ", resultUV);\n      }\n    "; var c = oi(u), l = vo(t.shapeInfo.logicalShape, e.logicalShape), h = u - s, f = ["x", "y", "z", "w", "u", "v"]; return "\n    float " + o + "() {\n      " + c + " coords = getOutputCoords();\n      " + (0 === s ? "" : u < 2 && 1 <= l.length ? "coords = 0;" : l.map(function (t) { return "coords." + f[t + h] + " = 0;" }).join("\n")) + "\n      return get" + r + "(" + (u < 2 && 0 < s ? "coords" : t.shapeInfo.logicalShape.map(function (t, e) { return "coords." + f[e + h] }).join(", ")) + ");\n    }\n  " }(t, e)), r }(t, e, r) }).join("\n"), l = e.texShape, h = Jo(), f = "\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return " + h.texture2D + "(textureSampler, uv).r;\n    }\n  ", p = (s = h).version + "\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    " + s.varyingFs + " vec2 resultUV;\n    " + s.defineOutput + "\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    " + s.defineSpecialNaN + "\n    " + s.defineSpecialInf + "\n    " + s.defineRound + "\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    \nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n    \nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n    \nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n  "; return a = e.isPacked ? (i = function (t, e) { switch (t.length) { case 0: return "\n    int getOutputCoords() {\n      return 0;\n    }\n  "; case 1: return n = e, 1 === (r = [Math.ceil(n[0] / 2), Math.ceil(n[1] / 2)])[0] ? "\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * " + r[1] + ".0);\n      }\n    " : 1 === r[1] ? "\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * " + r[0] + ".0);\n      }\n    " : "\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + r[0] + ", " + r[1] + "));\n      return 2 * (resTexRC.x * " + r[1] + " + resTexRC.y);\n    }\n  "; case 2: return function (t, e) { var n = [Math.ceil(e[0] / 2), Math.ceil(e[1] / 2)]; if (A(t, e)) return "\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2(" + n[0] + ", " + n[1] + "));\n      }\n    "; var r = Math.ceil(t[1] / 2); return "\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + n[0] + ", " + n[1] + "));\n\n      int index = resTexRC.x * " + n[1] + " + resTexRC.y;\n      int r = 2 * (index / " + r + ");\n      int c = imod(index, " + r + ") * 2;\n\n      return ivec2(r, c);\n    }\n  " }(t, e); case 3: return o = t, i = e, a = [Math.ceil(i[0] / 2), Math.ceil(i[1] / 2)], u = (s = Math.ceil(o[2] / 2)) * Math.ceil(o[1] / 2), "\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + a[0] + ", " + a[1] + "));\n      int index = resTexRC.x * " + a[1] + " + resTexRC.y;\n\n      int b = index / " + u + ";\n      index -= b * " + u + ";\n\n      int r = 2 * (index / " + s + ");\n      int c = imod(index, " + s + ") * 2;\n\n      return ivec3(b, r, c);\n    }\n  "; default: return function (t, e) { for (var n = [Math.ceil(e[0] / 2), Math.ceil(e[1] / 2)], r = Math.ceil(t[t.length - 1] / 2), o = r * Math.ceil(t[t.length - 2] / 2), i = o, a = "", s = "b, r, c", u = 2; u < t.length - 1; u++)a = "\n      int b" + u + " = index / " + (i *= t[t.length - u - 1]) + ";\n      index -= b" + u + " * " + i + ";\n    " + a, s = "b" + u + ", " + s; return "\n    ivec" + t.length + " getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + n[0] + ", " + n[1] + "));\n      int index = resTexRC.x * " + n[1] + " + resTexRC.y;\n\n      " + a + "\n\n      int b = index / " + o + ";\n      index -= b * " + o + ";\n\n      int r = 2 * (index / " + r + ");\n      int c = imod(index, " + r + ") * 2;\n\n      return ivec" + t.length + "(" + s + ");\n    }\n  " }(t, e) }var n, r, o, i, a, s, u }(e.logicalShape, l), "\n    void setOutput(vec4 val) {\n      " + h.output + " = val;\n    }\n  ") : (i = function (t, e) { switch (t.length) { case 0: return "\n    int getOutputCoords() {\n      return 0;\n    }\n  "; case 1: return 1 === (l = e)[0] ? "\n      int getOutputCoords() {\n        return int(resultUV.x * " + l[1] + ".0);\n      }\n    " : 1 === l[1] ? "\n      int getOutputCoords() {\n        return int(resultUV.y * " + l[0] + ".0);\n      }\n    " : "\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + l[0] + ", " + l[1] + "));\n      return resTexRC.x * " + l[1] + " + resTexRC.y;\n    }\n  "; case 2: return A(u = t, c = e) ? "\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(" + c[0] + ", " + c[1] + "));\n      }\n    " : 1 === u[1] ? "\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(" + c[0] + ", " + c[1] + "));\n        int index = resTexRC.x * " + c[1] + " + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    " : 1 === u[0] ? "\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(" + c[0] + ", " + c[1] + "));\n        int index = resTexRC.x * " + c[1] + " + resTexRC.y;\n        return ivec2(0, index);\n      }\n    " : "\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + c[0] + ", " + c[1] + "));\n      int index = resTexRC.x * " + c[1] + " + resTexRC.y;\n      int r = index / " + u[1] + ";\n      int c = index - r * " + u[1] + ";\n      return ivec2(r, c);\n    }\n  "; case 3: return h = e, f = Qo(["r", "c", "d"], t), "\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + h[0] + ", " + h[1] + "));\n      int index = resTexRC.x * " + h[1] + " + resTexRC.y;\n      " + f + "\n      return ivec3(r, c, d);\n    }\n  "; case 4: return a = e, s = Qo(["r", "c", "d", "d2"], t), "\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(" + a[0] + ", " + a[1] + "));\n      int index = resTexRC.x * " + a[1] + " + resTexRC.y;\n      " + s + "\n      return ivec4(r, c, d, d2);\n    }\n  "; case 5: return o = e, i = Qo(["r", "c", "d", "d2", "d3"], t), "\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2(" + o[0] + ",\n                             " + o[1] + "));\n\n      int index = resTexRC.x * " + o[1] + " + resTexRC.y;\n\n      " + i + "\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  "; case 6: return n = e, r = Qo(["r", "c", "d", "d2", "d3", "d4"], t), "\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(" + n[0] + ", " + n[1] + "));\n      int index = resTexRC.x * " + n[1] + " + resTexRC.y;\n\n      " + r + "\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  "; default: throw new Error(t.length + "-D output sampling is not yet supported") }var n, r, o, i, a, s, u, c, l, h, f }(e.logicalShape, l), "\n    void setOutput(float val) {\n      " + h.output + " = vec4(val, 0, 0, 0);\n    }\n  "), r && (p += "\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n"), [p, f, a, u, i, c, n].join("\n") } function ni(t) { return "offset" + t } function ri(t) { var e = t.name, n = L(t.shapeInfo.logicalShape); return n < 2 ? "return " + e + ";" : "\n    for (int i = 0; i < " + n + "; i++) {\n      if (i == index) {\n        return " + e + "[i];\n      }\n    }\n  " } function oi(t) { if (t <= 1) return "int"; if (2 === t) return "ivec2"; if (3 === t) return "ivec3"; if (4 === t) return "ivec4"; if (5 === t) return "ivec5"; if (6 === t) return "ivec6"; throw Error("GPU for rank " + t + " is not yet supported") } function ii(t, e) { var n = JSON.parse(JSON.stringify(t)); return n.shapeInfo.logicalShape = e, n } function ai(e, t) { return t.map(function (t) { return e[t] }).join(", ") } function si(t, e, n, r) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0, P(2 < t.length, function () { return "Packed arg" + (n.charAt(0).toUpperCase() + n.slice(1)) + " supports only inputs with rank above 2." }); var o = t[t.length - 1], i = Math.ceil(o / e); this.outputShape = t.slice(0, -1), 1 < i && this.outputShape.push(i), r || this.variableNames.push("bestIndicesA"); var a, s, u = this.outputShape, c = u.length, l = oi(c), h = $o("coords", c); if (1 === i) { var f = oi(s = c + 1); a = "\n        " + f + " sourceLocR = " + f + "(" + h.join() + ", 0);\n        ++" + h[c - 1] + ";\n        " + f + " sourceLocG = " + f + "(" + h.join() + ", 0);\n        ++" + h[c - 2] + ";\n        " + f + " sourceLocA = " + f + "(" + h.join() + ", 0);\n        --" + h[c - 1] + ";\n        " + f + " sourceLocB = " + f + "(" + h.join() + ", 0);\n        --" + h[c - 2] + ";" } else a = "\n        " + l + " sourceLocR = coords;\n        ++" + h[(s = c) - 1] + ";\n        " + l + " sourceLocG = coords;\n        ++" + h[c - 2] + ";\n        " + l + " sourceLocA = coords;\n        --" + h[c - 1] + ";\n        " + l + " sourceLocB = coords;\n        --" + h[c - 2] + ";"; var p = ["x", "y", "z", "w", "u", "v"].slice(0, s), d = "." + p[s - 1], v = p.map(function (t) { return "int " + t }), m = $o("sourceLocR", s - 1).concat("inIdx.r"), g = $o("sourceLocG", s - 1).concat("inIdx.g"), y = $o("sourceLocB", s - 1).concat("inIdx.b"), x = $o("sourceLocA", s - 1).concat("inIdx.a"), b = "max" === n ? "greaterThan" : "lessThan", w = r ? "" : "\n          inIdx = round(vec4(getBestIndicesAChannel(" + m.join() + "),\n                             getBestIndicesAChannel(" + g.join() + "),\n                             getBestIndicesAChannel(" + y.join() + "),\n                             getBestIndicesAChannel(" + x.join() + ")));", C = "vec4(\n            getAChannel(" + m.join() + "),\n            hasNextCol ? getAChannel(" + g.join() + ") : 0.,\n            hasNextRow ? getAChannel(" + y.join() + ") : 0.,\n            hasNextRow && hasNextCol ? getAChannel(" + x.join() + ") : 0.)", E = r ? "" : "\n      float getBestIndicesAChannel(" + v.join() + ") {\n        return getChannel(getBestIndicesA(" + p.join() + "),\n                                          vec2(" + p.slice(-2).join() + "));\n      }"; this.userCode = "\n      float getAChannel(" + v.join() + ") {\n        return getChannel(getA(" + p.join() + "),\n                               vec2(" + p.slice(-2).join() + "));\n      }\n      " + E + "\n      void main() {\n        " + l + " coords = getOutputCoords();\n        bool hasNextCol = " + h[c - 1] + " < " + (u[c - 1] - 1) + ";\n        bool hasNextRow = " + h[c - 2] + " < " + (u[c - 2] - 1) + ";\n        " + a + "\n        ivec4 srcIdx = ivec4(sourceLocR" + d + ", sourceLocG" + d + ",\n          sourceLocB" + d + ", sourceLocA" + d + ") * " + e + ";\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = " + C + ";\n\n        for (int i = 0; i < " + e + "; i++) {\n          inIdx = srcIdx;\n          " + w + "\n          vec4 candidate = " + C + ";\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4(" + b + "(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    " } function ui(t) { this.variableNames = ["dy"], this.outputShape = t.inShape; var e = t.filterHeight, n = t.filterWidth, r = t.strideHeight, o = t.strideWidth, i = t.dilationHeight, a = t.dilationWidth, s = t.effectiveFilterHeight, u = t.effectiveFilterWidth, c = s - 1 - t.padInfo.top, l = u - 1 - t.padInfo.left, h = 1 / (e * n); this.userCode = "\n      const ivec2 pads = ivec2(" + c + ", " + l + ");\n      const float avgMultiplier = float(" + h + ");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < " + s + ";\n            wR += " + i + ") {\n          float dyR = float(dyRCorner + wR) / " + r + ".0;\n\n          if (dyR < 0.0 || dyR >= " + t.outHeight + ".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < " + u + ";\n            wC+= " + a + ") {\n            float dyC = float(dyCCorner + wC) / " + o + ".0;\n\n            if (dyC < 0.0 || dyC >= " + t.outWidth + ".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function ci(t) { this.variableNames = ["dy"], this.outputShape = t.inShape; var e = t.filterDepth, n = t.filterHeight, r = t.filterWidth, o = t.strideDepth, i = t.strideHeight, a = t.strideWidth, s = t.dilationDepth, u = t.dilationHeight, c = t.dilationWidth, l = t.effectiveFilterDepth, h = t.effectiveFilterHeight, f = t.effectiveFilterWidth, p = l - 1 - t.padInfo.front, d = h - 1 - t.padInfo.top, v = f - 1 - t.padInfo.left, m = 1 / (e * n * r); this.userCode = "\n      const ivec3 pads = ivec3(" + p + ", " + d + ", " + v + ");\n      const float avgMultiplier = float(" + m + ");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < " + l + ";\n            wD += " + s + ") {\n          float dyD = float(dyDCorner + wD) / " + o + ".0;\n\n          if (dyD < 0.0 || dyD >= " + t.outDepth + ".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < " + h + ";\n              wR += " + u + ") {\n            float dyR = float(dyRCorner + wR) / " + i + ".0;\n\n            if (dyR < 0.0 || dyR >= " + t.outHeight + ".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < " + f + ";\n                wC += " + c + ") {\n              float dyC = float(dyCCorner + wC) / " + a + ".0;\n\n              if (dyC < 0.0 || dyC >= " + t.outWidth + ".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function li(t, e, n, r, o, i) { this.outputShape = [], this.variableNames = ["x", "mean", "variance"], go(t, e), go(t, n); var a = "0.0"; null != r && (go(t, r), this.variableNames.push("offset"), a = "getOffsetAtOutCoords()"); var s = "1.0"; null != o && (go(t, o), this.variableNames.push("scale"), s = "getScaleAtOutCoords()"), this.outputShape = t, this.userCode = "\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = " + a + ";\n        float scale = " + s + ";\n        float inv = scale * inversesqrt(variance + float(" + i + "));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    " } function hi(t, e, n, r, o, i) { this.packedInputs = !0, this.packedOutput = !0, this.variableNames = ["x", "mean", "variance"], go(t, e), go(t, n); var a = "vec4(0.0)"; null != r && (go(t, r), this.variableNames.push("offset"), a = "getOffsetAtOutCoords()"); var s = "vec4(1.0)"; null != o && (go(t, o), this.variableNames.push("scale"), s = "getScaleAtOutCoords()"), this.outputShape = t, this.userCode = "\n      void main() {\n        vec4 offset = " + a + ";\n        vec4 scale = " + s + ";\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4(" + i + "));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    " } function fi(t, e, n) { this.variableNames = ["AReal", "AImag", "BReal", "BImag"], this.outputShape = go(e, n), this.userCode = "\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        " + t + "\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    " } function pi(t, e, n) { this.variableNames = ["A", "B"], this.outputShape = go(e, n), this.userCode = "\n      float binaryOperation(float a, float b) {\n        " + t + "\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    " } function di(t, e, n, r) { void 0 === r && (r = !1), this.variableNames = ["A", "B"], this.supportsBroadcasting = !0, this.packedInputs = !0, this.packedOutput = !0, this.outputShape = go(e, n); var o = this.outputShape.length, i = ""; if (r) if (0 === o || 1 === L(this.outputShape)) i = "\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        "; else if (i = "\n          " + oi(o) + " coords = getOutputCoords();\n        ", 1 === o) i += "\n            result.y = (coords + 1) >= " + this.outputShape[0] + " ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          "; else { var a = $o("coords", o); i += "\n            bool nextRowOutOfBounds =\n              (" + a[o - 2] + " + 1) >= " + this.outputShape[o - 2] + ";\n            bool nextColOutOfBounds =\n              (" + a[o - 1] + " + 1) >= " + this.outputShape[o - 1] + ";\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          " } this.userCode = "\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        " + t + "\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        " + i + "\n\n        setOutput(result);\n      }\n    " } function vi(t) { this.variableNames = ["real", "imag"], this.outputShape = t, this.userCode = "\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    " } function mi(t) { this.outputShape = [], this.outputShape = bn(t, 1), this.variableNames = t.map(function (t, e) { return "T" + e }); var e = new Array(t.length - 1); e[0] = t[0][1]; for (var n = 1; n < e.length; n++)e[n] = e[n - 1] + t[n][1]; var r = ["if (yC < " + e[0] + ") setOutput(getT0(yR, yC));"]; for (n = 1; n < e.length; n++) { var o = e[n - 1]; r.push("else if (yC < " + e[n] + ") setOutput(getT" + n + "(yR, yC-" + o + "));") } var i = e.length, a = e[e.length - 1]; r.push("else setOutput(getT" + i + "(yR, yC-" + a + "));"), this.userCode = "\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        " + r.join("\n        ") + "\n      }\n    " } function gi(t, e) { this.packedInputs = !0, this.packedOutput = !0, this.outputShape = [], this.outputShape = bn(t, e); var n = this.outputShape, r = n.length, o = oi(r), i = $o("coords", r), a = ["x", "y", "z", "w", "u", "v"].slice(0, r); this.variableNames = t.map(function (t, e) { return "T" + e }); var s = new Array(t.length - 1); s[0] = t[0][e]; for (var u = 1; u < s.length; u++)s[u] = s[u - 1] + t[u][e]; var c = a[e], l = a.slice(-2), h = a.join(), f = "if (" + c + " < " + s[0] + ") {\n        return getChannel(\n            getT0(" + h + "), vec2(" + l.join() + "));\n        }"; for (u = 1; u < s.length; u++) { var p = s[u - 1]; f += "\n        if (" + c + " < " + s[u] + "  && " + c + " >= " + s[u - 1] + ") {\n          return getChannel(\n            getT" + u + "(" + ki(a, c, p) + "),\n            vec2(" + ki(l, c, p) + "));\n        }" } var d = s.length, v = s[s.length - 1]; f += "\n        return getChannel(\n          getT" + d + "(" + ki(a, c, v) + "),\n          vec2(" + ki(l, c, v) + "));", this.userCode = "\n      float getValue(" + a.map(function (t) { return "int " + t }) + ") {\n        " + f + "\n      }\n\n      void main() {\n        " + o + " coords = getOutputCoords();\n        vec4 result = vec4(getValue(" + i + "), 0., 0., 0.);\n\n        " + i[r - 1] + " = " + i[r - 1] + " + 1;\n        if (" + i[r - 1] + " < " + n[r - 1] + ") {\n          result.g = getValue(" + i + ");\n        }\n\n        " + i[r - 2] + " = " + i[r - 2] + " + 1;\n        if (" + i[r - 2] + " < " + n[r - 2] + ") {\n          result.a = getValue(" + i + ");\n        }\n\n        " + i[r - 1] + " = " + i[r - 1] + " - 1;\n        if (" + i[r - 2] + " < " + n[r - 2] + " &&\n            " + i[r - 1] + " < " + n[r - 1] + ") {\n          result.b = getValue(" + i + ");\n        }\n        setOutput(result);\n      }\n    " } var yi = "return a + b;", xi = "return a - b;", bi = "return a * b;", wi = "return (a < 0.) ? b * a : a;", Ci = "\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n", Ei = (Ri.prototype.getCustomSetupFunc = function (n, r) { var o = this; return function (t, e) { null == o.minLoc && (o.minLoc = t.getUniformLocationNoThrow(e, "minVal"), o.maxLoc = t.getUniformLocationNoThrow(e, "maxVal")), t.gl.uniform1f(o.minLoc, n), t.gl.uniform1f(o.maxLoc, r) } }, Ri), _i = (Ii.prototype.getCustomSetupFunc = function (n, r) { var o = this; return function (t, e) { null == o.minLoc && (o.minLoc = t.getUniformLocationNoThrow(e, "minVal"), o.maxLoc = t.getUniformLocationNoThrow(e, "maxVal")), t.gl.uniform1f(o.minLoc, n), t.gl.uniform1f(o.maxLoc, r) } }, Ii); function Ii(t) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t, this.userCode = "\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    " } function Ri(t) { this.variableNames = ["A"], this.outputShape = t, this.userCode = "\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    " } function ki(t, e, n) { var r = t.indexOf(e); return t.map(function (t, e) { return e === r ? t + " - " + n : t }).join() } function Si(t) { this.variableNames = ["x", "dy"], this.outputShape = t.filterShape; var e = t.strideHeight, n = t.strideWidth, r = t.padInfo.top, o = t.padInfo.left, i = "channelsLast" === t.dataFormat; this.userCode = "\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < " + t.batchSize + "; b++) {\n          for (int yR = 0; yR < " + t.outHeight + "; yR++) {\n            int xR = wR + yR * " + e + " - " + r + ";\n\n            if (xR < 0 || xR >= " + t.inHeight + ") {\n              continue;\n            }\n\n            for (int yC = 0; yC < " + t.outWidth + "; yC++) {\n              int xC = wC + yC * " + n + " - " + o + ";\n\n              if (xC < 0 || xC >= " + t.inWidth + ") {\n                continue;\n              }\n\n              if (" + i + ") {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Di(t) { this.variableNames = ["dy", "W"], this.outputShape = t.inShape; var e = t.filterHeight, n = t.filterWidth, r = t.strideHeight, o = t.strideWidth, i = "channelsLast" === t.dataFormat, a = e - 1 - t.padInfo.top, s = n - 1 - t.padInfo.left, u = i ? 1 : 2, c = i ? 2 : 3, l = i ? 3 : 1; this.userCode = "\n      const ivec2 pads = ivec2(" + a + ", " + s + ");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[" + l + "];\n\n        ivec2 dyCorner = ivec2(coords[" + u + "], coords[" + c + "]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < " + e + "; wR++) {\n          float dyR = float(dyRCorner + wR) / " + r + ".0;\n\n          if (dyR < 0.0 || dyR >= " + t.outHeight + ".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = " + e + " - 1 - wR;\n\n          for (int wC = 0; wC < " + n + "; wC++) {\n            float dyC = float(dyCCorner + wC) / " + o + ".0;\n\n            if (dyC < 0.0 || dyC >= " + t.outWidth + ".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = " + n + " - 1 - wC;\n\n            for (int d2 = 0; d2 < " + t.outChannels + "; d2++) {\n\n              if (" + i + ") {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Ai(t) { this.variableNames = ["x", "dy"], this.outputShape = t.filterShape; var e = t.strideDepth, n = t.strideHeight, r = t.strideWidth, o = t.padInfo.front, i = t.padInfo.top, a = t.padInfo.left; this.userCode = "\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < " + t.batchSize + "; b++) {\n          for (int yF = 0; yF < " + t.outDepth + "; yF++) {\n            int xF = wF + yF * " + e + " - " + o + ";\n\n            if (xF < 0 || xF >= " + t.inDepth + ") {\n              continue;\n            }\n\n            for (int yR = 0; yR < " + t.outHeight + "; yR++) {\n              int xR = wR + yR * " + n + " - " + i + ";\n\n              if (xR < 0 || xR >= " + t.inHeight + ") {\n                continue;\n              }\n\n              for (int yC = 0; yC < " + t.outWidth + "; yC++) {\n                int xC = wC + yC * " + r + " - " + a + ";\n\n                if (xC < 0 || xC >= " + t.inWidth + ") {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Ti(t) { this.variableNames = ["dy", "W"], this.outputShape = t.inShape; var e = t.filterDepth, n = t.filterHeight, r = t.filterWidth, o = t.strideDepth, i = t.strideHeight, a = t.strideWidth, s = e - 1 - t.padInfo.front, u = n - 1 - t.padInfo.top, c = r - 1 - t.padInfo.left; this.userCode = "\n      const ivec3 pads = ivec3(" + s + ", " + u + ", " + c + ");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < " + e + "; wF++) {\n          float dyF = float(dyFCorner + wF) / " + o + ".0;\n\n          if (dyF < 0.0 || dyF >= " + t.outDepth + ".0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = " + e + " - 1 - wF;\n\n          for (int wR = 0; wR < " + n + "; wR++) {\n            float dyR = float(dyRCorner + wR) / " + i + ".0;\n\n            if (dyR < 0.0 || dyR >= " + t.outHeight + ".0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = " + n + " - 1 - wR;\n\n            for (int wC = 0; wC < " + r + "; wC++) {\n              float dyC = float(dyCCorner + wC) / " + a + ".0;\n\n              if (dyC < 0.0 || dyC >= " + t.outWidth + ".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = " + r + " - 1 - wC;\n\n              for (int d2 = 0; d2 < " + t.outChannels + "; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Ni(t) { this.variableNames = ["x", "dy"], this.outputShape = t.filterShape; var e = t.strideHeight, n = t.strideWidth, r = t.padInfo.top, o = t.padInfo.left, i = t.outChannels / t.inChannels; this.userCode = "\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * " + i + " + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < " + t.batchSize + "; b++) {\n          for (int yR = 0; yR < " + t.outHeight + "; yR++) {\n            int xR = wR + yR * " + e + " - " + r + ";\n\n            if (xR < 0 || xR >= " + t.inHeight + ") {\n              continue;\n            }\n\n            for (int yC = 0; yC < " + t.outWidth + "; yC++) {\n              int xC = wC + yC * " + n + " - " + o + ";\n\n              if (xC < 0 || xC >= " + t.inWidth + ") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Fi(t) { this.variableNames = ["dy", "W"], this.outputShape = t.inShape; var e = t.filterHeight, n = t.filterWidth, r = t.strideHeight, o = t.strideWidth, i = e - 1 - t.padInfo.top, a = n - 1 - t.padInfo.left, s = t.outChannels / t.inChannels; this.userCode = "\n      const ivec2 pads = ivec2(" + i + ", " + a + ");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < " + e + "; wR++) {\n          float dyR = float(dyRCorner + wR) / " + r + ".0;\n\n          if (dyR < 0.0 || dyR >= " + t.outHeight + ".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = " + e + " - 1 - wR;\n\n          for (int wC = 0; wC < " + n + "; wC++) {\n            float dyC = float(dyCCorner + wC) / " + o + ".0;\n\n            if (dyC < 0.0 || dyC >= " + t.outWidth + ".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = " + n + " - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < " + s + "; dm++) {\n              int d2 = d1 * " + s + " + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Mi(t, e, n, r) { void 0 === e && (e = !1), void 0 === n && (n = null), void 0 === r && (r = !1), this.variableNames = ["x", "W"], this.outputShape = t.outShape; var o = t.padInfo.top, i = t.padInfo.left, a = t.strideHeight, s = t.strideWidth, u = t.dilationHeight, c = t.dilationWidth, l = t.filterHeight, h = t.filterWidth, f = 4 * Math.floor(t.inChannels / 4), p = t.inChannels % 4, d = "channelsLast" === t.dataFormat, v = d ? 1 : 2, m = d ? 2 : 3, g = d ? 3 : 1, y = "", x = ""; n && (y = r ? "float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          " + n + "\n        }" : "\n          float activation(float x) {\n            " + n + "\n          }\n        ", x = "result = activation(result);"); var b = e ? "result += getBiasAtOutCoords();" : ""; e && this.variableNames.push("bias"), r && this.variableNames.push("preluActivationWeights"), this.userCode = "\n      " + y + "\n\n      const ivec2 strides = ivec2(" + a + ", " + s + ");\n      const ivec2 pads = ivec2(" + o + ", " + i + ");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords[" + g + "];\n\n        ivec2 xRCCorner =\n            ivec2(coords[" + v + "], coords[" + m + "]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < " + l + "; wR++) {\n          int xR = xRCorner + wR * " + u + ";\n\n          if (xR < 0 || xR >= " + t.inHeight + ") {\n            continue;\n          }\n\n          for (int wC = 0; wC < " + h + "; wC++) {\n            int xC = xCCorner + wC * " + c + ";\n\n            if (xC < 0 || xC >= " + t.inWidth + ") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < " + f + "; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if (" + d + ") {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if (" + (1 == p) + ") {\n\n              if (" + d + ") {\n                dotProd +=\n                    getX(batch, xR, xC, " + f + ") *\n                    getW(wR, wC, " + f + ", d2);\n              } else {\n                dotProd +=\n                    getX(batch, " + f + ", xR, xC) *\n                    getW(wR, wC, " + f + ", d2);\n              }\n\n            } else if (" + (2 == p) + ") {\n              vec2 wValues = vec2(\n                getW(wR, wC, " + f + ", d2),\n                getW(wR, wC, " + f + " + 1, d2)\n              );\n\n              if (" + d + ") {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, " + f + "),\n                  getX(batch, xR, xC, " + f + " + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, " + f + ", xR, xC),\n                  getX(batch, " + f + " + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if (" + (3 == p) + ") {\n              vec3 wValues = vec3(\n                getW(wR, wC, " + f + ", d2),\n                getW(wR, wC, " + f + " + 1, d2),\n                getW(wR, wC, " + f + " + 2, d2)\n              );\n\n              if (" + d + ") {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, " + f + "),\n                  getX(batch, xR, xC, " + f + " + 1),\n                  getX(batch, xR, xC, " + f + " + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, " + f + ", xR, xC),\n                  getX(batch, " + f + " + 1, xR, xC),\n                  getX(batch, " + f + " + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        " + b + "\n        " + x + "\n        setOutput(result);\n      }\n    " } function Oi(t) { this.variableNames = ["x", "W"], this.outputShape = t.outShape; var e = t.padInfo.front, n = t.padInfo.top, r = t.padInfo.left, o = t.strideDepth, i = t.strideHeight, a = t.strideWidth, s = t.dilationDepth, u = t.dilationHeight, c = t.dilationWidth, l = t.filterDepth, h = t.filterHeight, f = t.filterWidth, p = 4 * Math.floor(t.inChannels / 4), d = t.inChannels % 4; this.userCode = "\n      const ivec3 strides = ivec3(" + o + ", " + i + ", " + a + ");\n      const ivec3 pads = ivec3(" + e + ", " + n + ", " + r + ");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < " + l + "; wF++) {\n          int xF = xFCorner + wF * " + s + ";\n\n          if (xF < 0 || xF >= " + t.inDepth + ") {\n            continue;\n          }\n\n          for (int wR = 0; wR < " + h + "; wR++) {\n            int xR = xRCorner + wR * " + u + ";\n\n            if (xR < 0 || xR >= " + t.inHeight + ") {\n              continue;\n            }\n\n            for (int wC = 0; wC < " + f + "; wC++) {\n              int xC = xCCorner + wC * " + c + ";\n\n              if (xC < 0 || xC >= " + t.inWidth + ") {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < " + p + "; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if (" + (1 == d) + ") {\n                dotProd +=\n                  getX(batch, xF, xR, xC, " + p + ") *\n                  getW(wF, wR, wC, " + p + ", d2);\n              } else if (" + (2 == d) + ") {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, " + p + "),\n                  getX(batch, xF, xR, xC, " + p + " + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, " + p + ", d2),\n                  getW(wF, wR, wC, " + p + " + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if (" + (3 == d) + ") {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, " + p + "),\n                  getX(batch, xF, xR, xC, " + p + " + 1),\n                  getX(batch, xF, xR, xC, " + p + " + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, " + p + ", d2),\n                  getW(wF, wR, wC, " + p + " + 1, d2),\n                  getW(wF, wR, wC, " + p + " + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Pi(t, e, n, r) { void 0 === e && (e = !1), void 0 === n && (n = null), void 0 === r && (r = !1), this.variableNames = ["x", "W"], this.outputShape = t.outShape; var o = t.inHeight, i = t.inWidth, a = t.padInfo.top, s = t.padInfo.left, u = t.strideHeight, c = t.strideWidth, l = t.dilationHeight, h = t.dilationWidth, f = t.filterHeight, p = t.filterWidth, d = t.outChannels / t.inChannels, v = "", m = ""; n && (v = r ? "float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          " + n + "\n        }" : "\n          float activation(float x) {\n            " + n + "\n          }\n        ", m = "result = activation(result);"); var g = e ? "result += getBiasAtOutCoords();" : ""; e && this.variableNames.push("bias"), r && this.variableNames.push("preluActivationWeights"), this.userCode = "\n      " + v + "\n\n      const ivec2 strides = ivec2(" + u + ", " + c + ");\n      const ivec2 pads = ivec2(" + a + ", " + s + ");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / " + d + ";\n        int q = d2 - d1 * " + d + ";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < " + f + "; wR++) {\n          int xR = xRCorner + wR * " + l + ";\n\n          if (xR < 0 || xR >= " + o + ") {\n            continue;\n          }\n\n          for (int wC = 0; wC < " + p + "; wC++) {\n            int xC = xCCorner + wC * " + h + ";\n\n            if (xC < 0 || xC >= " + i + ") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        " + g + "\n        " + m + "\n        setOutput(result);\n      }\n    " } function Bi(t, e, n, r) { void 0 === e && (e = !1), void 0 === n && (n = null), void 0 === r && (r = !1), this.variableNames = ["x", "W"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t.outShape; for (var o = t.inHeight, i = t.inWidth, a = t.padInfo.top, s = t.padInfo.left, u = t.strideHeight, c = t.strideWidth, l = t.dilationHeight, h = t.dilationWidth, f = t.filterHeight, p = t.filterWidth, d = p, v = "int xR; int xC; int xCOffset;", m = 0; m < f; m++)for (var g = 0; g < p; g++)v += "\n          vec4 xTexelR" + m + "C" + 2 * g + " = vec4(0.);\n          vec4 wR" + m + "C" + g + " = vec4(0.);\n          vec4 xR" + m + "C" + g + " = vec4(0.);"; for (m = 0; m < f; m++)for (var y = 0; y < d; y++) { if (v += "\n          xR = xRCorner + " + m * l + ";\n          xC = xCCorner + " + (g = 2 * y) * h + ";\n        ", 1 === c) { if (g < p && (v += s % 2 == 1 ? "\n                xCOffset = xC + 1;\n                if(xR >= 0 && xR < " + o + " && xCOffset >= 0 && xCOffset < " + i + ") {\n                  xTexelR" + m + "C" + g + " = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if(xCOffset + 1 >= " + i + ") {\n                    xTexelR" + m + "C" + g + ".zw = vec2(0.);\n                  }\n                } else {\n                  xTexelR" + m + "C" + g + " = vec4(0.);\n                }\n\n                xCOffset = xC + 1 - 2;\n                if(xR >= 0 && xR < " + o + " && xCOffset >= 0 && xCOffset < " + i + ") {\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if(xCOffset + 1 >= " + i + ") {\n                    previous.zw = vec2(0.);\n                  }\n\n                  xR" + m + "C" + g + " = vec4(previous.zw, xTexelR" + m + "C" + g + ".xy);\n                } else {\n                  xR" + m + "C" + g + " = vec4(0, 0, xTexelR" + m + "C" + g + ".xy);\n                }\n              " : "\n                if(xR >= 0 && xR < " + o + " && xC >= 0 && xC < " + i + ") {\n                  xTexelR" + m + "C" + g + " = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR" + m + "C" + g + " = vec4(0.);\n                }\n\n                xR" + m + "C" + g + " = xTexelR" + m + "C" + g + ";\n              ", g + 1 < p)) { var x = s % 2 == 0 ? E(h) : h; h % 2 == 0 && s % 2 == 1 || h % 2 != 0 && s % 2 != 1 ? (v += "\n                  xCOffset = xC + " + s % 2 + " + " + x + ";\n\n                  if(xR >= 0 && xR < " + o + " &&\n                    xCOffset >= 0 && xCOffset < " + i + ") {\n                    xTexelR" + m + "C" + (g + 2) + " = getX(batch, xR, xCOffset, d1);\n                  }\n                ", 1 < h && (v += "\n                    xCOffset -= 2;\n                    if(xR >= 0 && xR < " + o + " &&\n                      xCOffset >= 0 && xCOffset < " + i + ") {\n                      xTexelR" + m + "C" + g + " = getX(batch, xR, xCOffset, d1);\n                    } else {\n                      xTexelR" + m + "C" + g + " = vec4(0.);\n                    }\n                  "), v += "\n                  xR" + m + "C" + (g + 1) + " = vec4(\n                    xTexelR" + m + "C" + g + ".zw, xTexelR" + m + "C" + (g + 2) + ".xy);\n                ") : v += "\n                  xCOffset = xC + " + x + ";\n\n                  if(xR >= 0 && xR < " + o + " &&\n                    xCOffset >= 0 && xCOffset < " + i + ") {\n                    xTexelR" + m + "C" + (g + 2) + " = getX(batch, xR, xCOffset, d1);\n                  }\n\n                  xR" + m + "C" + (g + 1) + " = xTexelR" + m + "C" + (g + 2) + ";\n                " } } else g < p && (v += "\n              if(xR >= 0 && xR < " + o + ") {\n            ", s % 2 == 1 ? (v += "\n                xCOffset = xC + 1 - " + c + ";\n                if(xCOffset >= 0 && xCOffset < " + i + ") {\n                  xTexelR" + m + "C" + g + " = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR" + m + "C" + g + " = vec4(0.);\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < " + i + ") {\n                  xTexelR" + m + "C" + (g + 2) + " = getX(batch, xR, xC + 1, d1);\n                } else {\n                  xTexelR" + m + "C" + (g + 2) + " = vec4(0.);\n                }\n\n                xR" + m + "C" + g + " = vec4(\n                  xTexelR" + m + "C" + g + ".zw, xTexelR" + m + "C" + (g + 2) + ".zw);\n              ", g + 1 < p && (v += "\n                  vec4 final = vec4(0.);\n                  xCOffset = xC + 1 + " + c + ";\n                  if(xCOffset >= 0 && xCOffset < " + i + ") {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xR" + m + "C" + (g + 1) + " = vec4(xTexelR" + m + "C" + (g + 2) + ".xy, final.xy);\n                ")) : (v += "\n                if(xC >= 0 && xC < " + i + ") {\n                  xTexelR" + m + "C" + g + " = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR" + m + "C" + g + " = vec4(0.);\n                }\n\n                xCOffset = xC + " + c + ";\n                if(xCOffset >= 0 && xCOffset < " + i + ") {\n                  xTexelR" + m + "C" + (g + 2) + " = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR" + m + "C" + (g + 2) + " = vec4(0.);\n                }\n\n                xR" + m + "C" + g + " = vec4(\n                  xTexelR" + m + "C" + g + ".xy, xTexelR" + m + "C" + (g + 2) + ".xy);\n              ", g + 1 < p && (v += "\n                  xR" + m + "C" + (g + 1) + " = vec4(\n                    xTexelR" + m + "C" + g + ".zw, xTexelR" + m + "C" + (g + 2) + ".zw);\n                ")), v += "}"); g < p && (v += "\n            vec4 wTexelR" + m + "C" + g + " = getW(" + m + ", " + g + ", d1, q);\n            wR" + m + "C" + g + " = vec4(wTexelR" + m + "C" + g + ".xz, wTexelR" + m + "C" + g + ".xz);\n          ", g + 1 < p && (v += "\n              vec4 wTexelR" + m + "C" + (g + 1) + " = getW(" + m + ", " + (g + 1) + ", d1, q);\n              wR" + m + "C" + (g + 1) + " =\n                vec4(wTexelR" + m + "C" + (g + 1) + ".xz, wTexelR" + m + "C" + (g + 1) + ".xz);")) } for (m = 0; m < f; m++)for (g = 0; g < p; g++)v += "dotProd += xR" + m + "C" + g + " * wR" + m + "C" + g + ";"; var b = "", w = ""; n && (b = r ? "vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          " + n + "\n        }" : "vec4 activation(vec4 x) {\n          " + n + "\n        }", w = "result = activation(result);"); var C = e ? "result += getBiasAtOutCoords();" : ""; e && this.variableNames.push("bias"), r && this.variableNames.push("preluActivationWeights"), this.userCode = "\n      " + b + "\n\n      const ivec2 strides = ivec2(" + u + ", " + c + ");\n      const ivec2 pads = ivec2(" + a + ", " + s + ");\n\n      void main() {\n\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2;\n        int q = 0;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        vec4 dotProd = vec4(0.);\n\n        " + v + "\n\n        vec4 result = dotProd;\n        " + C + "\n        " + w + "\n        setOutput(result);\n      }\n    " } function Li(t, e, n, r, o) { this.variableNames = ["Image", "Boxes", "BoxInd"], this.outputShape = []; var i = t[0], a = t[1], s = t[2], u = t[3], c = e[0], l = n[0], h = n[1]; this.outputShape = [c, l, h, u]; var f = "bilinear" === r ? 1 : 0, p = [a - 1 + ".0", s - 1 + ".0"], d = p[0], v = p[1], m = 1 < l ? ["" + (a - 1) / (l - 1), "(y2-y1) * height_ratio", "y1*" + d + " + float(y)*(height_scale)"] : ["0.0", "0.0", "0.5 * (y1+y2) * " + d], g = m[0], y = m[1], x = m[2], b = 1 < h ? ["" + (s - 1) / (h - 1), "(x2-x1) * width_ratio", "x1*" + v + " + float(x)*(width_scale)"] : ["0.0", "0.0", "0.5 * (x1+x2) * " + v], w = b[0], C = b[1], E = b[2]; this.userCode = "\n      const float height_ratio = float(" + g + ");\n      const float width_ratio = float(" + w + ");\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= " + i + ") {\n          return;\n        }\n\n        float height_scale = " + y + ";\n        float width_scale = " + C + ";\n\n        float in_y = " + x + ";\n        if( in_y < 0.0 || in_y > " + d + " ) {\n          setOutput(float(" + o + "));\n          return;\n        }\n        float in_x = " + E + ";\n        if( in_x < 0.0 || in_x > " + v + " ) {\n          setOutput(float(" + o + "));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if(" + f + " == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    " } function Wi(t, e, n) { this.variableNames = ["x"]; var r = (this.outputShape = t).length, o = t[t.length - 1], i = n ? "<" : ">"; this.userCode = "\n      int getIndex(int i) {\n        " + (n ? "return " + o + " -i - 1;" : "return i;") + "\n      }\n\n      void main() {\n        " + oi(r) + " coords = getOutputCoords();\n        int end = " + zi(r, "coords") + ";\n        float val = 0.0;\n        for (int i = " + o + " - 1; i >= 0; i -= 1) {\n          int idx = getIndex(i);\n          if (idx " + i + " end) {\n            continue;\n          }\n          if (idx == end && " + e + ") {\n            continue;\n          }\n          " + zi(r, "coords") + " = idx;\n          val += getX(" + function (t, e) { if (1 === r) return e; if (2 === r) return e + ".x, " + e + ".y"; if (3 === r) return "coords.x, coords.y, coords.z"; if (4 === r) return "coords.x, coords.y, coords.z, coords.w"; throw Error("Cumulative sum for rank " + r + " is not yet supported") }(0, "coords") + ");\n        }\n        setOutput(val);\n      }\n    " } function zi(t, e) { if (1 === t) return "" + e; if (2 === t) return e + ".y"; if (3 === t) return e + ".z"; if (4 === t) return e + ".w"; throw Error("Cumulative sum for rank " + t + " is not yet supported") } function Ui(t) { this.variableNames = ["A"], this.packedInputs = !1, this.packedOutput = !0, this.outPackingScheme = $t.DENSE; var e = se(t), n = Jo(); this.outputShape = t, this.userCode = "\n      ivec3 outCoordsFromFlatIndex(int index) {\n        " + Qo(["r", "c", "d"], t) + "\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2(" + e[0] + ", " + e[1] + "));\n        int index = 4 * (resTexRC.x * " + e[1] + " + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        " + n.output + " = result;\n      }\n    " } function Vi(t) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0, this.outPackingScheme = $t.DENSE; var e = se(t), n = Jo(); this.outputShape = t, this.userCode = "\n      ivec3 outCoordsFromFlatIndex(int index) {\n        " + Qo(["r", "c", "d"], t) + "\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2(" + e[0] + ", " + e[1] + "));\n        int index = 4 * (resTexRC.x * " + e[1] + " + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        " + n.output + " = result;\n      }\n    " } function Gi(t) { this.variableNames = ["X"], this.outputShape = [t, t], this.userCode = "\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    " } function Hi(t) { this.variableNames = ["A"], this.outTexUsage = Jt.DOWNLOAD; var e = Jo(); this.outputShape = t, this.userCode = "\n      " + ti + "\n\n      void main() {\n        float x = getAAtOutCoords();\n        " + e.output + " = encode_float(x);\n      }\n    " } function qi(t) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !1, this.outTexUsage = Jt.DOWNLOAD; var e = Jo(); this.outputShape = t, this.userCode = "\n      " + ti + "\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        " + e.output + " = encode_float(x);\n      }\n    " } function ji(t, e, n) { void 0 === n && (n = !1), this.variableNames = ["A"]; var r = Jo(), o = e[0], i = e[1]; this.outputShape = t; var a = "result"; n && (a = "floor(result * 255. + 0.5)"), this.userCode = "\n      " + Zo(t) + "\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n        \n        int r = flatIndex / " + i + ";\n        int c = imod(flatIndex, " + i + ");\n        vec2 uv = (vec2(c, r) + halfCR) / vec2(" + i + ".0, " + o + ".0);\n        vec4 values = " + r.texture2D + "(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        " + r.output + " = vec4(" + a + ", 0., 0., 0.);\n      }\n    " } function Ki(t, e, n) { void 0 === n && (n = !1), this.variableNames = ["A"], this.packedInputs = !1, this.packedOutput = !0; var r = Jo(), o = e[0], i = e[1]; this.outputShape = t; var a = "", s = "result"; n && (s = "floor(result * 255. + 0.5)"); for (var u = 0; u <= 1; u++)for (var c = 0; c <= 1; c++) { var l = 2 * u + c; a += "\n          localCoords = coords;\n          if(localCoords[2] + " + c + " < " + t[2] + ") {\n            localCoords[2] += " + c + ";\n            if(localCoords[1] + " + u + " < " + t[1] + ") {\n              localCoords[1] += " + u + ";\n\n              flatIndex = getFlatIndex(localCoords);\n              offset = imod(flatIndex, 4);\n\n              flatIndex = idiv(flatIndex, 4, 1.);\n\n              r = flatIndex / " + i + ";\n              c = imod(flatIndex, " + i + ");\n              uv = (vec2(c, r) + halfCR) / vec2(" + i + ".0, " + o + ".0);\n              values = " + r.texture2D + "(A, uv);\n\n              if(offset == 0) {\n                result[" + l + "] = values[0];\n              } else if(offset == 1) {\n                result[" + l + "] = values[1];\n              } else if(offset == 2) {\n                result[" + l + "] = values[2];\n              } else {\n                result[" + l + "] = values[3];\n              }\n            }\n          }\n        " } this.userCode = "\n      " + Zo(t) + "\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        vec4 result = vec4(0.);\n        int flatIndex, r, c, offset;\n        ivec3 localCoords;\n        vec2 uv;\n        vec4 values;\n\n        " + a + "\n\n        " + r.output + " = " + s + ";\n      }\n    " } function Xi(t, e, n) { this.variableNames = ["real", "imag"]; var r = e[1]; this.outputShape = e; var o = n ? "2.0 * " + Math.PI : "-2.0 * " + Math.PI, i = n ? r + ".0" : "1.0"; this.userCode = "\n      const float exponentMultiplier = " + o + ";\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        " + t + "\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float(" + r + ");\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < " + r + "; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / " + i + ";\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    " } function Yi(t, e, n) { this.variableNames = ["A", "indices"]; var r = t.slice(); r[n] = e, this.outputShape = r, this.rank = r.length; var o = oi(this.rank), i = function (t, e) { var n = t.length; if (4 < n) throw Error("Gather for rank " + n + " is not yet supported"); if (1 === n) return "int(getIndices(resRC))"; for (var r = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"], o = [], i = 0; i < t.length; i++)i === e ? o.push("int(getIndices(" + r[i] + "))") : o.push("" + r[i]); return o.join() }(t, n); this.userCode = "\n      void main() {\n        " + o + " resRC = getOutputCoords();\n        setOutput(getA(" + i + "));\n      }\n    " } var $i = (Zi.prototype.getHeightCoordString = function () { return "NHWC" === this.dataFormat ? "coords[1]" : "coords[2]" }, Zi.prototype.getWidthCoordString = function () { return "NHWC" === this.dataFormat ? "coords[2]" : "coords[3]" }, Zi.prototype.getDepthCoordString = function () { return "NHWC" === this.dataFormat ? "coords[3]" : "coords[1]" }, Zi.prototype.getOutputDepthSize = function () { return "NHWC" === this.dataFormat ? this.outputShape[3] : this.outputShape[1] }, Zi.prototype.getInputSamplingString = function () { return "NHWC" === this.dataFormat ? "getX(b, in_h, in_w, in_d)" : "getX(b, in_d, in_h, in_w)" }, Zi), Ji = (Qi.prototype.getCustomSetupFunc = function (n) { var r = this; return function (t, e) { null == r.valueLoc && (r.valueLoc = t.getUniformLocationNoThrow(e, "value")), t.gl.uniform1f(r.valueLoc, n) } }, Qi); function Qi(t, e) { this.outputShape = [], this.variableNames = ["x"], this.outputShape = t, this.userCode = "\n      uniform float value;\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    " } function Zi(t, e, n) { this.variableNames = ["x"], this.outputShape = [], this.outputShape = t, this.blockSize = e, this.dataFormat = n, this.userCode = "\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = " + this.getHeightCoordString() + ";\n      int w = " + this.getWidthCoordString() + ";\n      int d = " + this.getDepthCoordString() + ";\n\n      int in_h = h / " + e + ";\n      int offset_h = imod(h, " + e + ");\n      int in_w = w / " + e + ";\n      int offset_w = imod(w, " + e + ");\n      int offset_d = (offset_h * " + e + " + offset_w) *\n        " + this.getOutputDepthSize() + ";\n      int in_d = d + offset_d;\n\n      float result = " + this.getInputSamplingString() + ";\n      setOutput(result);\n    }\n  " } function ta(t, e, n) { this.sliceDim = t, this.strides = e, this.variableNames = ["x", "indices"], this.outputShape = n; var r = oi(e.length), o = oi(n.length), i = 1 < this.sliceDim ? "strides[j]" : "strides"; this.userCode = "\n        " + r + " strides = " + r + "(" + this.strides + ");\n         void main() {\n          " + o + " coords = getOutputCoords();\n          int flattenIndex = 0;\n          for (int j = 0; j < " + this.sliceDim + "; j++) {\n            int index = round(getIndices(coords[0], j));\n            flattenIndex += index * " + i + ";\n          }\n          setOutput(getX(flattenIndex, coords[1]));\n        }\n      " } function ea(t, e) { var n = Jo(); return de(t, e, n.version + "\n    precision highp float;\n    " + n.attribute + " vec3 clipSpacePos;\n    " + n.attribute + " vec2 uv;\n    " + n.varyingVs + " vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }") } function na(t, e) { return Ce(t, e, new Float32Array([-1, 1, 0, 0, 1, -1, -1, 0, 0, 0, 1, 1, 0, 1, 1, 1, -1, 0, 1, 0])) } function ra(t, e) { return Ee(t, e, new Uint16Array([0, 1, 2, 2, 1, 3])) } function oa(t, e, n, r, o, i, a) { Ie(n, r); var s = _e(t, e), u = t.TEXTURE_2D; return le(t, e, function () { return t.bindTexture(u, s) }), le(t, e, function () { return t.texParameteri(u, t.TEXTURE_WRAP_S, t.CLAMP_TO_EDGE) }), le(t, e, function () { return t.texParameteri(u, t.TEXTURE_WRAP_T, t.CLAMP_TO_EDGE) }), le(t, e, function () { return t.texParameteri(u, t.TEXTURE_MIN_FILTER, t.NEAREST) }), le(t, e, function () { return t.texParameteri(u, t.TEXTURE_MAG_FILTER, t.NEAREST) }), le(t, e, function () { return t.texImage2D(u, 0, o, n, r, 0, i, a, null) }), le(t, e, function () { return t.bindTexture(t.TEXTURE_2D, null) }), s } function ia(t, e, n, r, o) { var i = ae(n, r); return oa(t, e, i[0], i[1], o.internalFormatFloat, o.textureFormatFloat, t.FLOAT) } function aa(t, e, n, r, o) { var i = ae(n, r); return oa(t, e, i[0], i[1], o.internalFormatHalfFloat, o.textureFormatFloat, o.textureTypeHalfFloat) } function sa(t, e, n, r, o) { var i = ae(n, r); return oa(t, e, i[0], i[1], t.RGBA, t.RGBA, t.UNSIGNED_BYTE) } function ua(t, e, n, r, o) { var i = ue(n, r); return oa(t, e, i[0], i[1], o.internalFormatPackedFloat, t.RGBA, t.FLOAT) } function ca(t, e, n, r, o) { var i = ue(n, r); return oa(t, e, i[0], i[1], o.internalFormatPackedHalfFloat, t.RGBA, o.textureTypeHalfFloat) } function la(t, e, n, r) { return le(t, e, function () { return t.bindBuffer(t.ARRAY_BUFFER, r) }), ke(t, e, n, "clipSpacePos", r, 3, 20, 0) && ke(t, e, n, "uv", r, 2, 20, 12) } function ha(t, e, n, r, o, i, a) { var s, u, c; le(t, e, function () { return t.bindTexture(t.TEXTURE_2D, n) }), c = i instanceof Uint8Array ? (s = new Uint8Array(r * o * 4), u = t.UNSIGNED_BYTE, t.RGBA) : (s = new Float32Array(r * o * 4), u = t.FLOAT, a.internalFormatPackedFloat), s.set(i), le(t, e, function () { return t.texImage2D(t.TEXTURE_2D, 0, c, r, o, 0, t.RGBA, u, s) }), le(t, e, function () { return t.bindTexture(t.TEXTURE_2D, null) }) } function fa(t, e, n, r) { le(t, e, function () { return t.bindTexture(t.TEXTURE_2D, n) }), r.data instanceof Uint8Array ? le(t, e, function () { return t.texImage2D(t.TEXTURE_2D, 0, t.RGBA, r.width, r.height, 0, t.RGBA, t.UNSIGNED_BYTE, r.data) }) : le(t, e, function () { return t.texImage2D(t.TEXTURE_2D, 0, t.RGBA, t.RGBA, t.UNSIGNED_BYTE, r) }), le(t, e, function () { return t.bindTexture(t.TEXTURE_2D, null) }) } function pa(t, e, n, r, o) { var i = t.createBuffer(); le(t, e, function () { return t.bindBuffer(t.PIXEL_PACK_BUFFER, i) }); var a = 16 * n * r; return le(t, e, function () { return t.bufferData(t.PIXEL_PACK_BUFFER, a, t.STREAM_READ) }), le(t, e, function () { return t.readPixels(0, 0, r, n, t.RGBA, t.FLOAT, 0) }), le(t, e, function () { return t.bindBuffer(t.PIXEL_PACK_BUFFER, null) }), i } function da(t, e, n) { var r = t, o = new Float32Array(n); return r.bindBuffer(r.PIXEL_PACK_BUFFER, e), r.getBufferSubData(r.PIXEL_PACK_BUFFER, 0, o), r.bindBuffer(r.PIXEL_PACK_BUFFER, null), o } function va(t, e, n, r, o) { var i = ae(n, r), a = i[0], s = i[1], u = new Uint8Array(n * r * 4); return le(t, e, function () { return t.readPixels(0, 0, a, s, o.downloadTextureFormat, t.UNSIGNED_BYTE, u) }), new Float32Array(u.buffer) } function ma(t, e, n, r, o, i, a, s) { var u, c = t, l = new Float32Array((u = ue(i, a))[0] * u[1] * 4); return c.bindBuffer(c.PIXEL_PACK_BUFFER, e), c.getBufferSubData(c.PIXEL_PACK_BUFFER, 0, l), c.bindBuffer(c.PIXEL_PACK_BUFFER, null), l } function ga(t, e, n, r) { var o = new Float32Array(n * r * 4); return le(t, e, function () { return t.readPixels(0, 0, r, n, t.RGBA, t.FLOAT, o) }), o } var ya = Object.freeze({ createVertexShader: ea, createVertexBuffer: na, createIndexBuffer: ra, createFloat32MatrixTexture: ia, createFloat16MatrixTexture: aa, createUnsignedBytesMatrixTexture: sa, createPackedMatrixTexture: ua, createFloat16PackedMatrixTexture: ca, bindVertexProgramAttributeStreams: la, uploadDenseMatrixToTexture: ha, uploadPixelDataToTexture: fa, createBufferFromOutputTexture: pa, downloadFloat32MatrixFromBuffer: da, downloadByteEncodedFloatMatrixFromOutputTexture: va, downloadPackedMatrixFromBuffer: ma, downloadMatrixFromPackedOutputTexture: ga }), xa = (Object.defineProperty(ba.prototype, "debug", { get: function () { return _().getBool("DEBUG") }, enumerable: !0, configurable: !0 }), ba.prototype.dispose = function () { var t = this; if (!this.disposed) { null != this.program && console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."), null != this.outputTexture && console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing."); var e = this.gl; le(e, this.debug, function () { return e.finish() }), le(e, this.debug, function () { return e.bindFramebuffer(e.FRAMEBUFFER, null) }), le(e, this.debug, function () { return e.deleteFramebuffer(t.framebuffer) }), le(e, this.debug, function () { return e.bindBuffer(e.ARRAY_BUFFER, null) }), le(e, this.debug, function () { return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER, null) }), le(e, this.debug, function () { return e.deleteBuffer(t.indexBuffer) }), this.disposed = !0 } }, ba.prototype.createFloat32MatrixTexture = function (t, e) { return this.throwIfDisposed(), ia(this.gl, this.debug, t, e, this.textureConfig) }, ba.prototype.createFloat16MatrixTexture = function (t, e) { return this.throwIfDisposed(), aa(this.gl, this.debug, t, e, this.textureConfig) }, ba.prototype.createUnsignedBytesMatrixTexture = function (t, e) { return this.throwIfDisposed(), sa(this.gl, this.debug, t, e, this.textureConfig) }, ba.prototype.uploadPixelDataToTexture = function (t, e) { this.throwIfDisposed(), fa(this.gl, this.debug, t, e) }, ba.prototype.uploadDenseMatrixToTexture = function (t, e, n, r) { this.throwIfDisposed(), ha(this.gl, this.debug, t, e, n, r, this.textureConfig) }, ba.prototype.createFloat16PackedMatrixTexture = function (t, e) { return this.throwIfDisposed(), ca(this.gl, this.debug, t, e, this.textureConfig) }, ba.prototype.createPackedMatrixTexture = function (t, e) { return this.throwIfDisposed(), ua(this.gl, this.debug, t, e, this.textureConfig) }, ba.prototype.deleteMatrixTexture = function (t) { var e = this; this.throwIfDisposed(), this.outputTexture === t && (Fe(this.gl, this.debug, this.framebuffer), this.outputTexture = null), le(this.gl, this.debug, function () { return e.gl.deleteTexture(t) }) }, ba.prototype.downloadByteEncodedFloatMatrixFromOutputTexture = function (t, e, n) { var r = this; return this.downloadMatrixDriver(t, function () { return va(r.gl, r.debug, e, n, r.textureConfig) }) }, ba.prototype.downloadPackedMatrixFromBuffer = function (t, e, n, r, o, i) { return ma(this.gl, t, 0, 0, 0, o, i, this.textureConfig) }, ba.prototype.downloadFloat32MatrixFromBuffer = function (t, e) { return da(this.gl, t, e) }, ba.prototype.createBufferFromTexture = function (t, e, n) { this.bindTextureToFrameBuffer(t); var r = pa(this.gl, this.debug, e, n, this.textureConfig); return this.unbindTextureToFrameBuffer(), r }, ba.prototype.createAndWaitForFence = function () { var t = this.createFence(this.gl); return this.pollFence(t) }, ba.prototype.createFence = function (t) { var e, n, r = this; if (_().getBool("WEBGL_FENCE_API_ENABLED")) { var o = t, i = o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE, 0); t.flush(), n = function () { var t = o.clientWaitSync(i, 0, 0); return t === o.ALREADY_SIGNALED || t === o.CONDITION_SATISFIED }, e = i } else n = 0 < _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") ? (e = this.beginQuery(), this.endQuery(), function () { return r.isQueryAvailable(e, _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")) }) : function () { return !0 }; return { query: e, isFencePassed: n } }, ba.prototype.downloadMatrixFromPackedTexture = function (t, e, n) { var r = this; return this.downloadMatrixDriver(t, function () { return ga(r.gl, r.debug, e, n) }) }, ba.prototype.createProgram = function (t) { this.throwIfDisposed(); var e = this.gl, n = ve(e, this.debug, t), r = ea(e, this.debug), o = xe(e, this.debug); return le(e, this.debug, function () { return e.attachShader(o, r) }), le(e, this.debug, function () { return e.attachShader(o, n) }), be(e, this.debug, o), this.debug && we(e, this.debug, o), this.vertexAttrsAreBound || (this.setProgram(o), this.vertexAttrsAreBound = la(e, this.debug, this.program, this.vertexBuffer)), o }, ba.prototype.deleteProgram = function (t) { var e = this; this.throwIfDisposed(), t === this.program && (this.program = null), null != t && le(this.gl, this.debug, function () { return e.gl.deleteProgram(t) }) }, ba.prototype.setProgram = function (t) { var e = this; this.throwIfDisposed(), this.program = t, null != this.program && this.debug && we(this.gl, this.debug, this.program), le(this.gl, this.debug, function () { return e.gl.useProgram(t) }) }, ba.prototype.getUniformLocation = function (t, e, n) { return void 0 === n && (n = !0), this.throwIfDisposed(), n ? De(this.gl, this.debug, t, e) : Ae(this.gl, t, e) }, ba.prototype.getAttributeLocation = function (t, e) { var n = this; return this.throwIfDisposed(), le(this.gl, this.debug, function () { return n.gl.getAttribLocation(t, e) }) }, ba.prototype.getUniformLocationNoThrow = function (t, e) { return this.throwIfDisposed(), this.gl.getUniformLocation(t, e) }, ba.prototype.setInputMatrixTexture = function (t, e, n) { this.throwIfDisposed(), this.throwIfNoProgram(), Te(this.gl, this.debug, this.program, t, e, n) }, ba.prototype.setOutputMatrixTexture = function (t, e, n) { this.setOutputMatrixTextureDriver(t, n, e) }, ba.prototype.setOutputPackedMatrixTexture = function (t, e, n) { this.throwIfDisposed(); var r = ue(e, n), o = r[0], i = r[1]; this.setOutputMatrixTextureDriver(t, o, i) }, ba.prototype.setOutputMatrixWriteRegion = function (t, e, n, r) { this.setOutputMatrixWriteRegionDriver(n, t, r, e) }, ba.prototype.setOutputPackedMatrixWriteRegion = function (t, e, n, r) { throw new Error("setOutputPackedMatrixWriteRegion not implemented.") }, ba.prototype.debugValidate = function () { null != this.program && we(this.gl, this.debug, this.program), Me(this.gl) }, ba.prototype.executeProgram = function () { this.throwIfDisposed(), this.throwIfNoProgram(); var t = this.gl; this.debug && this.debugValidate(), le(t, this.debug, function () { return t.drawElements(t.TRIANGLES, 6, t.UNSIGNED_SHORT, 0) }) }, ba.prototype.blockUntilAllProgramsCompleted = function () { var t = this; this.throwIfDisposed(), le(this.gl, this.debug, function () { return t.gl.finish() }) }, ba.prototype.getQueryTimerExtension = function () { return null == this.disjointQueryTimerExtension && (this.disjointQueryTimerExtension = pe(this.gl, this.debug, 2 === _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") ? "EXT_disjoint_timer_query_webgl2" : "EXT_disjoint_timer_query")), this.disjointQueryTimerExtension }, ba.prototype.getQueryTimerExtensionWebGL2 = function () { return this.getQueryTimerExtension() }, ba.prototype.getQueryTimerExtensionWebGL1 = function () { return this.getQueryTimerExtension() }, ba.prototype.beginQuery = function () { if (2 === _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")) { var t = this.gl, e = this.getQueryTimerExtensionWebGL2(), n = t.createQuery(); return t.beginQuery(e.TIME_ELAPSED_EXT, n), n } var r = this.getQueryTimerExtensionWebGL1(), o = r.createQueryEXT(); return r.beginQueryEXT(r.TIME_ELAPSED_EXT, o), o }, ba.prototype.endQuery = function () { if (2 !== _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")) { var t = this.getQueryTimerExtensionWebGL1(); t.endQueryEXT(t.TIME_ELAPSED_EXT) } else { var e = this.gl, n = this.getQueryTimerExtensionWebGL2(); e.endQuery(n.TIME_ELAPSED_EXT) } }, ba.prototype.waitForQueryAndGetTime = function (n) { return y(this, void 0, void 0, function () { var e = this; return R(this, function (t) { switch (t.label) { case 0: return [4, k(function () { return e.disposed || e.isQueryAvailable(n, _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")) })]; case 1: return t.sent(), [2, this.getQueryTime(n, _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))] } }) }) }, ba.prototype.getQueryTime = function (t, e) { if (0 === e) return null; if (2 === e) { var n = this.gl; return n.getQueryParameter(t, n.QUERY_RESULT) / 1e6 } var r = this.getQueryTimerExtensionWebGL1(); return r.getQueryObjectEXT(t, r.QUERY_RESULT_EXT) / 1e6 }, ba.prototype.isQueryAvailable = function (t, e) { if (0 === e) return !0; if (2 !== e) return o = (r = this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t, r.QUERY_RESULT_AVAILABLE_EXT), null == this.disjoint && (this.disjoint = this.gl.getParameter(r.GPU_DISJOINT_EXT)), o && !this.disjoint; var n = this.gl, r = this.getQueryTimerExtensionWebGL2(), o = n.getQueryParameter(t, n.QUERY_RESULT_AVAILABLE); return null == this.disjoint && (this.disjoint = this.gl.getParameter(r.GPU_DISJOINT_EXT)), o && !this.disjoint }, ba.prototype.pollFence = function (e) { var n = this; return new Promise(function (t) { n.addItemToPoll(function () { return e.isFencePassed() }, function () { return t() }) }) }, ba.prototype.pollItems = function () { for (var t = function (t) { for (var e = 0; e < t.length && t[e](); ++e); return e - 1 }(this.itemsToPoll.map(function (t) { return t.isDoneFn })), e = 0; e <= t; ++e)(0, this.itemsToPoll[e].resolveFn)(); this.itemsToPoll = this.itemsToPoll.slice(t + 1) }, ba.prototype.addItemToPoll = function (t, e) { var n = this; this.itemsToPoll.push({ isDoneFn: t, resolveFn: e }), 1 < this.itemsToPoll.length || k(function () { return n.pollItems(), 0 === n.itemsToPoll.length }) }, ba.prototype.bindTextureToFrameBuffer = function (t) { this.throwIfDisposed(), Ne(this.gl, this.debug, t, this.framebuffer), this.debug && Me(this.gl) }, ba.prototype.unbindTextureToFrameBuffer = function () { null != this.outputTexture ? (Ne(this.gl, this.debug, this.outputTexture, this.framebuffer), this.debug && Me(this.gl)) : Fe(this.gl, this.debug, this.framebuffer) }, ba.prototype.downloadMatrixDriver = function (t, e) { this.bindTextureToFrameBuffer(t); var n = e(); return this.unbindTextureToFrameBuffer(), n }, ba.prototype.setOutputMatrixTextureDriver = function (t, e, n) { this.throwIfDisposed(); var r = this.gl; Ne(r, this.debug, t, this.framebuffer), this.debug && Me(r), this.outputTexture = t, le(r, this.debug, function () { return r.viewport(0, 0, e, n) }), le(r, this.debug, function () { return r.scissor(0, 0, e, n) }) }, ba.prototype.setOutputMatrixWriteRegionDriver = function (t, e, n, r) { var o = this; this.throwIfDisposed(), le(this.gl, this.debug, function () { return o.gl.scissor(t, e, n, r) }) }, ba.prototype.throwIfDisposed = function () { if (this.disposed) throw new Error("Attempted to use disposed GPGPUContext.") }, ba.prototype.throwIfNoProgram = function () { if (null == this.program) throw new Error("No GPU program is currently set.") }, ba); function ba(t) { this.outputTexture = null, this.program = null, this.disposed = !1, this.vertexAttrsAreBound = !1, this.itemsToPoll = []; var e = _().getNumber("WEBGL_VERSION"); null != t ? oe(e, this.gl = t) : this.gl = ie(e); var n = "WEBGL_color_buffer_float"; if (1 === _().getNumber("WEBGL_VERSION")) { if (this.textureFloatExtension = pe(this.gl, this.debug, "OES_texture_float"), Ke(this.gl, "OES_texture_half_float")) this.textureHalfFloatExtension = pe(this.gl, this.debug, "OES_texture_half_float"); else if (_().get("WEBGL_FORCE_F16_TEXTURES")) throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true."); if (this.colorBufferFloatExtension = this.gl.getExtension(n), Ke(this.gl, "EXT_color_buffer_half_float")) this.colorBufferHalfFloatExtension = pe(this.gl, this.debug, "EXT_color_buffer_half_float"); else if (_().get("WEBGL_FORCE_F16_TEXTURES")) throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.") } else if (n = "EXT_color_buffer_float", Ke(this.gl, n)) this.colorBufferFloatExtension = this.gl.getExtension(n); else { if (!Ke(this.gl, "EXT_color_buffer_half_float")) throw new Error("GL context does not support color renderable floats"); this.colorBufferHalfFloatExtension = this.gl.getExtension("EXT_color_buffer_half_float") } this.vertexBuffer = na(this.gl, this.debug), this.indexBuffer = ra(this.gl, this.debug), this.framebuffer = Re(this.gl, this.debug), this.textureConfig = ce(this.gl, this.textureHalfFloatExtension) } function wa(t, s) { if (t.length !== s.length) throw Error("Binary was compiled with " + t.length + " inputs, but was executed with " + s.length + " inputs"); t.forEach(function (t, e) { var n = t.logicalShape, r = s[e], o = r.shape; if (!A(n, o)) throw Error("Binary was compiled with different shapes than the current args. Shapes " + n + " and " + o + " must match"); if (!t.isUniform || !r.isUniform) { var i = t.texShape, a = r.isUniform ? null : r.texData.texShape; if (!A(i, a)) throw Error("Binary was compiled with different texture shapes than the current args. Shape " + i + " and " + a + " must match") } }) } function Ca(t, e, n) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t; for (var r = n.filterWidth, o = n.inChannels, i = n.strideWidth, a = n.strideHeight, s = n.padInfo, u = n.outWidth, c = n.dilationWidth, l = n.dilationHeight, h = n.dataFormat, f = s.left, p = s.top, d = o * r, v = Jo(), m = "channelsLast" === h, g = m ? 0 : 1, y = m ? 1 : 2, x = "", b = 0; b <= 1; b++)for (var w = 0; w <= 1; w++)x += "\n          blockIndex = rc.y + " + w + ";\n          pos = rc.x + " + b + ";\n\n          if(blockIndex < " + t[1] + " && pos < " + t[0] + ") {\n            offsetY = int(blockIndex / (" + u + ")) * " + a + " - " + p + ";\n            d0 = offsetY + " + l + " * (pos / " + d + ");\n\n            if(d0 < " + e[g] + " && d0 >= 0) {\n\n              offsetX = int(mod(float(blockIndex), " + u + ".) * " + i + ". - " + f + ".);\n              d1 = offsetX + " + c + " * (int(mod(float(pos), " + d + ".) / " + o + ".));\n\n              if(d1 < " + e[y] + " && d1 >= 0) {\n\n                ch = int(mod(float(pos), " + o + ".));\n\n                if (" + m + ") {\n                  innerDims = vec2(d1, ch);\n                  result[" + (2 * b + w) + "] = getChannel(\n                    getA(d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result[" + (2 * b + w) + "] = getChannel(\n                    getA(ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        "; this.userCode = "\n      void main() {\n        ivec2 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        " + x + "\n\n        " + v.output + " = result;\n      }\n    " } function Ea(t, e, n, r, o) { this.variableNames = ["x"], this.outputShape = []; var i, a = e, s = t[3] - 1; this.outputShape = t; var u = "float(" + n + ") + float(" + r + ") * sum"; i = .5 === o ? "inversesqrt(" + u + ")" : 1 === o ? "1.0/(" + u + ")" : "exp(log(" + u + ") * float(-" + o + "));", this.userCode = "\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -" + a + "; j <= " + a + "; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  " + s + ") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * " + i + ";\n        setOutput(val);\n      }\n    " } function _a(t, e, n, r, o) { this.variableNames = ["inputImage", "outputImage", "dy"], this.outputShape = [], this.outputShape = t, this.depth = t[3], this.depthRadius = e, this.bias = n, this.alpha = r, this.beta = o, this.userCode = "\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < " + this.depth + "; ++d) {\n          int depthBegin = int(max(0.0, float(d - " + e + ")));\n          int depthEnd = int(min(float(" + this.depth + "),\n              float(d + " + e + " + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = " + this.depth + ";\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float(" + r + ") * norm + float(" + n + ");\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float(" + r + ")\n                * float(" + o + ")\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * " + o + ");\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    " } function Ia(t, e, n, r, o) { this.variableNames = ["x"], this.outputShape = [], this.packedInputs = !0, this.packedOutput = !0; var i, a = e, s = t[3] - 1; this.outputShape = t; var u = "float(" + n + ") + float(" + r + ") * sum"; i = .5 === o ? "inversesqrt(" + u + ")" : 1 === o ? "1.0/(" + u + ")" : "exp(log(" + u + ") * float(-" + o + "));", this.userCode = "\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < " + this.outputShape[3] + ";\n        bool hasNextRow = c < " + this.outputShape[2] + ";\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - " + a + ";\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - " + a + "; j <= " + a + "; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(" + s + "));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * " + i + ";\n        setOutput(result);\n      }\n    " } function Ra(t) { this.variableNames = ["dy", "maxPos"], this.outputShape = t.inShape; var e = t.strideHeight, n = t.strideWidth, r = t.dilationHeight, o = t.effectiveFilterHeight, i = t.effectiveFilterWidth, a = o - 1 - t.padInfo.top, s = i - 1 - t.padInfo.left, u = o * i - 1; this.userCode = "\n      const ivec2 pads = ivec2(" + a + ", " + s + ");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < " + o + ";\n          wR += " + r + ") {\n          float dyR = float(dyRCorner + wR) / " + e + ".0;\n\n          if (dyR < 0.0 || dyR >= " + t.outHeight + ".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < " + i + "; wC++) {\n            float dyC = float(dyCCorner + wC) / " + n + ".0;\n\n            if (dyC < 0.0 || dyC >= " + t.outWidth + ".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = " + u + " - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * " + i + " + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function ka(t) { this.variableNames = ["dy", "maxPos"], this.outputShape = t.inShape; var e = t.strideDepth, n = t.strideHeight, r = t.strideWidth, o = t.dilationDepth, i = t.dilationHeight, a = t.dilationWidth, s = t.effectiveFilterDepth, u = t.effectiveFilterHeight, c = t.effectiveFilterWidth, l = s - 1 - t.padInfo.front, h = u - 1 - t.padInfo.top, f = c - 1 - t.padInfo.left, p = s * u * c - 1; this.userCode = "\n      const ivec3 pads = ivec3(" + l + ", " + h + ", " + f + ");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < " + s + ";\n           wD += " + o + ") {\n          float dyD = float(dyDCorner + wD) / " + e + ".0;\n\n          if (dyD < 0.0 || dyD >= " + t.outDepth + ".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < " + u + ";\n              wR += " + i + ") {\n            float dyR = float(dyRCorner + wR) / " + n + ".0;\n\n            if (dyR < 0.0 || dyR >= " + t.outHeight + ".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < " + c + ";\n                wC += " + a + ") {\n              float dyC = float(dyCCorner + wC) / " + r + ".0;\n\n              if (dyC < 0.0 || dyC >= " + t.outWidth + ".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = " + p + " -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * " + u + " * " + c + " +\n                  wR * " + c + " + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    " } function Sa(t, e, n, r, o, i, a) { void 0 === n && (n = !1), void 0 === r && (r = !1), void 0 === o && (o = !1), void 0 === i && (i = null), void 0 === a && (a = !1), this.variableNames = ["matrixA", "matrixB"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = e; var s = n ? t[1] : t[2], u = Math.ceil(s / 2), c = n ? "i * 2, rc.y" : "rc.y, i * 2", l = r ? "rc.z, i * 2" : "i * 2, rc.z", h = n ? ["a.xxyy", "a.zzww"] : ["a.xxzz", "a.yyww"], f = r ? ["b.xzxz", "b.ywyw"] : ["b.xyxy", "b.zwzw"], p = "", d = ""; i && (p = a ? "vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          " + i + "\n        }" : "vec4 activation(vec4 x) {\n          " + i + "\n        }", d = "result = activation(result);"); var v = o ? "result += getBiasAtOutCoords();" : ""; o && this.variableNames.push("bias"), a && this.variableNames.push("preluActivationWeights"), this.userCode = "\n      " + p + "\n\n      const float sharedDimension = " + u + ".0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < " + u + "; i++) {\n          vec4 a = getMatrixA(rc.x, " + c + ");\n          vec4 b = getMatrixB(rc.x, " + l + ");\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += (" + h[0] + " * " + f[0] + ");\n          result += (" + h[1] + " * " + f[1] + ");\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        " + v + "\n\n        " + d + "\n\n        setOutput(result);\n      }\n    " } function Da(t, e, n, r) { this.variableNames = ["indices"], this.outputShape = [t, e], this.userCode = "\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float(" + r + "), float(" + n + "),\n                      float(index == coords.y)));\n      }\n    " } function Aa(t) { this.variableNames = ["A"], this.packedInputs = !1, this.packedOutput = !0; var e, n, r, o, i = (this.outputShape = t).length; if (0 === i) this.userCode = "\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      "; else { var a = $o("rc", i), s = oi(i), u = function (t, e, n) { if (1 === t) return "rc > " + e[0]; for (var r = "", o = t - 2; o < t; o++)r += n[o] + " >= " + e[o], o < t - 1 && (r += "||"); return r }(i, t, a), c = function (t, e, n) { if (1 === t) return ""; var r = a.slice(-2); return "\n    int r = " + r[0] + ";\n    int c = " + r[1] + ";\n    int rp1 = r + 1;\n    int cp1 = c + 1;\n\n    bool cEdge = cp1 >= " + e + ";\n    bool rEdge = rp1 >= " + n + ";\n  " }(i, t[t.length - 1], t[t.length - 2]), l = (n = a, r = (e = t).length, o = function (t, e) { for (var n = [], r = 0; r <= 1; r++)for (var o = 0; o <= 1; o++) { for (var i = (0 === r ? "r" : "rp1") + ", " + (0 === o ? "c" : "cp1"), a = 2; a < t; a++)i = e[e.length - 1 - a] + "," + i; n.push(i) } return n }(r, n), 1 === r ? "getA(rc),\n            rc + 1 >= " + e[0] + " ? 0. : getA(rc + 1),\n            0, 0" : "getA(" + o[0] + "),\n          cEdge ? 0. : getA(" + o[1] + "),\n          rEdge ? 0. : getA(" + o[2] + "),\n          rEdge || cEdge ? 0. : getA(" + o[3] + ")"); this.userCode = "\n        void main() {\n          " + s + " rc = getOutputCoords();\n\n          if(" + u + ") {\n            setOutput(vec4(0));\n          } else {\n            " + c + "\n\n            setOutput(vec4(" + l + "));\n          }\n        }\n      " } } var Ta = (Na.prototype.getCustomSetupFunc = function (n) { var r = this; return function (t, e) { null == r.seedLoc && (r.seedLoc = t.getUniformLocation(e, "seed")), t.gl.uniform1f(r.seedLoc, n) } }, Na); function Na(t, e, n) { this.variableNames = ["probs"], this.outputShape = [t, n], this.userCode = "\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < " + (e - 1) + "; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float(" + (e - 1) + "));\n      }\n    " } function Fa(n, t, e) { this.variableNames = ["x"], this.outputShape = t.map(function (t, e) { return t[0] + n[e] + t[1] }); var r = n.length, o = oi(r), i = t.map(function (t) { return t[0] }).join(","), a = t.map(function (t, e) { return t[0] + n[e] }).join(","), s = ["coords[0]", "coords[1]", "coords[2]", "coords[3]"].slice(0, r); this.userCode = 1 !== r ? "\n      " + o + " start = " + o + "(" + i + ");\n      " + o + " end = " + o + "(" + a + ");\n\n      void main() {\n        " + o + " outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float(" + e + "));\n        } else {\n          " + o + " coords = outC - start;\n          setOutput(getX(" + s + "));\n        }\n      }\n    " : "\n        int start = " + i + ";\n        int end = " + a + ";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float(" + e + "));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      " } function Ma(n, t, e) { this.variableNames = ["x"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t.map(function (t, e) { return t[0] + n[e] + t[1] }); for (var r = n.length, o = oi(r), i = t.map(function (t) { return t[0] }).join(","), a = t.map(function (t, e) { return t[0] + n[e] }).join(","), s = $o("rc", r), u = $o("source", r), c = s[r - 1] + " < " + this.outputShape[r - 1], l = 1 === r ? "source" : "vec2(" + u.slice(-2).join() + ")", h = [o + " rc = outputLoc;", s[r - 1] + " += 1;\n       if(" + c + ") {\n      ", 1 === r ? "" : "}\n       rc = outputLoc;\n       " + s[r - 2] + " += 1;\n       if(" + s[r - 2] + " < " + this.outputShape[r - 2] + ") {", 1 === r ? "" : "  " + s[r - 1] + " += 1;\n         if(" + c + ") {"], f = 1 === r ? "rc < start || rc >= end" : "any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))", p = "", d = 0, v = 1 === r ? 2 : 4; d < v; d++)p += "\n        " + h[d] + "\n        if (" + f + ") {\n          result[" + d + "] = float(" + e + ");\n        } else {\n          " + o + " source = rc - start;\n          result[" + d + "] = getChannel(getX(" + u.join() + "), " + l + ");\n        }\n      "; p += 1 === r ? "} " : "}}", this.userCode = "\n      const " + o + " start = " + o + "(" + i + ");\n      const " + o + " end = " + o + "(" + a + ");\n\n      void main() {\n        " + o + " outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        " + p + "\n        setOutput(result);\n      }\n    " } function Oa(t, e, n) { if (this.variableNames = ["x"], "avg" === e && n) throw new Error("Cannot compute positions for average pool."); var r = t.filterWidth, o = t.strideHeight, i = t.strideWidth, a = t.dilationHeight, s = t.dilationWidth, u = t.effectiveFilterHeight, c = t.effectiveFilterWidth, l = t.padInfo.top, h = t.padInfo.left; this.outputShape = t.outShape; var f = "avg" === e, p = "0.0"; if (f || (p = "-1.0 / 1e-20"), n) this.userCode = "\n        const ivec2 strides = ivec2(" + o + ", " + i + ");\n        const ivec2 pads = ivec2(" + l + ", " + h + ");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < " + u + ";\n              wR += " + a + ") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= " + t.inHeight + ") {\n              continue;\n            }\n\n            for (int wC = 0; wC < " + c + ";\n                wC += " + s + ") {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= " + t.inWidth + ") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value >= currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * " + c + " + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      "; else { var d = e + "(" + e + "(" + e + "(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])"; "avg" === e && (d = "avgValue / count"); var v = 4 * Math.floor(r / 4), m = r % 4, g = "\n      if (" + f + ") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    "; this.userCode = "\n      const ivec2 strides = ivec2(" + o + ", " + i + ");\n      const ivec2 pads = ivec2(" + l + ", " + h + ");\n      const float initializationValue = " + p + ";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= " + t.inWidth + ") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(" + p + ");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < " + u + ";\n            wR += " + a + ") {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= " + t.inHeight + ") {\n            continue;\n          }\n\n          for (int wC = 0; wC < " + v + "; wC += 4) {\n            int xC = xCCorner + wC * " + s + ";\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + " + s + ", d),\n              getValue(batch, xR, xC + 2 * " + s + ", d),\n              getValue(batch, xR, xC + 3 * " + s + ", d)\n            );\n\n            " + g + "\n          }\n\n          int xC = xCCorner + " + v + ";\n          if (" + (1 == m) + ") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            " + g + "\n          } else if (" + (2 == m) + ") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + " + s + ", d),\n              initializationValue,\n              initializationValue\n            );\n\n            " + g + "\n          } else if (" + (3 == m) + ") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + " + s + ", d),\n              getValue(batch, xR, xC + 2 * " + s + ", d),\n              initializationValue\n            );\n\n            " + g + "\n          }\n        }\n        setOutput(" + d + ");\n      }\n    " } } function Pa(t, e, n) { if (this.variableNames = ["x"], "avg" === e && n) throw new Error("Cannot compute positions for average pool."); var r = t.filterWidth, o = t.strideDepth, i = t.strideHeight, a = t.strideWidth, s = t.dilationDepth, u = t.dilationHeight, c = t.dilationWidth, l = t.effectiveFilterDepth, h = t.effectiveFilterHeight, f = t.effectiveFilterWidth, p = t.padInfo.front, d = t.padInfo.top, v = t.padInfo.left; this.outputShape = t.outShape; var m = "avg" === e, g = "0.0"; if (m || (g = "-1.0 / 1e-20"), n) this.userCode = "\n        const ivec3 strides =\n            ivec3(" + o + ", " + i + ", " + a + ");\n        const ivec3 pads = ivec3(" + p + ", " + d + ", " + v + ");\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < " + l + ";\n              wD += " + s + ") {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= " + t.inDepth + ") {\n              continue;\n            }\n\n            for (int wR = 0; wR < " + h + ";\n                wR += " + u + ") {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= " + t.inHeight + ") {\n                continue;\n              }\n\n              for (int wC = 0; wC < " + f + ";\n                  wC += " + c + ") {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= " + t.inWidth + ") {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value >= currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition =\n                      wD * " + h + " * " + f + " +\n                      wR * " + f + " + wC;;\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      "; else { var y = e + "(" + e + "(" + e + "(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])"; "avg" === e && (y = "avgValue / count"); var x = 4 * Math.floor(r / 4), b = r % 4, w = "\n      if (" + m + ") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    "; this.userCode = "\n      const ivec3 strides =\n        ivec3(" + o + ", " + i + ", " + a + ");\n      const ivec3 pads = ivec3(" + p + ", " + d + ", " + v + ");\n      const float initializationValue = " + g + ";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= " + t.inWidth + ") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(" + g + ");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < " + l + ";\n            wD += " + s + ") {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= " + t.inDepth + ") {\n            continue;\n          }\n\n          for (int wR = 0; wR < " + h + ";\n            wR += " + u + ") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= " + t.inHeight + ") {\n              continue;\n            }\n\n            for (int wC = 0; wC < " + x + "; wC += 4) {\n              int xC = xCCorner + wC * " + c + ";\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + " + c + ", ch),\n                getValue(batch, xD, xR, xC + 2 * " + c + ", ch),\n                getValue(batch, xD, xR, xC + 3 * " + c + ", ch)\n              );\n\n              " + w + "\n            }\n\n            int xC = xCCorner + " + x + ";\n            if (" + (1 == b) + ") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              " + w + "\n            } else if (" + (2 == b) + ") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + " + c + ", ch),\n                initializationValue,\n                initializationValue\n              );\n\n              " + w + "\n            } else if (" + (3 == b) + ") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + " + c + ", ch),\n                getValue(batch, xD, xR, xC + 2 * " + c + ", ch),\n                initializationValue\n              );\n\n              " + w + "\n            }\n          }\n          setOutput(" + y + ");\n        }\n      }\n    " } } function Ba(t, e) { this.variableNames = ["x"]; var n = t.windowSize, r = t.batchSize, o = t.inSize, i = Math.ceil(o / n); this.outputShape = [r, i]; var a = "0.0", s = ""; "prod" === e ? a = "1.0" : "min" === e ? (a = "1.0 / 1e-20", s = "min") : "max" === e && (a = "-1.0 / 1e-20", s = "max"); var u = e + "(" + e + "(" + e + "(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])"; "sum" === e ? u = "sumValue" : "prod" === e ? u = "prodValue" : "all" === e ? u = "allValue" : "any" === e && (u = "anyValue"); var c = 4 * Math.floor(n / 4), l = n % 4, h = "\n      if (" + ("sum" === e) + ") {\n        sumValue += dot(values, ones);\n      } else if (" + ("prod" === e) + ") {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = " + s + "(values, minMaxValue);\n      }\n    ", f = "vec4"; "all" === e ? (a = "1.0", h = "\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ", f = "bvec4") : "any" === e && (a = "0.0", h = "\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ", f = "bvec4"); var p = ""; 0 < o % n && (p = "\n        if (inIdx < 0 || inIdx >= " + o + ") {\n          return initializationValue;\n        }\n      "), this.userCode = "\n      const float initializationValue = " + a + ";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        " + p + "\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * " + n + ";\n\n        vec4 minMaxValue = vec4(" + a + ");\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < " + c + "; i += 4) {\n          int inIdx = inOffset + i;\n          " + f + " values = " + f + "(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          " + h + "\n        }\n\n        int inIdx = inOffset + " + c + ";\n        if (" + (1 == l) + ") {\n          " + f + " values = " + f + "(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          " + h + "\n        } else if (" + (2 == l) + ") {\n          " + f + " values = " + f + "(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          " + h + "\n        } else if (" + (3 == l) + ") {\n          " + f + " values = " + f + "(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          " + h + "\n        }\n        setOutput(" + u + ");\n      }\n    " } function La(t, e) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t; for (var n = "", r = 0; r < 4; r++) { var o = "thisRC = rc;"; r % 2 == 1 && (o += "thisRC.z += 1;"), 1 < r && (o += "thisRC.y += 1;"), n += "\n        " + o + "\n        " + (0 < r ? "if(thisRC.y < rows && thisRC.z < cols){" : "") + "\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result[" + r + "] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        " + (0 < r ? "}" : "") + "\n      " } this.userCode = "\n      \n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      " + Qo(["r", "c", "d"], e) + "\n      return ivec3(r, c, d);\n    }\n  \n      " + Zo(t) + "\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = " + t[1] + ";\n        int cols = " + t[2] + ";\n\n        " + n + "\n\n        setOutput(result);\n      }\n    " } function Wa(t, e, n) { this.variableNames = ["dy"], this.outputShape = [], this.outputShape = e.shape; var r = e.shape, o = r[1], i = r[2], a = t.shape, s = a[1], u = a[2], c = [n && 1 < s ? o - 1 : o, n && 1 < u ? i - 1 : i], l = [n && 1 < s ? s - 1 : s, n && 1 < u ? u - 1 : u], h = c[0] / l[0], f = c[1] / l[1], p = 1 / h, d = 1 / f, v = 2 * Math.ceil(p) + 2, m = 2 * Math.ceil(d) + 2; this.userCode = "\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(" + h + ");\n        const float widthScale = float(" + f + ");\n\n        const float invHeightScale = float(" + p + ");\n        const float invWidthScale = float(" + d + ");\n\n        const int winHeight = int(" + v + ");\n        const int winWidth = int(" + m + ");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= " + s + ") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= " + u + ") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), " + (o - 1) + ".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), " + (i - 1) + ".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    " } function za(t, e, n, r) { this.variableNames = ["A"], this.outputShape = []; var o = t[0], i = t[1], a = t[2], s = t[3]; this.outputShape = [o, e, n, s]; var u = [r && 1 < e ? i - 1 : i, r && 1 < n ? a - 1 : a], c = [r && 1 < e ? e - 1 : e, r && 1 < n ? n - 1 : n]; this.userCode = "\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          " + u[0] / c[0] + ",\n          " + u[1] / c[1] + ");\n      const vec2 inputShapeRC = vec2(" + i + ".0, " + a + ".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    " } function Ua(t, e, n, r) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = []; var o = t[0], i = t[1], a = t[2], s = t[3]; this.outputShape = [o, e, n, s]; var u = [r && 1 < e ? i - 1 : i, r && 1 < n ? a - 1 : a], c = [r && 1 < e ? e - 1 : e, r && 1 < n ? n - 1 : n]; this.userCode = "\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          " + u[0] / c[0] + ",\n          " + u[1] / c[1] + ",\n          " + u[1] / c[1] + ");\n      const vec3 inputShapeRC = vec3(" + i + ".0, " + a + ".0,\n                                     " + a + ".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < " + (s - 1) + ";\n        bool hasNextRow = coords.z < " + (n - 1) + ";\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    " } function Va(t, e, n) { this.variableNames = ["dy"], this.outputShape = [], this.outputShape = e.shape; var r = e.shape, o = r[1], i = r[2], a = t.shape, s = a[1], u = a[2], c = [n && 1 < s ? o - 1 : o, n && 1 < u ? i - 1 : i], l = [n && 1 < s ? s - 1 : s, n && 1 < u ? u - 1 : u], h = c[0] / l[0], f = c[1] / l[1], p = 1 / h, d = 1 / f, v = 2 * Math.ceil(p) + 2, m = 2 * Math.ceil(d) + 2; this.userCode = "\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(" + h + ");\n        const float widthScale = float(" + f + ");\n\n        const float invHeightScale = float(" + p + ");\n        const float invWidthScale = float(" + d + ");\n\n        const int winHeight = int(" + v + ");\n        const int winWidth = int(" + m + ");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= " + s + ") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= " + u + ") {\n              continue;\n            }\n\n            float sourceFracRow =\n              float(" + c[0] + ") *\n                (float(dyR) / float(" + l[0] + "));\n\n            float sourceFracCol =\n                float(" + c[1] + ") *\n                  (float(dyC) / float(" + l[1] + "));\n\n            int sourceNearestRow = int(min(\n                float(int(" + o + ") - 1),\n                " + n + " ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int(" + i + ") - 1),\n                " + n + " ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    " } function Ga(t, e, n, r) { this.variableNames = ["A"], this.outputShape = []; var o = t[0], i = t[1], a = t[2], s = t[3]; this.outputShape = [o, e, n, s]; var u = [r && 1 < e ? i - 1 : i, r && 1 < n ? a - 1 : a], c = [r && 1 < e ? e - 1 : e, r && 1 < n ? n - 1 : n], l = r ? "0.5" : "0.0"; this.userCode = "\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          " + u[0] / c[0] + ",\n          " + u[1] / c[1] + ");\n      const vec2 inputShapeRC = vec2(" + i + ".0, " + a + ".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + " + l + ")));\n\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    " } function Ha(r, o) { this.variableNames = ["x"]; var t = r.length; if (4 < t) throw new Error("WebGL backend: Reverse of rank-" + t + " tensor is not yet supported"); if (this.outputShape = r, 1 !== t) { var e = r.map(function (t, e) { return n = e, -1 !== o.indexOf(n) && 1 !== r[n] ? r[n] + " - coords[" + n + "] - 1" : "coords[" + n + "]"; var n }).join(","), n = oi(t); this.userCode = "\n      void main() {\n        " + n + " coords = getOutputCoords();\n        setOutput(getX(" + e + "));\n      }\n    " } else this.userCode = "\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX(" + r[0] + " - coord - 1));\n        }\n      " } function qa(i, a) { this.variableNames = ["x"], this.packedInputs = !0, this.packedOutput = !0; var t = i.length; if (4 < t) throw new Error("WebGL backend: Reverse of rank-" + t + " tensor is not yet supported"); this.outputShape = i; var e, n, r, o = $o("rc", t), s = o[t - 1] + " + 1 < " + this.outputShape[t - 1], u = o[t - 2] + " + 1 < " + this.outputShape[t - 2], c = oi(t); function l(o) { var t = i.map(function (t, e) { return n = e, r = o, -1 !== a.indexOf(n) && 1 !== i[n] ? i[n] + " - " + r[n] + " - 1" : "" + r[n]; var n, r }); return "getChannel(getX(" + t.join(",") + "), vec2(" + t.slice(-2).join(",") + "))" } this.userCode = 1 === t ? "\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX(" + i[0] + " - rc - 1),\n            " + i[0] + " - rc - 1);\n          if(" + s + "){\n              result.g = getChannel(getX(" + i[0] + " - (rc  + 1) - 1),\n                " + i[0] + " - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      " : "\n        void main() {\n          " + c + " rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = " + l(o.slice()) + ";\n          if(" + s + "){\n            result.g = " + ((r = o.slice())[t - 1] = "(" + r[t - 1] + " + 1)", l(r)) + ";\n          }\n          if(" + u + ") {\n            result.b = " + ((n = o.slice())[t - 2] = "(" + n[t - 2] + " + 1)", l(n)) + ";\n            if(" + s + ") {\n              result.a = " + ((e = o.slice())[t - 1] = "(" + e[t - 1] + " + 1)", e[t - 2] = "(" + e[t - 2] + " + 1)", l(e)) + ";\n            }\n          }\n          setOutput(result);\n        }\n    " } function ja(t, e, n, r, o, i, a) { this.variableNames = ["updates", "indices", "defaultValue"], this.outputShape = i; var s = oi(o.length), u = oi(i.length), c = ""; 1 === n ? c = "i" : 2 === n && (c = "i, j"); var l = "getIndices(" + c + ")", h = ""; 1 === r ? h = "i" : 2 === r && (h = "i, coords[1]"); var f = "getUpdates(" + h + ")", p = 1 < e ? "strides[j]" : "strides"; this.userCode = "\n        " + s + " strides = " + s + "(" + o + ");\n\n        void main() {\n          " + u + " coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < " + t + "; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < " + e + "; j++) {\n              int index = round(" + l + ");\n              flattenedIndex += index * " + p + ";\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += " + f + ";\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      " } function Ka(t, e) { this.variableNames = ["x", "segmentIds"]; var n = t.windowSize, r = t.batchSize, o = t.inSize, i = t.numSegments, a = i * Math.ceil(o / n); this.outputShape = [r, a]; var s = 4 * Math.floor(n / 4), u = n % 4, c = "\n        sumValue += dot(values, segFilter);\n    ", l = ""; 0 < o % n && (l = "\n        if (inIdx < 0 || inIdx >= " + o + ") {\n          return initializationValue;\n        }\n      "); var h = ""; 0 < o % n && (h = "\n        if (inIdx < 0 || inIdx >= " + o + ") {\n          return -1.0;\n        }\n      "), this.userCode = "\n      const float initializationValue = 0.0;\n\n      float getValue(int batch, int inIdx) {\n        " + l + "\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        " + h + "\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          " + i + ")) * float(" + n + "));\n        int currentSeg = int(mod(float(outIdx), float(" + i + ")));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < " + s + "; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          " + c + "\n        }\n\n        int inIdx = inOffset + " + s + ";\n        if (" + (1 == u) + ") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          " + c + "\n        } else if (" + (2 == u) + ") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          " + c + "\n        } else if (" + (3 == u) + ") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          " + c + "\n        }\n        setOutput(sumValue);\n      }\n    " } function Xa(t, e, n) { var r, o; if (this.variableNames = ["c", "a", "b"], this.outputShape = e, 4 < n) throw Error("Where for rank " + n + " is not yet supported"); if (1 === n) r = o = "resRC"; else { for (var i = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"], a = [], s = [], u = 0; u < e.length; u++)s.push("" + i[u]), u < t && a.push("" + i[u]); r = a.join(), o = s.join() } var c = oi(n); this.userCode = "\n      void main() {\n        " + c + " resRC = getOutputCoords();\n        float cVal = getC(" + r + ");\n        if (cVal >= 1.0) {\n          setOutput(getA(" + o + "));\n        } else {\n          setOutput(getB(" + o + "));\n        }\n      }\n    " } var Ya = (Ja.prototype.getCustomSetupFunc = function (n) { var r = this; if (n.length !== this.rank) throw Error("The rank (" + this.rank + ") of the program must match the length of start (" + n.length + ")"); return function (t, e) { null == r.startLoc && (r.startLoc = t.getUniformLocationNoThrow(e, "start"), null == r.startLoc) || t.gl.uniform1iv(r.startLoc, n) } }, Ja), $a = ["x", "y", "z", "w", "u", "v"]; function Ja(t) { this.variableNames = ["source"], this.outputShape = t, this.rank = t.length; var e, n = oi(this.rank), r = "uniform int start[" + this.rank + "];", o = function (t) { if (1 === t) return "sourceLoc"; if (t <= 6) return $a.slice(0, t).map(function (t) { return "sourceLoc." + t }).join(","); throw Error("Slicing for rank " + t + " is not yet supported") }(this.rank); e = "\n        " + n + " sourceLoc;\n        " + n + " coords = getOutputCoords();\n        " + t.map(function (t, e) { return "sourceLoc." + $a[e] + " = start[" + e + "] + coords." + $a[e] + ";" }).join("\n") + "\n      ", this.userCode = "\n      " + r + "\n      void main() {\n        " + e + "\n        setOutput(getSource(" + o + "));\n      }\n    " } function Qa(t, e, n) { this.variableNames = ["x"]; var r = (this.outputShape = n).length, o = oi(n.length), i = oi(n.length), a = ""; if (1 === r) a = "coords * strides + begin"; else { var s = 0; a = n.map(function (t, e) { return s++, 1 === n.length ? "coords * strides[" + e + "] + begin[" + e + "]" : "coords[" + (s - 1) + "] * strides[" + e + "] + begin[" + e + "]" }).join(",") } this.userCode = "\n      " + o + " begin = " + o + "(" + t + ");\n      " + o + " strides = " + o + "(" + e + ");\n\n      void main() {\n        " + i + " coords = getOutputCoords();\n        setOutput(getX(" + a + "));\n      }\n    " } var Za = (ns.prototype.getCustomSetupFunc = function (n) { var r = this; if (n.length !== this.rank) throw Error("The rank (" + this.rank + ") of the program must match the length of start (" + n.length + ")"); return function (t, e) { null == r.startLoc && (r.startLoc = t.getUniformLocationNoThrow(e, "start"), null == r.startLoc) || t.gl.uniform1iv(r.startLoc, n) } }, ns), ts = (es.prototype.acquireTexture = function (t, e, n) { var r, o = rs(e, n), i = os(t, o, n); if (i in this.freeTextures || (this.freeTextures[i] = []), i in this.usedTextures || (this.usedTextures[i] = []), 0 < this.freeTextures[i].length) { this.numFreeTextures--, this.numUsedTextures++, this.log(); var a = this.freeTextures[i].shift(); return this.usedTextures[i].push(a), a } return this.numUsedTextures++, this.log(), o === Qt.PACKED_2X2_FLOAT32 ? r = this.gpgpu.createPackedMatrixTexture(t[0], t[1]) : o === Qt.PACKED_2X2_FLOAT16 ? r = this.gpgpu.createFloat16PackedMatrixTexture(t[0], t[1]) : o === Qt.UNPACKED_FLOAT32 ? r = this.gpgpu.createFloat32MatrixTexture(t[0], t[1]) : o === Qt.UNPACKED_FLOAT16 ? r = this.gpgpu.createFloat16MatrixTexture(t[0], t[1]) : o === Qt.PACKED_4X1_UNSIGNED_BYTE && (r = this.gpgpu.createUnsignedBytesMatrixTexture(t[0], t[1])), this.usedTextures[i].push(r), r }, es.prototype.releaseTexture = function (t, e, n, r) { if (null != this.freeTextures) { var o = os(e, rs(n, r), r); o in this.freeTextures || (this.freeTextures[o] = []), this.freeTextures[o].push(t), this.numFreeTextures++, this.numUsedTextures--; var i = this.usedTextures[o], a = i.indexOf(t); if (a < 0) throw new Error("Cannot release a texture that was never provided by this texture manager"); i.splice(a, 1), this.log() } }, es.prototype.log = function () { if (this.logEnabled) { var t = this.numFreeTextures + this.numUsedTextures; console.log("Free/Used", this.numFreeTextures + " / " + this.numUsedTextures, "(" + t + ")") } }, es.prototype.getNumUsedTextures = function () { return this.numUsedTextures }, es.prototype.getNumFreeTextures = function () { return this.numFreeTextures }, es.prototype.dispose = function () { var e = this; if (null != this.freeTextures) { for (var t in this.freeTextures) this.freeTextures[t].forEach(function (t) { e.gpgpu.deleteMatrixTexture(t) }); for (var t in this.usedTextures) this.usedTextures[t].forEach(function (t) { e.gpgpu.deleteMatrixTexture(t) }); this.freeTextures = null, this.usedTextures = null, this.numUsedTextures = 0, this.numFreeTextures = 0 } }, es); function es(t) { this.gpgpu = t, this.numUsedTextures = 0, this.numFreeTextures = 0, this.freeTextures = {}, this.logEnabled = !1, this.usedTextures = {} } function ns(t) { this.variableNames = ["source"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t, this.rank = t.length; var e = oi(this.rank), n = $o("coords", this.rank), r = $o("sourceLoc", this.rank), o = 1 === this.rank ? "sourceLoc" : "vec2(" + r.slice(-2).join() + ")", i = "getChannel(getSource(" + r.join() + "), " + o + ")", a = "\n      result.x = " + i + ";\n      if (++" + n[this.rank - 1] + " < " + t[this.rank - 1] + ") {\n        ++" + r[this.rank - 1] + ";\n        result.y = " + i + ";\n        --" + r[this.rank - 1] + ";\n      }\n    ", s = 1 === this.rank ? "" : "\n      --" + n[this.rank - 1] + ";\n      if (++" + n[this.rank - 2] + " < " + t[this.rank - 2] + ") {\n        ++" + r[this.rank - 2] + ";\n        result.z = " + i + ";\n        if (++" + n[this.rank - 1] + " < " + t[this.rank - 1] + ") {\n          ++" + r[this.rank - 1] + ";\n          result.w = " + i + ";\n        }\n      }\n    ", u = this.rank <= 4 ? "sourceLoc = coords +\n            " + e + "(" + t.map(function (t, e) { return "start[" + e + "]" }).join() + ");" : t.map(function (t, e) { return r[e] + " = " + n[e] + " + start[" + e + "];" }).join("\n"); this.userCode = "\n      uniform int start[" + this.rank + "];\n      void main() {\n        " + e + " coords = getOutputCoords();\n        " + e + " sourceLoc;\n        " + u + "\n        vec4 result = vec4(0.);\n        " + a + "\n        " + s + "\n        setOutput(result);\n      }\n    " } function rs(t, e) { if (t === Jt.UPLOAD) return Qt.PACKED_2X2_FLOAT32; if (t === Jt.RENDER || null == t) return n = e, _().getBool("WEBGL_RENDER_FLOAT32_ENABLED") ? n ? Qt.PACKED_2X2_FLOAT32 : Qt.UNPACKED_FLOAT32 : n ? Qt.PACKED_2X2_FLOAT16 : Qt.UNPACKED_FLOAT16; var n; if (t === Jt.DOWNLOAD || t === Jt.PIXELS) return Qt.PACKED_4X1_UNSIGNED_BYTE; throw new Error("Unknown logical texture type " + t) } function os(t, e, n) { return t[0] + "_" + t[1] + "_" + e + "_" + n } function is(t, e) { this.variableNames = ["A"]; for (var n = new Array(t.length), r = 0; r < n.length; r++)n[r] = t[r] * e[r]; this.outputShape = n, this.rank = n.length; var o = oi(this.rank), i = function (t) { var e = t.length; if (5 < e) throw Error("Tile for rank " + e + " is not yet supported"); if (1 === e) return "imod(resRC, " + t[0] + ")"; for (var n = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u"], r = [], o = 0; o < t.length; o++)r.push("imod(" + n[o] + ", " + t[o] + ")"); return r.join() }(t); this.userCode = "\n      void main() {\n        " + o + " resRC = getOutputCoords();\n        setOutput(getA(" + i + "));\n      }\n    " } function as(t, e) { this.variableNames = ["A"]; for (var n = new Array(t.length), r = 0; r < n.length; r++)n[r] = t[e[r]]; this.outputShape = n, this.rank = n.length; var o = oi(this.rank), i = function (t) { var e = t.length; if (6 < e) throw Error("Transpose for rank " + e + " is not yet supported"); for (var n = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u", "resRC.v"], r = new Array(e), o = 0; o < t.length; o++)r[t[o]] = n[o]; return r.join() }(e); this.userCode = "\n    void main() {\n      " + o + " resRC = getOutputCoords();\n      setOutput(getA(" + i + "));\n    }\n    " } function ss(t, e) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0; for (var n = new Array(t.length), r = 0; r < n.length; r++)n[r] = t[e[r]]; if (this.outputShape = n, this.rank = n.length, 6 < this.rank) throw Error("Packed transpose for rank " + this.rank + " is not yet supported."); var o = oi(this.rank), i = Yo("rc", this.rank), a = new Array(this.rank); for (r = 0; r < e.length; r++)a[e[r]] = i[r]; var s = "vec2(" + a.slice(-2).join() + ")", u = "++" + i[this.rank - 1] + " < " + n[this.rank - 1], c = "getChannel(getA(" + a.join() + "), " + s + ")"; this.userCode = "\n    void main() {\n      " + o + " rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = " + c + ";\n      if(" + u + ") {\n        result[1] = " + c + ";\n      }\n      --" + i[this.rank - 1] + ";\n      if(++" + i[this.rank - 2] + " < " + n[this.rank - 2] + ") {\n        result[2] = " + c + ";\n        if(" + u + ") {\n          result[3] = " + c + ";\n        }\n      }\n      setOutput(result);\n    }\n    " } function us(t, e) { this.variableNames = ["A"], this.outputShape = t, this.userCode = "\n      float unaryOperation(float x) {\n        " + e + "\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    " } function cs(t, e) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !0, this.outputShape = t, this.userCode = "\n      vec4 unaryOperation(vec4 x) {\n        " + e + "\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    " } function ls(t) { this.variableNames = ["A"], this.packedInputs = !0, this.packedOutput = !1; var e = (this.outputShape = t).length, n = $o("rc", e), r = oi(e), o = function (t, e) { if (1 === t) return "rc"; for (var n = "", r = 0; r < t; r++)n += e[r], r < t - 1 && (n += ","); return n }(e, n), i = n.slice(-2), a = e <= 1 ? "rc" : "vec2(" + i.join(",") + ")"; this.userCode = "\n      void main() {\n        " + r + " rc = getOutputCoords();\n        vec4 packedInput = getA(" + o + ");\n\n        setOutput(getChannel(packedInput, " + a + "));\n      }\n    " } var hs = 1.7580993408473768, fs = 1.0507009873554805, ps = "if (isnan(x)) return x;", ds = "return abs(x);", vs = ps + "\n  return (x < 0.0) ? 0.0 : x;\n", ms = ps + "\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n", gs = "return (x >= 0.0) ? x : (exp(x) - 1.0);", ys = "return -x;", xs = "return ceil(x);", bs = "return floor(x);", ws = "return exp(x);", Cs = "return exp(x) - 1.0;", Es = "return x;", _s = "\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n", Is = "\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n", Rs = "\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n", ks = {}; function Ss(t, e) { if (void 0 === e && (e = !1), "linear" === t) return "return x;"; if ("relu" === t) return e ? _s : vs; if ("elu" === t) return e ? Rs : gs; if ("relu6" === t) return e ? Is : ms; if ("prelu" === t) return e ? Ci : wi; throw new Error("Activation " + t + " has not been implemented for the WebGL backend.") } var Ds, As = (t(Ts, Ds = lo), Ts.prototype.numDataIds = function () { return this.texData.numDataIds() + (this.cpuBackend ? this.cpuBackend.numDataIds() : 0) - this.pendingDeletes }, Ts.prototype.write = function (t, e, n) { if (_().getBool("DEBUG") && this.checkNumericalProblems(t), "complex64" === n && null != t) throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag)."); var r = {}; return this.texData.set(r, { shape: e, dtype: n, values: t, usage: Jt.UPLOAD }), r }, Ts.prototype.move = function (t, e, n, r) { if (_().getBool("DEBUG") && this.checkNumericalProblems(e), "complex64" === r) throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag)."); this.texData.set(t, { shape: n, dtype: r, values: e, usage: Jt.UPLOAD }) }, Ts.prototype.readSync = function (t) { var e = this.texData.get(t), n = e.values, r = e.dtype, o = e.complexTensors, i = e.slice, a = e.shape, s = e.isPacked; if (null != i) { var u; u = s ? new cs(a, Es) : new us(a, Es); var c = this.runWebGLProgram(u, [{ dataId: t, shape: a, dtype: r }], r), l = this.readSync(c.dataId); return this.disposeData(c.dataId), l } if (null != n) return this.convertAndCacheOnCPU(t); if ("string" === r) return n; var h, f, p = null != this.activeTimers; return p && (h = tt()), f = "complex64" === r ? Mo(o.real.dataSync(), o.imag.dataSync()) : this.getValuesFromTexture(t), p && (this.downloadWaitMs += tt() - h), this.convertAndCacheOnCPU(t, f) }, Ts.prototype.read = function (E) { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p, d, v, m, g, y, x, b, w, C; return R(this, function (t) { switch (t.label) { case 0: if (this.pendingRead.has(E)) return e = this.pendingRead.get(E), [2, new Promise(function (t) { return e.push(t) })]; if (n = this.texData.get(E), r = n.values, o = n.shape, i = n.slice, a = n.dtype, s = n.complexTensors, u = n.isPacked, null != i) return c = u ? new cs(o, Es) : new us(o, Es), l = this.runWebGLProgram(c, [{ dataId: E, shape: o, dtype: a }], a), h = this.read(l.dataId), this.disposeData(l.dataId), [2, h]; if (null != r) return [2, this.convertAndCacheOnCPU(E)]; if (!_().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED") && 2 === _().getNumber("WEBGL_VERSION")) throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported."); return f = null, "complex64" !== a && _().get("WEBGL_BUFFER_SUPPORTED") && (p = this.decode(E), d = this.texData.get(p.dataId), f = (C = this.gpgpu).createBufferFromTexture.apply(C, [d.texture].concat(se(o)))), this.pendingRead.set(E, []), "complex64" === a ? [3, 2] : [4, this.gpgpu.createAndWaitForFence()]; case 1: t.sent(), t.label = 2; case 2: return "complex64" !== a ? [3, 4] : [4, Promise.all([s.real.data(), s.imag.data()])]; case 3: return m = t.sent(), g = m[0], y = m[1], v = Mo(g, y), [3, 5]; case 4: v = null == f ? this.getValuesFromTexture(E) : (x = L(o), this.gpgpu.downloadFloat32MatrixFromBuffer(f, x)), t.label = 5; case 5: return null != p && this.disposeData(p.dataId), b = this.convertAndCacheOnCPU(E, v), w = this.pendingRead.get(E), this.pendingRead.delete(E), w.forEach(function (t) { return t(b) }), this.pendingDisposal.has(E) && (this.pendingDisposal.delete(E), this.disposeData(E), this.pendingDeletes--), [2, b] } }) }) }, Ts.prototype.checkNumericalProblems = function (t) { if (null != t) for (var e = 0; e < t.length; e++) { var n = t[e]; if (!he(n)) { if (_().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")) throw Error("The value " + n + " cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'"); throw Error("The value " + n + " cannot be represented on this device.") } } }, Ts.prototype.getValuesFromTexture = function (t) { var e, n = this.texData.get(t), r = n.shape, o = n.dtype, i = n.isPacked, a = L(r); if (_().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")) { var s = this.decode(t), u = this.texData.get(s.dataId), c = (e = this.gpgpu).downloadMatrixFromPackedTexture.apply(e, [u.texture].concat(se(r))).subarray(0, a); return this.disposeData(s.dataId), c } var l = _().getBool("WEBGL_PACK") && !0 === i, h = l ? ze(r) : r, f = l ? new qi(h) : new Hi(h), p = this.runWebGLProgram(f, [{ shape: h, dtype: o, dataId: t }], "float32"), d = this.texData.get(p.dataId), v = this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(d.texture, d.texShape[0], d.texShape[1]).subarray(0, a); return this.disposeData(p.dataId), v }, Ts.prototype.time = function (u) { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s; return R(this, function (t) { switch (t.label) { case 0: return e = this.activeTimers, r = !(n = []), null == this.programTimersStack ? (this.programTimersStack = n, r = !0) : this.activeTimers.push(n), this.activeTimers = n, u(), o = b(this.activeTimers.map(function (t) { return t.query })).filter(function (t) { return null != t }), i = b(this.activeTimers.map(function (t) { return t.name })).filter(function (t) { return null != t }), this.activeTimers = e, r && (this.programTimersStack = null), a = { uploadWaitMs: this.uploadWaitMs, downloadWaitMs: this.downloadWaitMs, kernelMs: null, wallMs: null }, 0 < _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") ? [4, Promise.all(o)] : [3, 2]; case 1: return s = t.sent(), a.kernelMs = v(s), a.getExtraProfileInfo = function () { return s.map(function (t, e) { return { name: i[e], ms: t } }).map(function (t) { return t.name + ": " + t.ms }).join(", ") }, [3, 3]; case 2: a.kernelMs = { error: "WebGL query timers are not supported in this environment." }, t.label = 3; case 3: return this.uploadWaitMs = 0, this.downloadWaitMs = 0, [2, a] } }) }) }, Ts.prototype.memory = function () { return { unreliable: !1, numBytesInGPU: this.numBytesInGPU } }, Ts.prototype.startTimer = function () { return 0 < _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") ? this.gpgpu.beginQuery() : { startMs: tt(), endMs: null } }, Ts.prototype.endTimer = function (t) { return 0 < _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") ? this.gpgpu.endQuery() : t.endMs = tt(), t }, Ts.prototype.getQueryTime = function (n) { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { return 0 < _().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") ? [2, this.gpgpu.waitForQueryAndGetTime(n)] : [2, (e = n).endMs - e.startMs] }) }) }, Ts.prototype.disposeData = function (t) { if (!this.pendingDisposal.has(t)) { if (this.pendingRead.has(t)) return this.pendingDisposal.add(t), void this.pendingDeletes++; if (this.texData.has(t)) { this.releaseGPUData(t); var e = this.texData.get(t).complexTensors; null != e && (e.real.dispose(), e.imag.dispose()), this.texData.delete(t) } } }, Ts.prototype.releaseGPUData = function (t) { var e = this.texData.get(t), n = e.texture, r = e.dtype, o = e.texShape, i = e.usage, a = e.isPacked, s = e.slice, u = s && s.origDataId || t, c = this.dataRefCount.get(u); 1 < c ? this.dataRefCount.set(u, c - 1) : (this.dataRefCount.delete(u), null != n && (this.numBytesInGPU -= this.computeBytes(o, r), this.textureManager.releaseTexture(n, o, i, a))); var l = this.texData.get(t); l.texture = null, l.texShape = null, l.isPacked = !1, l.slice = null }, Ts.prototype.getTexture = function (t) { return this.uploadToGPU(t), this.texData.get(t).texture }, Ts.prototype.getDataInfo = function (t) { return this.texData.get(t) }, Ts.prototype.getCPUBackend = function () { return _().getBool("WEBGL_CPU_FORWARD") ? (null == this.cpuBackend && (this.cpuBackend = Kt.findBackend("cpu")), this.cpuBackend) : null }, Ts.prototype.shouldExecuteOnCPU = function (t, e) { var n = this; return void 0 === e && (e = 128), null != this.getCPUBackend() && t.every(function (t) { return null == n.texData.get(t.dataId).texture && t.size < e }) }, Ts.prototype.getGPGPUContext = function () { return this.gpgpu }, Ts.prototype.complex = function (t, e) { var n = this.makeOutput(t.shape, "complex64"); return this.texData.get(n.dataId).complexTensors = { real: Kt.keep(t.clone()), imag: Kt.keep(e.clone()) }, n }, Ts.prototype.real = function (t) { return this.texData.get(t.dataId).complexTensors.real.clone() }, Ts.prototype.imag = function (t) { return this.texData.get(t.dataId).complexTensors.imag.clone() }, Ts.prototype.slice = function (t, e, n) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.slice(t, e, n); if (0 === L(n)) return In([], n, t.dtype); var r = this.texData.get(t.dataId).isPacked, o = eo(t.shape, e, n); if (!r && o) return this.uploadToGPU(t.dataId), this.shallowSlice(t, e, n); var i = _().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new Za(n) : new Ya(n), a = i.getCustomSetupFunc(e); return this.compileAndRun(i, [t], null, a) }, Ts.prototype.shallowSlice = function (t, e, n) { var r = this.texData.get(t.dataId), o = this.makeOutput(n, t.dtype), i = this.texData.get(o.dataId); Object.assign(i, r), i.shape = n, i.dtype = t.dtype; var a = no(e, t.strides); r.slice && (a += r.slice.flatOffset), i.slice = { flatOffset: a, origDataId: r.slice && r.slice.origDataId || t.dataId }; var s = this.dataRefCount.get(i.slice.origDataId) || 1; return this.dataRefCount.set(i.slice.origDataId, s + 1), o }, Ts.prototype.stridedSlice = function (t, e, n, r) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.stridedSlice(t, e, n, r); var o = Qr(e, n, r); if (o.some(function (t) { return 0 === t })) return In([], o); var i = new Qa(e, r, o); return this.compileAndRun(i, [t]) }, Ts.prototype.reverse = function (t, e) { var n = _().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new qa(t.shape, e) : new Ha(t.shape, e); return this.compileAndRun(n, [t]) }, Ts.prototype.concat = function (t, e) { if ("complex64" === t[0].dtype) { var n = t.map(function (t) { return En(t) }), r = t.map(function (t) { return _n(t) }); return Cn(this.concat(n, e), this.concat(r, e)) } if (this.shouldExecuteOnCPU(t)) return this.cpuBackend.concat(t, e); if (1 === t.length) return t[0]; if (t.length > _().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")) { var o = Math.floor(t.length / 2), i = this.concat(t.slice(0, o), e), a = this.concat(t.slice(o), e); return this.concat([i, a], e) } if (_().getBool("WEBGL_PACK_ARRAY_OPERATIONS") && 1 < t[0].rank) { var s = new gi(t.map(function (t) { return t.shape }), e); return this.compileAndRun(s, t) } var u = bn(t.map(function (t) { return t.shape }), e), c = t.map(function (t) { return t.as2D(-1, L(t.shape.slice(e))) }), l = new mi(c.map(function (t) { return t.shape })); return this.compileAndRun(l, c).reshape(u) }, Ts.prototype.neg = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.neg(t); if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, ys, t.dtype); var e = new us(t.shape, ys); return this.compileAndRun(e, [t]) }, Ts.prototype.batchMatMul = function (t, e, n, r) { var o = n ? t.shape[2] : t.shape[1], i = r ? e.shape[1] : e.shape[2], a = n ? t.shape[1] : t.shape[2], s = t.shape[0]; if ((1 === o || 1 === i) && 1e3 < a) { n && (t = t.transpose([0, 2, 1])), r && (e = e.transpose([0, 2, 1])); var u = 1 === i ? t : t.as3D(s, a, 1), c = 1 === i ? 2 : 1, l = 1 === i ? e.as3D(s, 1, a) : e; return this.multiply(u, l).sum(c, !0) } var h = Pt(t.dtype, e.dtype), f = new Sa(t.shape, [s, o, i], n, r); return this.compileAndRun(f, [t, e], h) }, Ts.prototype.fusedBatchMatMul = function (t) { var e = t.a, n = t.b, r = t.transposeA, o = t.transposeB, i = t.bias, a = t.activation, s = t.preluActivationWeights, u = r ? e.shape[2] : e.shape[1], c = o ? n.shape[1] : n.shape[2], l = e.shape[0], h = Pt(e.dtype, n.dtype), f = null != i, p = null != s, d = a ? Ss(a, !0) : null, v = new Sa(e.shape, [l, u, c], r, o, f, d, p), m = [e, n]; return i && m.push(i), s && m.push(s), this.compileAndRun(v, m, h) }, Ts.prototype.multiply = function (t, e) { if ("complex64" === t.dtype) { var n = this.texData.get(t.dataId), r = this.texData.get(e.dataId), o = new fi("return areal * breal - aimag * bimag;", t.shape, e.shape), i = new fi("return areal * bimag + aimag * breal;", t.shape, e.shape), a = [this.makeComplexComponentTensorInfo(t, n.complexTensors.real), this.makeComplexComponentTensorInfo(t, n.complexTensors.imag), this.makeComplexComponentTensorInfo(e, r.complexTensors.real), this.makeComplexComponentTensorInfo(e, r.complexTensors.imag)], s = this.compileAndRun(o, a), u = this.compileAndRun(i, a), c = this.complex(s, u); return s.dispose(), u.dispose(), c } if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.multiply(t, e); if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, bi, t.dtype); var l = new pi(bi, t.shape, e.shape); return this.compileAndRun(l, [t, e], t.dtype) }, Ts.prototype.batchNormalization = function (t, e, n, r, o, i) { var a = [t, e, n], s = null; null != i && (s = i.shape, a.push(i)); var u = null; if (null != o && (u = o.shape, a.push(o)), _().getBool("WEBGL_PACK_NORMALIZATION")) { var c = new hi(t.shape, e.shape, n.shape, s, u, r); return this.compileAndRun(c, a) } var l = new li(t.shape, e.shape, n.shape, s, u, r); return this.compileAndRun(l, a) }, Ts.prototype.localResponseNormalization4D = function (t, e, n, r, o) { var i = _().getBool("WEBGL_PACK_NORMALIZATION") ? new Ia(t.shape, e, n, r, o) : new Ea(t.shape, e, n, r, o); return this.compileAndRun(i, [t]) }, Ts.prototype.LRNGrad = function (t, e, n, r, o, i, a) { var s = new _a(e.shape, r, o, i, a); return this.compileAndRun(s, [e, n, t]) }, Ts.prototype.tile = function (t, e) { if ("string" === t.dtype) { var n = this.readSync(t.dataId).map(function (t) { return rt(t) }); return Go(cr(t.shape, t.dtype, n), e) } var r = new is(t.shape, e); return this.compileAndRun(r, [t]) }, Ts.prototype.pad = function (t, e, n) { var r = _().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new Ma(t.shape, e, n) : new Fa(t.shape, e, n); return this.compileAndRun(r, [t]) }, Ts.prototype.transpose = function (t, e) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.transpose(t, e); var n = _().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new ss(t.shape, e) : new as(t.shape, e); return this.compileAndRun(n, [t]) }, Ts.prototype.gather = function (t, e, n) { if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.gather(t, e, n); var r = new Yi(t.shape, e.size, n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.batchToSpaceND = function (t, e, n) { P(t.rank <= 4, function () { return "batchToSpaceND for rank > 4 with a WebGL backend not implemented yet" }); var r = e.reduce(function (t, e) { return t * e }), o = Lr(t.shape, e, r), i = Wr(o.length, e.length), a = zr(t.shape, e, r), s = Ur(n, e.length), u = Vr(a, n, e.length); return t.reshape(o).transpose(i).reshape(a).slice(s, u) }, Ts.prototype.spaceToBatchND = function (t, e, n) { P(t.rank <= 4, function () { return "spaceToBatchND for rank > 4 with a WebGL backend not implemented yet" }); var r = e.reduce(function (t, e) { return t * e }), o = [[0, 0]]; o.push.apply(o, n); for (var i = 1 + e.length; i < t.shape.length; ++i)o.push([0, 0]); var a = t.pad(o), s = Lr(a.shape, e, r, !1), u = Wr(s.length, e.length, !1), c = zr(a.shape, e, r, !1); return a.reshape(s).transpose(u).reshape(c) }, Ts.prototype.reduce = function (t, e, n) { var r = t.shape[0], o = t.shape[1], i = qr(o), a = new Ba({ windowSize: i, inSize: o, batchSize: r }, e), s = this.compileAndRun(a, [t], n); return 1 === s.shape[1] ? s : this.reduce(s, e, n) }, Ts.prototype.argReduce = function (t, e, n) { void 0 === n && (n = null); var r = t.shape[0], o = t.shape[1]; null != n && (r = n.shape[0], o = n.shape[1]); var i = qr(o), a = new Xo({ windowSize: i, inSize: o, batchSize: r }, e, null == n), s = [t]; null != n && s.push(n); var u = this.compileAndRun(a, s, "int32"); return 1 === u.shape[1] ? u : this.argReduce(t, e, u) }, Ts.prototype.argReducePacked = function (t, e, n) { void 0 === n && (n = null); var r = null != n ? n.shape : t.shape, o = qr(r[r.length - 1]), i = new si(r, o, e, null == n), a = null == n ? [t] : [t, n], s = this.compileAndRun(i, a, "int32"); return s.rank === t.rank ? this.argReducePacked(t, e, s) : s }, Ts.prototype.sum = function (t, e) { vn("sum", e, t.rank); var n = pn(t.shape, e), r = n[0], o = L(n[1]), i = t.as2D(-1, o), a = Bt(t.dtype); return this.reduce(i, "sum", a).reshape(r) }, Ts.prototype.prod = function (t, e) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.prod(t, e); var n = pn(t.shape, e), r = n[0], o = L(n[1]), i = t.as2D(-1, o), a = Bt(t.dtype); return this.reduce(i, "prod", a).reshape(r) }, Ts.prototype.unsortedSegmentSum = function (t, e, n) { var r = 0, o = mn([r], t.rank), i = t; null != o && (i = t.transpose(o), r = yn(1, t.rank)[0]); var a = function (t, e, n) { for (var r = [], o = t.length, i = 0; i < o; i++)i !== e ? r.push(t[i]) : r.push(n); return r }(i.shape, r, n), s = L([i.shape[r]]), u = i.as2D(-1, s), c = Bt(t.dtype), l = this.segOpCompute(u, "unsortedSegmentSum", e, c, n).reshape(a); return null != o && (l = l.transpose(gn(o))), l }, Ts.prototype.segOpCompute = function (t, e, n, r, o) { var i = t.shape[0], a = t.shape[1], s = function (t, e) { var n, r = !1; for (t <= 30 ? (n = t, r = !0) : n = X(t, Math.floor(Math.sqrt(t))); !r;)e < n || n === t ? r = !0 : n = X(t, n + 1); return n }(a, o), u = new Ka({ windowSize: s, inSize: a, batchSize: i, numSegments: o }, e), c = this.compileAndRun(u, [t, n], r); return c.shape[1] === o ? c : (n = Wn(0, o).tile([a / s]), this.segOpCompute(c, e, n, r, o)) }, Ts.prototype.argMinMaxReduce = function (t, e, n) { var r = [e]; if (vn("arg" + n.charAt(0).toUpperCase() + n.slice(1), r, t.rank), !_().getBool("WEBGL_PACK_REDUCE") || t.rank <= 2) { var o = pn(t.shape, r), i = o[0], a = L(o[1]), s = t.as2D(-1, a); return this.argReduce(s, n).reshape(i) } return this.argReducePacked(t, n) }, Ts.prototype.argMin = function (t, e) { return this.argMinMaxReduce(t, e, "min") }, Ts.prototype.argMax = function (t, e) { return this.argMinMaxReduce(t, e, "max") }, Ts.prototype.cumsum = function (t, e, n, r) { if (e !== t.rank - 1) throw new Error("WebGL cumsum shader expects an inner-most axis=" + (t.rank - 1) + " but got axis=" + e); var o = new Wi(t.shape, n, r); return this.compileAndRun(o, [t]) }, Ts.prototype.equal = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return vec4(equal(a, b));\n", "bool"); var n = new pi("return float(a == b);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.notEqual = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return vec4(notEqual(a, b));\n", "bool"); var n = new pi("return float(a != b);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.less = function (t, e) { if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.less(t, e); if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return vec4(lessThan(a, b));\n", "bool"); var n = new pi("return float(a < b);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.lessEqual = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return vec4(lessThanEqual(a, b));\n", "bool"); var n = new pi("return float(a <= b);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.greater = function (t, e) { if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.greater(t, e); if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return vec4(greaterThan(a, b));\n", "bool"); var n = new pi("return float(a > b);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.greaterEqual = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return vec4(greaterThanEqual(a, b));\n", "bool"); var n = new pi("return float(a >= b);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.logicalNot = function (t) { var e = new us(t.shape, "return float(!(x >= 1.0));"); return this.compileAndRun(e, [t]) }, Ts.prototype.logicalAnd = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n", "bool"); var n = new pi("return float(a >= 1.0 && b >= 1.0);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.logicalOr = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n", "bool"); var n = new pi("return float(a >= 1.0 || b >= 1.0);", t.shape, e.shape); return this.compileAndRun(n, [t, e], "bool") }, Ts.prototype.select = function (t, e, n) { var r = new Xa(t.rank, e.shape, e.rank); return this.compileAndRun(r, [t, e, n], Pt(e.dtype, n.dtype)) }, Ts.prototype.where = function (t) { an("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead"); var e = t.dataSync(); return qo(t.shape, e) }, Ts.prototype.topk = function (t, e, n) { return Ho(t.dataSync(), t.shape, t.dtype, e) }, Ts.prototype.min = function (t, e) { vn("min", e, t.rank); var n = pn(t.shape, e), r = n[0], o = L(n[1]), i = t.as2D(-1, o); return this.reduce(i, "min", i.dtype).reshape(r) }, Ts.prototype.minimum = function (t, e) { if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.minimum(t, e); var n = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di("\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n", t.shape, e.shape) : new pi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return min(a, b);\n", t.shape, e.shape); return this.compileAndRun(n, [t, e]) }, Ts.prototype.mod = function (t, e) { var n = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di("\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n", t.shape, e.shape) : new pi("if (b == 0.0) return NAN;\n  return mod(a, b);", t.shape, e.shape); return this.compileAndRun(n, [t, e]) }, Ts.prototype.max = function (t, e) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.max(t, e); vn("max", e, t.rank); var n = pn(t.shape, e), r = n[0], o = L(n[1]), i = t.as2D(-1, o); return this.reduce(i, "max", i.dtype).reshape(r) }, Ts.prototype.maximum = function (t, e) { if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.maximum(t, e); var n = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di("\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n", t.shape, e.shape) : new pi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return max(a, b);\n", t.shape, e.shape); return this.compileAndRun(n, [t, e]) }, Ts.prototype.all = function (t, e) { vn("all", e, t.rank); var n = pn(t.shape, e), r = n[0], o = L(n[1]), i = t.as2D(-1, o); return this.reduce(i, "all", i.dtype).reshape(r) }, Ts.prototype.any = function (t, e) { vn("any", e, t.rank); var n = pn(t.shape, e), r = n[0], o = L(n[1]), i = t.as2D(-1, o); return this.reduce(i, "any", i.dtype).reshape(r) }, Ts.prototype.realDivide = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n", "float32", !0); var n = new pi("\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;", t.shape, e.shape); return this.compileAndRun(n, [t, e], "float32") }, Ts.prototype.floorDiv = function (t, e) { if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, "\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n", "int32"); var n = new pi("\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n", t.shape, e.shape); return this.compileAndRun(n, [t, e], "int32") }, Ts.prototype.add = function (t, e) { if ("complex64" === t.dtype && "complex64" === e.dtype) return this.complexSeparableBinaryOp(t, e, yi); if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.add(t, e); var n = Pt(t.dtype, e.dtype); if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, yi, n); var r = new pi(yi, t.shape, e.shape); return this.compileAndRun(r, [t, e], n) }, Ts.prototype.packedUnaryOp = function (t, e, n) { var r = new cs(t.shape, e); return this.compileAndRun(r, [t], n) }, Ts.prototype.packedBinaryOp = function (t, e, n, r, o) { void 0 === o && (o = !1); var i = new di(n, t.shape, e.shape, o); return this.compileAndRun(i, [t, e], r) }, Ts.prototype.complexSeparableBinaryOp = function (a, s, u) { var c = this, t = this.texData.get(a.dataId), e = this.texData.get(s.dataId), n = [[t.complexTensors.real, e.complexTensors.real], [t.complexTensors.imag, e.complexTensors.imag]].map(function (t) { var e = t[0], n = t[1], r = c.makeComplexComponentTensorInfo(a, e), o = c.makeComplexComponentTensorInfo(s, n), i = new pi(u, a.shape, s.shape); return c.compileAndRun(i, [r, o], Pt(e.dtype, n.dtype)) }), r = n[0], o = n[1], i = this.complex(r, o); return r.dispose(), o.dispose(), i }, Ts.prototype.makeComplexComponentTensorInfo = function (t, e) { return { dataId: e.dataId, dtype: e.dtype, shape: t.shape } }, Ts.prototype.addN = function (t) { if (1 === t.length) return t[0]; if (t.length > _().get("WEBGL_MAX_TEXTURES_IN_SHADER")) { var e = Math.floor(t.length / 2), n = this.addN(t.slice(0, e)), r = this.addN(t.slice(e)); return this.addN([n, r]) } var o = t.map(function (t) { return t.dtype }).reduce(function (t, e) { return Pt(t, e) }), i = t.map(function (t) { return t.shape }), a = _().getBool("WEBGL_PACK") ? new Ko(t[0].shape, i) : new jo(t[0].shape, i); return this.compileAndRun(a, t, o) }, Ts.prototype.subtract = function (t, e) { if ("complex64" === t.dtype && "complex64" === e.dtype) return this.complexSeparableBinaryOp(t, e, xi); if (this.shouldExecuteOnCPU([t, e])) return this.cpuBackend.subtract(t, e); var n = Pt(t.dtype, e.dtype); if (_().getBool("WEBGL_PACK_BINARY_OPERATIONS")) return this.packedBinaryOp(t, e, xi, t.dtype); var r = new pi(xi, t.shape, e.shape); return this.compileAndRun(r, [t, e], n) }, Ts.prototype.pow = function (t, e) { var n = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di("\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n", t.shape, e.shape) : new pi("\nif(a < 0.0 && floor(b) < b){\n  return NAN;\n}\nif (b == 0.0) {\n  return 1.0;\n}\nreturn (round(mod(b, 2.0)) != 1) ?\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\n", t.shape, e.shape), r = Pt(t.dtype, e.dtype); return this.compileAndRun(n, [t, e], r) }, Ts.prototype.ceil = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.ceil(t); if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, xs, t.dtype); var e = new us(t.shape, xs); return this.compileAndRun(e, [t]) }, Ts.prototype.floor = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.floor(t); if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, bs, t.dtype); var e = new us(t.shape, bs); return this.compileAndRun(e, [t]) }, Ts.prototype.sign = function (t) { var e = new us(t.shape, "\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.isNaN = function (t) { var e = new us(t.shape, "return float(isnan(x));"); return this.compileAndRun(e, [t], "bool") }, Ts.prototype.isInf = function (t) { var e = new us(t.shape, "return float(isinf(x));"); return this.compileAndRun(e, [t], "bool") }, Ts.prototype.isFinite = function (t) { var e = new us(t.shape, "return float(!isnan(x) && !isinf(x));"); return this.compileAndRun(e, [t], "bool") }, Ts.prototype.round = function (t) { var e = new us(t.shape, "\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.exp = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.exp(t); if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, ws, t.dtype); var e = new us(t.shape, ws); return this.compileAndRun(e, [t]) }, Ts.prototype.expm1 = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.expm1(t); if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, Cs, t.dtype); var e = new us(t.shape, Cs); return this.compileAndRun(e, [t]) }, Ts.prototype.softmax = function (t, e) { var n = D([e], t.shape), r = this.max(t, n), o = dn(r.shape, n), i = this.subtract(t, r.reshape(o)), a = this.exp(i), s = this.sum(a, n).reshape(o); return this.realDivide(a, s) }, Ts.prototype.log = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.log(t); if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, "\n  vec4 result = log(x);\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n", t.dtype); var e = new us(t.shape, "if (x < 0.0) return NAN;\n  return log(x);"); return this.compileAndRun(e, [t]) }, Ts.prototype.log1p = function (t) { var e = new us(t.shape, "return log(1.0 + x);"); return this.compileAndRun(e, [t]) }, Ts.prototype.sqrt = function (t) { var e = new us(t.shape, "return sqrt(x);"); return this.compileAndRun(e, [t]) }, Ts.prototype.rsqrt = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.rsqrt(t); var e = new us(t.shape, "return inversesqrt(x);"); return this.compileAndRun(e, [t]) }, Ts.prototype.reciprocal = function (t) { var e = new us(t.shape, "return 1.0 / x;"); return this.compileAndRun(e, [t]) }, Ts.prototype.relu = function (t) { var e; return e = _().getBool("WEBGL_PACK") ? new cs(t.shape, _s) : new us(t.shape, vs), this.compileAndRun(e, [t]) }, Ts.prototype.relu6 = function (t) { var e; return e = _().getBool("WEBGL_PACK") ? new cs(t.shape, Is) : new us(t.shape, ms), this.compileAndRun(e, [t]) }, Ts.prototype.prelu = function (t, e) { var n = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di(Ci, t.shape, e.shape) : new pi(wi, t.shape, e.shape); return this.compileAndRun(n, [t, e]) }, Ts.prototype.elu = function (t) { if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, Rs, t.dtype); var e = new us(t.shape, gs); return this.compileAndRun(e, [t]) }, Ts.prototype.eluDer = function (t, e) { var n = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di("\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n", t.shape, e.shape) : new pi("return (b >= 1.0) ? a : a * (b + 1.0);", t.shape, e.shape); return this.compileAndRun(n, [t, e]) }, Ts.prototype.selu = function (t) { var e = new us(t.shape, "\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = 1.7580993408473768;\n  float scale = 1.0507009873554805;\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.int = function (t) { var e = new us(t.shape, "return float(int(x));"); return this.compileAndRun(e, [t], "int32") }, Ts.prototype.clip = function (t, e, n) { var r, o = (r = _().getBool("WEBGL_PACK_CLIP") ? new _i(t.shape) : new Ei(t.shape)).getCustomSetupFunc(e, n); return this.compileAndRun(r, [t], null, o) }, Ts.prototype.abs = function (t) { if (this.shouldExecuteOnCPU([t])) return this.cpuBackend.abs(t); if (_().getBool("WEBGL_PACK_UNARY_OPERATIONS")) return this.packedUnaryOp(t, ds, t.dtype); var e = new us(t.shape, ds); return this.compileAndRun(e, [t]) }, Ts.prototype.complexAbs = function (t) { var e = this.texData.get(t.dataId), n = new vi(t.shape), r = [this.makeComplexComponentTensorInfo(t, e.complexTensors.real), this.makeComplexComponentTensorInfo(t, e.complexTensors.imag)]; return this.compileAndRun(n, r) }, Ts.prototype.sigmoid = function (t) { var e = new us(t.shape, "return 1.0 / (1.0 + exp(-1.0 * x));"); return this.compileAndRun(e, [t]) }, Ts.prototype.softplus = function (t) { var e = new us(t.shape, "\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.sin = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;\n  return sin(x);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.cos = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;\n  return cos(x);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.tan = function (t) { var e = new us(t.shape, "return tan(x);"); return this.compileAndRun(e, [t]) }, Ts.prototype.asin = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.acos = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.atan = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;\n  return atan(x);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.atan2 = function (t, e) { var n = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di("\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n", t.shape, e.shape) : new pi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return atan(a, b);\n", t.shape, e.shape); return this.compileAndRun(n, [t, e]) }, Ts.prototype.sinh = function (t) { var e = new us(t.shape, "\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.cosh = function (t) { var e = new us(t.shape, "\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.tanh = function (t) { var e = new us(t.shape, "\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n"); return this.compileAndRun(e, [t]) }, Ts.prototype.asinh = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;return log(x + sqrt(x * x + 1.0));"); return this.compileAndRun(e, [t]) }, Ts.prototype.acosh = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;\n  if (x < 1.0) return NAN;\n  return log(x + sqrt(x * x - 1.0));"); return this.compileAndRun(e, [t]) }, Ts.prototype.atanh = function (t) { var e = new us(t.shape, "if (isnan(x)) return x;\n  if ((x < -1.0) || (x > 1.0)) return NAN;\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;"); return this.compileAndRun(e, [t]) }, Ts.prototype.erf = function (t) { var e = new us(t.shape, '\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = 0.3275911;\n  float a1 = 0.254829592;\n  float a2 = -0.284496736;\n  float a3 = 1.421413741;\n  float a4 = -1.453152027;\n  float a5 = 1.061405429;\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n'); return this.compileAndRun(e, [t]) }, Ts.prototype.step = function (t, e) { var n, r = new us(t.shape, (void 0 === (n = e) && (n = 0), ps + "\n    return x > 0.0 ? 1.0 : float(" + n + ");\n  ")); return this.compileAndRun(r, [t]) }, Ts.prototype.conv2dByMatMul = function (t, e, n, r, o, i) { var a = t.shape, s = this.texData.get(t.dataId), u = n.inChannels, c = a[0] * a[1] * a[2], l = n.outChannels, h = "channelsLast" === n.dataFormat, f = (1 == c || 1 === l) && 1e3 < u, p = a[2] % 2 != 0 && !!s.isPacked; if (f || !_().getBool("WEBGL_LAZILY_UNPACK") || !_().getBool("WEBGL_PACK_BINARY_OPERATIONS") || !p) { var d = h ? a[0] * a[1] * a[2] : a[0] * a[2] * a[3], v = this.reshape(t, [1, d, n.inChannels]), m = this.reshape(e, [1, n.inChannels, n.outChannels]); return this.reshape(this.fusedBatchMatMul({ a: v, b: m, transposeA: !1, transposeB: !1, bias: r, activation: o, preluActivationWeights: i }), n.outShape) } var g = h ? a[0] * a[1] * (a[2] + 1) : a[0] * a[2] * (a[3] + 1), y = { dataId: t.dataId, shape: [1, g, n.inChannels], dtype: t.dtype }, x = s.shape; s.shape = s.shape.slice(), s.shape[s.shape.length - 2]++, P(Ge(s.shape, y.shape), function () { return "packed reshape " + s.shape + " to " + y.shape + " isn't free" }); var b = this.reshape(e, [1, n.inChannels, n.outChannels]), w = this.fusedBatchMatMul({ a: y, b: b, transposeA: !1, transposeB: !1, bias: r, activation: o, preluActivationWeights: i }), C = this.texData.get(w.dataId); return P(C.isPacked, function () { return "batchMatMul result is expected to be packed" }), s.shape = x, C.shape = n.outShape, Kt.makeTensorFromDataId(w.dataId, n.outShape, w.dtype) }, Ts.prototype.conv2dWithIm2Row = function (t, e, n, r, o, i) { var a = n.filterWidth, s = n.filterHeight, u = n.inChannels, c = n.outWidth, l = n.outHeight, h = "channelsLast" === n.dataFormat, f = a * s * u, p = l * c, d = [f, p], v = t.squeeze([0]), m = e.reshape([1, f, -1]), g = new Ca(d, v.shape, n), y = this.compileAndRun(g, [v]).reshape([1, d[0], d[1]]), x = null != r, b = null != i, w = o ? Ss(o, !0) : null, C = new Sa(y.shape, [1, p, n.outChannels], !0, !1, x, w, b), E = [y, m]; r && E.push(r), b && E.push(i); var _ = this.compileAndRun(C, E); return h ? _.reshape([1, l, c, n.outChannels]) : _.reshape([1, n.outChannels, l, c]) }, Ts.prototype.fusedConv2d = function (t) { var e = t.input, n = t.filter, r = t.convInfo, o = t.bias, i = t.activation, a = t.preluActivationWeights; if (1 === r.filterHeight && 1 === r.filterWidth && 1 === r.dilationHeight && 1 === r.dilationWidth && 1 === r.strideHeight && 1 === r.strideWidth && ("SAME" === r.padInfo.type || "VALID" === r.padInfo.type)) return this.conv2dByMatMul(e, n, r, o, i, a); if (_().getBool("WEBGL_CONV_IM2COL") && 1 === e.shape[0]) return this.conv2dWithIm2Row(e, n, r, o, i, a); var s = null != o, u = null != a, c = i ? Ss(i, !1) : null, l = new Mi(r, s, c, u), h = [e, n]; return o && h.push(o), a && h.push(a), this.compileAndRun(l, h) }, Ts.prototype.conv2d = function (t, e, n) { if (1 === n.filterHeight && 1 === n.filterWidth && 1 === n.dilationHeight && 1 === n.dilationWidth && 1 === n.strideHeight && 1 === n.strideWidth && ("SAME" === n.padInfo.type || "VALID" === n.padInfo.type)) return this.conv2dByMatMul(t, e, n); if (_().getBool("WEBGL_CONV_IM2COL") && 1 === t.shape[0]) return this.conv2dWithIm2Row(t, e, n); var r = new Mi(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.conv2dDerInput = function (t, e, n) { var r = new Di(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.conv2dDerFilter = function (t, e, n) { var r = new Si(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.fusedDepthwiseConv2D = function (t) { var e, n = t.input, r = t.filter, o = t.convInfo, i = t.bias, a = t.activation, s = t.preluActivationWeights, u = _().getBool("WEBGL_PACK_DEPTHWISECONV") && o.strideWidth <= 2 && o.outChannels / o.inChannels == 1, c = a ? Ss(a, u) : null, l = [n, r], h = null != i, f = null != s; return h && l.push(i), f && l.push(s), e = u ? new Bi(o, h, c, f) : new Pi(o, h, c, f), this.compileAndRun(e, l) }, Ts.prototype.depthwiseConv2D = function (t, e, n) { var r; return r = _().getBool("WEBGL_PACK_DEPTHWISECONV") && n.strideWidth <= 2 && n.outChannels / n.inChannels == 1 ? new Bi(n) : new Pi(n), this.compileAndRun(r, [t, e]) }, Ts.prototype.depthwiseConv2DDerInput = function (t, e, n) { var r = new Fi(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.depthwiseConv2DDerFilter = function (t, e, n) { var r = new Ni(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.conv3d = function (t, e, n) { var r = new Oi(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.conv3dDerInput = function (t, e, n) { var r = new Ti(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.conv3dDerFilter = function (t, e, n) { var r = new Ai(n); return this.compileAndRun(r, [t, e]) }, Ts.prototype.maxPool = function (t, e) { var n = new Oa(e, "max", !1); return this.compileAndRun(n, [t]) }, Ts.prototype.avgPool = function (t, e) { var n = new Oa(e, "avg", !1); return this.compileAndRun(n, [t], "float32") }, Ts.prototype.maxPoolBackprop = function (t, e, n, r) { var o = new Oa(r, "max", !0), i = this.compileAndRun(o, [e]), a = new Ra(r), s = this.compileAndRun(a, [t, i], e.dtype); return i.dispose(), s }, Ts.prototype.avgPoolBackprop = function (t, e, n) { var r = new ui(n); return this.compileAndRun(r, [t], e.dtype) }, Ts.prototype.cast = function (t, e) { return Ao(t, e, this) }, Ts.prototype.unstack = function (t, e) { for (var n = t.shape[e], r = new Array(t.rank - 1), o = 0, i = 0; i < t.rank; i++)i !== e && (r[o++] = t.shape[i]); var a = new Array(t.rank).fill(0), s = t.shape.slice(); s[e] = 1; var u = new Array(n); for (i = 0; i < u.length; i++)u[a[e] = i] = this.slice(t, a, s).reshape(r); return u }, Ts.prototype.avgPool3d = function (t, e) { var n = new Pa(e, "avg", !1); return this.compileAndRun(n, [t], "float32") }, Ts.prototype.avgPool3dBackprop = function (t, e, n) { var r = new ci(n); return this.compileAndRun(r, [t], e.dtype) }, Ts.prototype.maxPool3d = function (t, e) { var n = new Pa(e, "max", !1); return this.compileAndRun(n, [t], "float32") }, Ts.prototype.maxPool3dBackprop = function (t, e, n, r) { var o = new Pa(r, "max", !0), i = this.compileAndRun(o, [e]), a = new ka(r), s = this.compileAndRun(a, [t, i], e.dtype); return i.dispose(), s }, Ts.prototype.reshape = function (t, e) { var n = this.texData.get(t.dataId); if (!n.isPacked || Ge(t.shape, e) || null !== n.texture && Ge(n.shape, e)) return To(t, e); var r = this.packedReshape(t, e); return Kt.makeTensorFromDataId(r.dataId, r.shape, r.dtype) }, Ts.prototype.resizeBilinear = function (t, e, n, r) { var o = _().getBool("WEBGL_PACK_IMAGE_OPERATIONS") ? new Ua(t.shape, e, n, r) : new za(t.shape, e, n, r); return this.compileAndRun(o, [t], "float32") }, Ts.prototype.resizeBilinearBackprop = function (t, e, n) { var r = new Wa(t, e, n); return this.compileAndRun(r, [t]) }, Ts.prototype.resizeNearestNeighbor = function (t, e, n, r) { var o = new Ga(t.shape, e, n, r); return this.compileAndRun(o, [t]) }, Ts.prototype.resizeNearestNeighborBackprop = function (t, e, n) { var r = new Va(t, e, n); return this.compileAndRun(r, [t]) }, Ts.prototype.multinomial = function (t, e, n, r) { var o = e ? t : so(t), i = o.shape[0], a = o.shape[1], s = new Ta(i, a, n), u = s.getCustomSetupFunc(r); return this.compileAndRun(s, [o], "int32", u) }, Ts.prototype.oneHot = function (t, e, n, r) { var o = new Da(t.size, e, n, r); return this.compileAndRun(o, [t]) }, Ts.prototype.diag = function (t) { var e = new Gi(t.size); return this.compileAndRun(e, [t]) }, Ts.prototype.nonMaxSuppression = function (t, e, n, r, o) { return an("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead"), Bo(t.dataSync(), e.dataSync(), n, r, o) }, Ts.prototype.cropAndResize = function (t, e, n, r, o, i) { var a = new Li(t.shape, e.shape, r, o, i); return this.compileAndRun(a, [t, e, n], "float32") }, Ts.prototype.depthToSpace = function (t, e, n) { P(1 < e, function () { return "blockSize should be > 1 for depthToSpace, but was: " + e }); var r = t.shape[0], o = "NHWC" === n ? t.shape[1] : t.shape[2], i = "NHWC" === n ? t.shape[2] : t.shape[3], a = "NHWC" === n ? t.shape[3] : t.shape[1], s = o * e, u = i * e, c = a / (e * e), l = new $i("NHWC" === n ? [r, s, u, c] : [r, c, s, u], e, n); return this.compileAndRun(l, [t]) }, Ts.prototype.split = function (t, e, n) { return Vo(t, e, n) }, Ts.prototype.scatterND = function (t, e, n) { var r = Xr(0, t, n), o = r.sliceRank, i = r.numUpdates, a = r.sliceSize, s = r.strides, u = r.outputSize, c = [u / a, a], l = t.reshape([i, o]), h = e.reshape([i, a]); if (0 === u) return To(In([]), n); var f = kn(0), p = new ja(i, o, l.rank, h.rank, s, c); return this.compileAndRun(p, [h, l, f]).reshape(n) }, Ts.prototype.sparseToDense = function (t, e, n, r) { var o = Xr(0, t, n), i = o.sliceRank, a = o.numUpdates, s = o.strides, u = o.outputSize, c = new ja(a, i, t.rank, e.rank, s, [u, 1], !1); return this.compileAndRun(c, [e, t, r]).reshape(n) }, Ts.prototype.fft = function (t) { return this.fftImpl(t, !1) }, Ts.prototype.ifft = function (t) { return this.fftImpl(t, !0) }, Ts.prototype.fftImpl = function (t, e) { var n = this.texData.get(t.dataId), r = new Xi("return real * expR - imag * expI;", t.shape, e), o = new Xi("return real * expI + imag * expR;", t.shape, e), i = [this.makeComplexComponentTensorInfo(t, n.complexTensors.real), this.makeComplexComponentTensorInfo(t, n.complexTensors.imag)], a = this.compileAndRun(r, i), s = this.compileAndRun(o, i), u = this.complex(a, s).as2D(t.shape[0], t.shape[1]); return a.dispose(), s.dispose(), u }, Ts.prototype.gatherND = function (t, e) { var n = e.shape, r = n[n.length - 1], o = Gr(t, e), i = o[0], a = o[1], s = o[2], u = o[3], c = e.reshape([a, r]), l = t.reshape([t.size / s, s]), h = new ta(r, u, [a, s]); return this.compileAndRun(h, [l, c]).reshape(i) }, Ts.prototype.fill = function (t, e, n) { if ("string" === (n = n || j(e))) { var r = F(n, L(t)); return r.fill(e), Kt.makeTensor(r, t, n, this) } var o = new Ji(t, e), i = o.getCustomSetupFunc(e); return this.compileAndRun(o, [], n, i) }, Ts.prototype.onesLike = function (t) { if ("string" === t.dtype) throw new Error("onesLike is not supported under string dtype"); return this.fill(t.shape, 1, t.dtype) }, Ts.prototype.zerosLike = function (t) { return this.fill(t.shape, "string" === t.dtype ? "" : 0, t.dtype) }, Ts.prototype.linspace = function (t, e, n) { return No(t, e, n) }, Ts.prototype.makeTensorInfo = function (t, e) { var n = this.write(null, t, e); return this.texData.get(n).usage = null, { dataId: n, shape: t, dtype: e } }, Ts.prototype.makeOutput = function (t, e) { var n = this.makeTensorInfo(t, e).dataId; return Kt.makeTensorFromDataId(n, t, e, this) }, Ts.prototype.unpackTensor = function (t) { var e = new ls(t.shape); return this.runWebGLProgram(e, [t], t.dtype) }, Ts.prototype.packTensor = function (t) { var e = new Aa(t.shape); return this.runWebGLProgram(e, [t], t.dtype, null, !0) }, Ts.prototype.packedReshape = function (t, e) { var n = [Le(t.shape)].concat(We(t.shape)), r = { dtype: t.dtype, shape: n, dataId: t.dataId }, o = [Le(e)].concat(We(e)), i = new La(o, n), a = this.runWebGLProgram(i, [r], t.dtype, null, !0); return { dataId: a.dataId, shape: e, dtype: a.dtype } }, Ts.prototype.decode = function (t) { var e, n = this.texData.get(t), r = n.isPacked, o = n.shape, i = n.dtype, a = ze(o); return e = r ? new Vi(a) : new Ui(a), { dtype: i, shape: o, dataId: this.runWebGLProgram(e, [{ shape: a, dtype: i, dataId: t }], i, null, !0).dataId } }, Ts.prototype.runWebGLProgram = function (o, t, e, n, r) { var i = this; void 0 === r && (r = !1); var a = this.makeTensorInfo(o.outputShape, e), s = this.texData.get(a.dataId); if (o.packedOutput && (s.isPacked = !0), o.outPackingScheme === $t.DENSE) { var u = se(o.outputShape); s.texShape = u.map(function (t) { return 2 * t }) } if (null != o.outTexUsage && (s.usage = o.outTexUsage), 0 === L(a.shape)) return s.values = N(a.dtype, 0), a; var c = [], l = t.map(function (t) { if ("complex64" === t.dtype) throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts."); var e = i.texData.get(t.dataId); if (null == e.texture) { if (!o.packedInputs && L(t.shape) <= _().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM")) return { shape: t.shape, texData: null, isUniform: !0, uniformValues: e.values }; o.packedInputs && (e.isPacked = !0, e.shape = t.shape) } else if (!!e.isPacked != !!o.packedInputs) t = e.isPacked ? i.unpackTensor(t) : i.packTensor(t), c.push(t), e = i.texData.get(t.dataId); else if (e.isPacked && !Ge(e.shape, t.shape)) { var n = t, r = t.shape; t.shape = e.shape, t = i.packedReshape(t, r), c.push(t), e = i.texData.get(t.dataId), n.shape = r } return i.uploadToGPU(t.dataId), { shape: t.shape, texData: e, isUniform: !1 } }); this.uploadToGPU(a.dataId); var h, f = { shape: a.shape, texData: s, isUniform: !1 }, p = function (t, e, n) { var r = ""; l.concat(n).forEach(function (t) { var e = null != t.texData && null != t.texData.slice && 0 < t.texData.slice.flatOffset, n = t.isUniform ? "uniform" : t.texData.texShape; r += t.shape + "_" + n + "_" + e }); var o = t.userCode; return t.constructor.name + "_" + r + "_" + o }(o, 0, f), d = this.getAndSaveBinary(p, function () { return function (t, r, e, n) { var o = r.userCode, i = e.map(function (t, e) { var n = { logicalShape: t.shape, texShape: t.isUniform ? null : t.texData.texShape, isUniform: t.isUniform, isPacked: !t.isUniform && t.texData.isPacked, flatOffset: null }; return null != t.texData && null != t.texData.slice && 0 < t.texData.slice.flatOffset && (n.flatOffset = t.texData.slice.flatOffset), { name: r.variableNames[e], shapeInfo: n } }), a = i.map(function (t) { return t.shapeInfo }), s = { logicalShape: n.shape, texShape: n.texData.texShape, isUniform: !1, isPacked: n.texData.isPacked, flatOffset: null }, u = ei(i, s, o, r.packedInputs), c = t.createProgram(u), l = null, h = t.getUniformLocation(c, "NAN", !1); 1 === _().getNumber("WEBGL_VERSION") && (l = t.getUniformLocation(c, "INFINITY", !1)); for (var f = {}, p = 0; p < r.variableNames.length; p++) { var d = r.variableNames[p]; f[d] = t.getUniformLocation(c, d, !1), f["offset" + d] = t.getUniformLocation(c, "offset" + d, !1) } return { program: r, source: u, webGLProgram: c, uniformLocations: f, inShapeInfos: a, outShapeInfo: s, infLoc: l, nanLoc: h } }(i.gpgpu, o, l, f) }), v = null != this.activeTimers; if (v && (h = this.startTimer()), function (a, s, t, e, n) { wa(s.inShapeInfos, t), wa([s.outShapeInfo], [e]); var r = e.texData.texture, o = e.texData.texShape; e.texData.isPacked ? a.setOutputPackedMatrixTexture(r, o[0], o[1]) : a.setOutputMatrixTexture(r, o[0], o[1]), a.setProgram(s.webGLProgram), 1 === _().getNumber("WEBGL_VERSION") && null !== s.infLoc && a.gl.uniform1f(s.infLoc, 1 / 0), null !== s.nanLoc && a.gl.uniform1f(s.nanLoc, NaN), t.forEach(function (t, e) { var n = s.program.variableNames[e], r = s.uniformLocations[n], o = s.uniformLocations["offset" + n]; if (null != r) if (t.isUniform) if (L(t.shape) < 2) a.gl.uniform1f(r, t.uniformValues[0]); else { var i = t.uniformValues; i instanceof Float32Array || (i = new Float32Array(i)), a.gl.uniform1fv(r, i) } else null != t.texData.slice && null != o && a.gl.uniform1i(o, t.texData.slice.flatOffset), a.setInputMatrixTexture(t.texData.texture, r, e) }), null != n && n(a, s.webGLProgram), a.executeProgram() }(this.gpgpu, d, l, f, n), c.forEach(function (t) { return i.disposeData(t.dataId) }), v && (h = this.endTimer(h), this.activeTimers.push({ name: o.constructor.name, query: this.getQueryTime(h) })), _().getBool("WEBGL_LAZILY_UNPACK") || !s.isPacked || !1 !== r) return a; var m = this.unpackTensor(a); return this.disposeData(a.dataId), m }, Ts.prototype.compileAndRun = function (t, e, n, r, o) { void 0 === o && (o = !1), n = n || e[0].dtype; var i = this.runWebGLProgram(t, e, n, r, o); return Kt.makeTensorFromDataId(i.dataId, i.shape, i.dtype) }, Ts.prototype.getAndSaveBinary = function (t, e) { return t in this.binaryCache || (this.binaryCache[t] = e()), this.binaryCache[t] }, Ts.prototype.getTextureManager = function () { return this.textureManager }, Ts.prototype.dispose = function () { var e = this; this.disposed || (_().getBool("IS_TEST") || Object.keys(this.binaryCache).forEach(function (t) { e.gpgpu.deleteProgram(e.binaryCache[t].webGLProgram), delete e.binaryCache[t] }), this.textureManager.dispose(), null != this.canvas && "undefined" != typeof HTMLCanvasElement && this.canvas instanceof HTMLCanvasElement ? this.canvas.remove() : this.canvas = null, this.gpgpuCreatedLocally && (this.gpgpu.program = null, this.gpgpu.dispose()), this.disposed = !0) }, Ts.prototype.floatPrecision = function () { var n = this; return null == this.floatPrecisionValue && (this.floatPrecisionValue = nn(function () { if (!_().get("WEBGL_RENDER_FLOAT32_ENABLED")) { var t = _().getBool("DEBUG"); _().set("DEBUG", !1); var e = n.abs(kn(1e-8)).dataSync()[0]; if (_().set("DEBUG", t), 0 < e) return 32 } return 16 })), this.floatPrecisionValue }, Ts.prototype.epsilon = function () { return 32 === this.floatPrecision() ? 1e-7 : 1e-4 }, Ts.prototype.uploadToGPU = function (t) { var e, n = this.texData.get(t), r = n.shape, o = n.dtype, i = n.values, a = n.texture, s = n.usage, u = n.isPacked; if (null == a) { var c, l = null != this.activeTimers; l && (c = tt()); var h = n.texShape; if (null == h && (h = Ue(r, u), n.texShape = h), null != i) { var f = ze(r), p = void 0, d = h[1], v = h[0], m = i instanceof Uint8Array; p = u ? (d = (e = ue(h[0], h[1]))[0], v = e[1], new Ki(f, [v, d], m)) : new ji(f, [v, d], m); var g = this.makeTensorInfo([v, d], o); this.texData.get(g.dataId).usage = m ? Jt.PIXELS : Jt.UPLOAD, this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId), d, v, i); var y = this.runWebGLProgram(p, [g], o, null, !0), x = this.texData.get(y.dataId); n.texture = x.texture, n.texShape = x.texShape, n.isPacked = x.isPacked, n.usage = x.usage, this.disposeData(g.dataId), this.texData.delete(y.dataId), n.values = null, l && (this.uploadWaitMs += tt() - c) } else { var b = this.acquireTexture(h, s, o, u); n.texture = b } } }, Ts.prototype.convertAndCacheOnCPU = function (t, e) { var n = this.texData.get(t), r = n.dtype; return this.releaseGPUData(t), null != e && (n.values = function (t, e) { if ("float32" === e || "complex64" === e) return t; if ("int32" !== e && "bool" !== e) throw new Error("Unknown dtype " + e); for (var n = "int32" === e ? new Int32Array(t.length) : new Uint8Array(t.length), r = 0; r < n.length; ++r)n[r] = Math.round(t[r]); return n }(e, r)), n.values }, Ts.prototype.acquireTexture = function (t, e, n, r) { if (this.numBytesInGPU += this.computeBytes(t, n), !this.warnedAboutMemory && this.numBytesInGPU > 1024 * this.numMBBeforeWarning * 1024) { var o = (this.numBytesInGPU / 1024 / 1024).toFixed(2); this.warnedAboutMemory = !0, console.warn("High memory usage in GPU: " + o + " MB, most likely due to a memory leak") } return this.textureManager.acquireTexture(t, e, r) }, Ts.prototype.computeBytes = function (t, e) { return t[0] * t[1] * U(e) }, Ts); function Ts(t) { var e, n = Ds.call(this) || this; if (n.pendingRead = new WeakMap, n.pendingDisposal = new WeakSet, n.dataRefCount = new WeakMap, n.numBytesInGPU = 0, n.uploadWaitMs = 0, n.downloadWaitMs = 0, n.warnedAboutMemory = !1, n.pendingDeletes = 0, n.disposed = !1, !_().getBool("HAS_WEBGL")) throw new Error("WebGL is not supported on this device"); if (null == t) { var r = ie(_().getNumber("WEBGL_VERSION")); n.binaryCache = ((e = _().getNumber("WEBGL_VERSION")) in ks || (ks[e] = {}), ks[e]), n.gpgpu = new xa(r), n.canvas = r.canvas, n.gpgpuCreatedLocally = !0 } else n.gpgpu = t, n.binaryCache = {}, n.gpgpuCreatedLocally = !1, n.canvas = t.gl.canvas; return n.textureManager = new ts(n.gpgpu), n.numMBBeforeWarning = null == _().global.screen ? 1024 : _().global.screen.height * _().global.screen.width * window.devicePixelRatio * 600 / 1024 / 1024, n.texData = new co(n, Kt), n } Xt() && Kt.registerBackend("webgl", function () { return new As }, 2); var Ns = wn({ square_: function (t) { var n = cn(t, "x", "square"), e = [n]; return Kt.runKernelFunc(function (t, e) { return e([n]), t.square(n) }, { x: n }, null, "Square", {}, e, []) } }), Fs = "SquaredDifference", Ms = wn({ squaredDifference_: function (t, e) { var n, r = cn(t, "a", "squaredDifference"), o = cn(e, "b", "squaredDifference"); n = Lt(r, o), r = n[0], o = n[1], go(r.shape, o.shape); var i = { a: r, b: o }, a = [r, o]; return Kt.runKernelFunc(function (t, e) { var n = t.squaredDifference(r, o); return e([r, o]), n }, i, function (t, e) { var n = e[0], r = e[1], o = kn(2); return { a: function () { return t.mul(n.sub(r).mul(o)) }, b: function () { return t.mul(r.sub(n).mul(o)) } } }, Fs, {}, a, []) } }), Os = wn({ abs_: function (t) { var r = cn(t, "x", "abs"); return "complex64" === r.dtype ? Kt.runKernelFunc(function (t) { return t.complexAbs(r) }, { $x: r }) : Kt.runKernelFunc(function (t, e) { var n = t.abs(r); return e([r]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return t.mul(n.toFloat().step(-1)) } } }, "Abs") } }), Ps = wn({ acos_: function (t) { var r = cn(t, "x", "acos"); return Kt.runKernelFunc(function (t, e) { var n = t.acos(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.divStrict(kn(1).sub(n.toFloat().square()).sqrt()).neg() } } }) } }), Bs = wn({ acosh_: function (t) { var r = cn(t, "x", "acosh"); return Kt.runKernelFunc(function (t, e) { var n = t.acosh(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.divStrict(n.toFloat().square().sub(1).sqrt()) } } }) } }), Ls = wn({ asin_: function (t) { var r = cn(t, "x", "asin"); return Kt.runKernelFunc(function (t, e) { var n = t.asin(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.divStrict(kn(1).sub(n.toFloat().square()).sqrt()) } } }) } }), Ws = wn({ asinh_: function (t) { var r = cn(t, "x", "asinh"); return Kt.runKernelFunc(function (t, e) { var n = t.asinh(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.divStrict(kn(1).add(n.toFloat().square()).sqrt()) } } }) } }), zs = wn({ atan_: function (t) { var r = cn(t, "x", "atan"); return Kt.runKernelFunc(function (t, e) { var n = t.atan(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.div(n.toFloat().square().add(1)) } } }) } }), Us = wn({ atanh_: function (t) { var r = cn(t, "x", "atanh"); return Kt.runKernelFunc(function (t, e) { var n = t.atanh(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.div(kn(1).sub(n.toFloat().square())) } } }) } }), Vs = wn({ ceil_: function (t) { var e = cn(t, "x", "ceil"); return Kt.runKernelFunc(function (t) { return t.ceil(e) }, { $x: e }, function (t) { return { $x: function () { return Un(t) } } }) } }), Gs = wn({ clipByValue_: function (t, r, o) { var i = cn(t, "x", "clipByValue"); P(r <= o, function () { return "Error in clip: min (" + r + ") must be less than or equal to max (" + o + ")." }); var e = [i], n = { min: r, max: o }; return Kt.runKernelFunc(function (t, e) { var n = t.clip(i, r, o); return e([i]), n }, { x: i }, function (t, e) { var n = e[0]; return { x: function () { return t.where(n.greaterEqual(r).logicalAnd(n.lessEqual(o)), Un(t)) } } }, "ClipByValue", n, e) } }), Hs = wn({ cos_: function (t) { var r = cn(t, "x", "cos"), e = [r]; return Kt.runKernelFunc(function (t, e) { var n = t.cos(r); return e([r]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return n.toFloat().sin().neg().mul(t) } } }, "Cos", {}, e) } }), qs = wn({ cosh_: function (t) { var r = cn(t, "x", "cosh"); return Kt.runKernelFunc(function (t, e) { var n = t.cosh(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return n.toFloat().sinh().mulStrict(t) } } }) } }), js = wn({ erf_: function (t) { var r = cn(t, "x", "erf"); return P("int32" === r.dtype || "float32" === r.dtype, function () { return "Input dtype must be `int32` or `float32`." }), "int32" === r.dtype && (r = r.toFloat()), Kt.runKernelFunc(function (t, e) { var n = t.erf(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.mul(n.square().neg().exp().mul(2 / Math.sqrt(Math.PI))) } } }) } }), Ks = wn({ exp_: function (t) { var r = cn(t, "x", "exp"); return Kt.runKernelFunc(function (t, e) { var n = t.exp(r); return e([n]), n }, { x: r }, function (t, e) { return { x: function () { return t.mulStrict(e[0]) } } }, "Exp", {}, [], [!0]) } }), Xs = wn({ expm1_: function (t) { var r = cn(t, "x", "expm1"); return Kt.runKernelFunc(function (t, e) { var n = t.expm1(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.mul(n.exp()) } } }) } }), Ys = wn({ floor_: function (t) { var e = cn(t, "x", "floor"); return Kt.runKernelFunc(function (t) { return t.floor(e) }, { $x: e }, function (t) { return { $x: function () { return Un(t) } } }) } }), $s = wn({ log_: function (t) { var r = cn(t, "x", "log"), e = [r]; return Kt.runKernelFunc(function (t, e) { var n = t.log(r); return e([r]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return t.div(n.toFloat()) } } }, "Log", {}, e) } }), Js = wn({ log1p_: function (t) { var r = cn(t, "x", "log1p"); return Kt.runKernelFunc(function (t, e) { var n = t.log1p(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.div(n.add(1)) } } }) } }), Qs = wn({ logSigmoid_: function (t) { var r = cn(t, "x", "logSigmoid"); return Kt.runKernelFunc(function (t, e) { var n = t.softplus(r.neg()).neg(); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.mul(n.neg().sigmoid()) } } }) } }), Zs = wn({ neg_: function (t) { var e = cn(t, "x", "neg"), n = [e]; return Kt.runKernelFunc(function (t) { return t.neg(e) }, { x: e }, function (t) { return { x: function () { return t.neg() } } }, "Neg", {}, n) } }), tu = wn({ reciprocal_: function (t) { var r = cn(t, "x", "reciprocal"); return Kt.runKernelFunc(function (t, e) { var n = t.reciprocal(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.div(n.square().neg()) } } }) } }), eu = wn({ round_: function (t) { var e = cn(t, "x", "round"); return Kt.runKernelFunc(function (t) { return t.round(e) }, { $x: e }, function (t) { return { $x: function () { return Un(t) } } }) } }), nu = wn({ rsqrt_: function (t) { var r = cn(t, "x", "rsqrt"), e = [r]; return Kt.runKernelFunc(function (t, e) { var n = t.rsqrt(r); return e([r]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return t.div(n.pow(1.5).mul(2)).neg() } } }, "Rsqrt", {}, e) } }), ru = wn({ sigmoid_: function (t) { var r = cn(t, "x", "sigmoid"); return Kt.runKernelFunc(function (t, e) { var n = t.sigmoid(r); return e([n]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return t.mul(n.mul(kn(1).sub(n))) } } }, "Sigmoid") } }), ou = wn({ sign_: function (t) { var e = cn(t, "x", "sign"); return Kt.runKernelFunc(function (t) { return t.sign(e) }, { $x: e }, function (t) { return { $x: function () { return Un(t) } } }) } }), iu = wn({ isNaN_: function (t) { var e = cn(t, "x", "isNaN"); return Kt.runKernelFunc(function (t) { return t.isNaN(e) }, { $x: e }, function (t) { return { $x: function () { return Un(t) } } }) } }), au = wn({ isInf_: function (t) { var e = cn(t, "x", "isInf"); return Kt.runKernelFunc(function (t) { return t.isInf(e) }, { $x: e }, function (t) { return { $x: function () { return Un(t) } } }) } }), su = wn({ isFinite_: function (t) { var e = cn(t, "x", "isFinite"); return Kt.runKernelFunc(function (t) { return t.isFinite(e) }, { $x: e }, function (t) { return { $x: function () { return Un(t) } } }) } }), uu = wn({ sin_: function (t) { var r = cn(t, "x", "sin"), e = [r]; return Kt.runKernelFunc(function (t, e) { var n = t.sin(r); return e([r]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return n.toFloat().cos().mul(t) } } }, "Sin", {}, e) } }), cu = wn({ sinh_: function (t) { var r = cn(t, "x", "sinh"); return Kt.runKernelFunc(function (t, e) { var n = t.sinh(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return n.toFloat().cosh().mulStrict(t) } } }) } }), lu = wn({ softplus_: function (t) { var r = cn(t, "x", "softplus"); return Kt.runKernelFunc(function (t, e) { var n = t.softplus(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.mul(n.sigmoid()) } } }) } }), hu = wn({ sqrt_: function (t) { var r = cn(t, "x", "sqrt"); return Kt.runKernelFunc(function (t, e) { var n = t.sqrt(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.div(n.toFloat().sqrt().mul(2)) } } }) } }), fu = wn({ step_: function (t, e) { void 0 === e && (e = 0); var n = cn(t, "x", "step"); return Kt.runKernelFunc(function (t) { return t.step(n, e) }, { $x: n }, function (t) { return { $x: function () { return Un(t) } } }) } }), pu = wn({ tan_: function (t) { var r = cn(t, "x", "tan"); return Kt.runKernelFunc(function (t, e) { var n = t.tan(r); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return t.div(n.cos().square()) } } }) } }), du = wn({ tanh_: function (t) { var r = cn(t, "x", "tanh"); return Kt.runKernelFunc(function (t, e) { var n = t.tanh(r); return e([n]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return kn(1).sub(n.square()).mulStrict(t) } } }, "Tanh", {}, null, [!0]) } }); function vu(t, e, n, r, o, i) { var a, s, u = cn(t, "x", "batchNorm"), c = cn(e, "mean", "batchNorm"), l = cn(n, "variance", "batchNorm"); return null != o && (a = cn(o, "scale", "batchNorm")), null != r && (s = cn(r, "offset", "batchNorm")), P(2 === u.rank, function () { return "Error in batchNorm3D: x must be rank 3 but got rank " + u.rank + "." }), P(2 === c.rank || 1 === c.rank, function () { return "Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank " + c.rank + "." }), P(2 === l.rank || 1 === l.rank, function () { return "Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank " + l.rank + "." }), null != a && P(2 === a.rank || 1 === a.rank, function () { return "Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank " + a.rank + "." }), null != s && P(2 === s.rank || 1 === s.rank, function () { return "Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank " + s.rank + "." }), yu(u, c, l, s, a, i) } function mu(t, e, n, r, o, i) { var a, s, u = cn(t, "x", "batchNorm"), c = cn(e, "mean", "batchNorm"), l = cn(n, "variance", "batchNorm"); return null != o && (a = cn(o, "scale", "batchNorm")), null != r && (s = cn(r, "offset", "batchNorm")), P(3 === u.rank, function () { return "Error in batchNorm3D: x must be rank 3 but got rank " + u.rank + "." }), P(3 === c.rank || 1 === c.rank, function () { return "Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank " + c.rank + "." }), P(3 === l.rank || 1 === l.rank, function () { return "Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank " + l.rank + "." }), null != a && P(3 === a.rank || 1 === a.rank, function () { return "Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank " + a.rank + "." }), null != s && P(3 === s.rank || 1 === s.rank, function () { return "Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank " + s.rank + "." }), yu(u, c, l, s, a, i) } function gu(t, e, n, r, o, i) { var a, s, u = cn(t, "x", "batchNorm"), c = cn(e, "mean", "batchNorm"), l = cn(n, "variance", "batchNorm"); return null != o && (a = cn(o, "scale", "batchNorm")), null != r && (s = cn(r, "offset", "batchNorm")), P(4 === u.rank, function () { return "Error in batchNorm4D: x must be rank 4 but got rank " + u.rank + "." }), P(4 === c.rank || 1 === c.rank, function () { return "Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank " + c.rank + "." }), P(4 === l.rank || 1 === l.rank, function () { return "Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank " + l.rank + "." }), null != a && P(4 === a.rank || 1 === a.rank, function () { return "Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank " + a.rank + "." }), null != s && P(4 === s.rank || 1 === s.rank, function () { return "Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank " + s.rank + "." }), yu(u, c, l, s, a, i) } function yu(t, e, n, r, o, v) { null == v && (v = .001); var i, a, m, s = cn(t, "x", "batchNorm"), u = cn(e, "mean", "batchNorm"), c = cn(n, "variance", "batchNorm"); null != o && (i = cn(o, "scale", "batchNorm")), null != r && (a = cn(r, "offset", "batchNorm")), P(u.rank === c.rank, function () { return "Batch normalization gradient requires mean and variance to have equal ranks." }), P(null == a || u.rank === a.rank, function () { return "Batch normalization gradient requires mean and offset to have equal ranks." }), P(null == i || u.rank === i.rank, function () { return "Batch normalization gradient requires mean and scale to have equal ranks." }), m = 0 === s.rank || 1 === s.rank ? s.as4D(1, 1, 1, s.size) : 2 === s.rank ? s.as4D(1, 1, s.shape[0], s.shape[1]) : 3 === s.rank ? s.as4D(1, s.shape[0], s.shape[1], s.shape[2]) : s; var l = [s, u, c, i]; return Kt.runKernelFunc(function (t, e) { var n = t.batchNormalization(m, xu(u), xu(c), v, xu(i), xu(a)); return e([s, u, c, i]), n }, { x: s, mean: u, variance: c, scale: i, offset: a }, function (n, t) { var e = t, r = e[0], o = e[1], i = e[2], a = e[3], s = null == a ? kn(1) : a, u = mo(o.shape, m.shape), c = []; if (1 === o.rank) { for (var l = 0; l < m.shape.length - 1; ++l)c.push(m.shape[l]); c.push(1) } var h = r.sub(o), f = n.mul(s), p = nu(i.add(kn(v))), d = p.mul(p).mul(p).mul(kn(-.5)); return { x: function () { return 1 === o.rank ? n.mul(Or(p.as4D(1, 1, 1, o.shape[0]), c)).mul(s).reshape(r.shape) : n.mul(p).mul(s).reshape(r.shape) }, mean: function () { var t = p.mul(kn(-1)).mul(f); return 1 === o.rank && (t = t.sum(u)), t.reshape(o.shape) }, variance: function () { var t = d.mul(h).mul(f); return 1 === o.rank && (t = t.sum(u)), t.reshape(o.shape) }, scale: function () { var t = h.mul(p), e = n.mul(t); return 1 === o.rank && (e = e.sum(u)), e.reshape(o.shape) }, offset: function () { var t = n; return 1 === o.rank && (t = t.sum(u)), t.reshape(o.shape) } } }, "BatchNormalization", { varianceEpsilon: v }, l).reshape(s.shape) } function xu(t) { return null == t ? null : 0 === t.rank ? t.as1D() : 1 === t.rank ? t : 2 === t.rank ? t.as4D(1, 1, t.shape[0], t.shape[1]) : 3 === t.rank ? t.as4D(1, t.shape[0], t.shape[1], t.shape[2]) : t } function bu() { en("tf.batchNormalization() is going away. Use tf.batchNorm() instead, and note the positional argument change of scale, offset, and varianceEpsilon") } function wu(o) { return y(this, void 0, void 0, function () { var e, n, r; return R(this, function (t) { switch (t.label) { case 0: return [4, (e = cn(o, "condition", "whereAsync", "bool")).data()]; case 1: return n = t.sent(), r = qo(e.shape, n), o !== e && e.dispose(), [2, r] } }) }) } var Cu = wn({ batchNormalization2d_: function (t, e, n, r, o, i) { return void 0 === r && (r = .001), bu(), vu(t, e, n, i, o, r) } }), Eu = wn({ batchNormalization3d_: function (t, e, n, r, o, i) { return void 0 === r && (r = .001), bu(), mu(t, e, n, i, o, r) } }), _u = wn({ batchNormalization4d_: function (t, e, n, r, o, i) { return void 0 === r && (r = .001), bu(), gu(t, e, n, i, o, r) } }), Iu = wn({ batchNormalization_: function (t, e, n, r, o, i) { return void 0 === r && (r = .001), bu(), yu(t, e, n, i, o, r) } }), Ru = wn({ batchNorm_: yu }), ku = wn({ batchNorm2d_: vu }), Su = wn({ batchNorm3d_: mu }), Du = wn({ batchNorm4d_: gu }), Au = wn({ logicalAnd_: function (t, e) { var n = cn(t, "a", "logicalAnd", "bool"), r = cn(e, "b", "logicalAnd", "bool"); return go(n.shape, r.shape), Kt.runKernelFunc(function (t) { return t.logicalAnd(n, r) }, { a: n, b: r }, null, "LogicalAnd") } }), Tu = wn({ logicalNot_: function (t) { var e = cn(t, "x", "logicalNot", "bool"); return Kt.runKernelFunc(function (t) { return t.logicalNot(e) }, { $x: e }) } }), Nu = wn({ logicalOr_: function (t, e) { var n = cn(t, "a", "logicalOr", "bool"), r = cn(e, "b", "logicalOr", "bool"); return go(n.shape, r.shape), Kt.runKernelFunc(function (t) { return t.logicalOr(n, r) }, { $a: n, $b: r }) } }), Fu = wn({ logicalXor_: function (t, e) { var n = cn(t, "a", "logicalXor", "bool"), r = cn(e, "b", "logicalXor", "bool"); return go(n.shape, r.shape), Nu(t, e).logicalAnd(Au(t, e).logicalNot()) } }), Mu = wn({ where_: function (t, e, n) { var r = cn(e, "a", "where"), o = cn(n, "b", "where"), i = cn(t, "condition", "where", "bool"); return x(r.shape, o.shape, "Error in where: "), 1 === i.rank ? P(i.shape[0] === r.shape[0], function () { return "The first dimension of `a` must match the size of `condition`." }) : x(i.shape, o.shape, "Error in where: "), Kt.runKernelFunc(function (t, e) { var n = t.select(i, r, o); return e([i]), n }, { $condition: i, $a: r, $b: o }, function (t, e) { var n = e[0]; return { $condition: function () { return Un(n).toFloat() }, $a: function () { return t.mul(n.cast(t.dtype)) }, $b: function () { return t.mul(n.logicalNot().cast(t.dtype)) } } }) } }), Ou = wn({ add_: function (t, e) { var n, r = cn(t, "a", "add"), o = cn(e, "b", "add"); n = Lt(r, o), r = n[0], o = n[1]; var i = go(r.shape, o.shape); return Kt.runKernelFunc(function (t) { return t.add(r, o) }, { a: r, b: o }, function (n) { return { a: function () { var t = n, e = mo(r.shape, i); return 0 < e.length && (t = t.sum(e)), t.reshape(r.shape) }, b: function () { var t = n, e = mo(o.shape, i); return 0 < e.length && (t = t.sum(e)), t.reshape(o.shape) } } }, "Add") } }), Pu = wn({ addN_: function (t) { P(Array.isArray(t), function () { return "The argument passed to tf.addN() must be a list of tensors" }), P(1 <= t.length, function () { return "Must pass at least one tensor to tf.addN(), but got " + t.length }); var e = t.map(function (t, e) { return cn(t, "tensors" + e, "addN") }), n = e[0]; e.forEach(function (t) { if (t.dtype !== n.dtype) throw new Error("All tensors passed to tf.addN() must have the same dtype") }), e.forEach(function (t) { if (!A(t.shape, n.shape)) throw new Error("All tensors passed to tf.addN() must have the same shape") }); var r = e; return Kt.runKernelFunc(function (t) { return t.addN(e) }, r, function (n) { var r = {}; return e.forEach(function (t, e) { r[e] = function () { return n.clone() } }), r }, "AddN") } }), Bu = wn({ addStrict_: function (t, e) { var n = cn(t, "a", "addStrict"), r = cn(e, "b", "addStrict"); return x(n.shape, r.shape, "Error in addStrict: "), n.add(r) } }), Lu = wn({ atan2_: function (t, e) { var n, r = cn(t, "a", "atan2"), o = cn(e, "b", "atan2"); n = Lt(r, o), r = n[0], o = n[1]; var a = go(r.shape, o.shape); return Kt.runKernelFunc(function (t, e) { var n = t.atan2(r, o); return e([r, o]), n }, { $a: r, $b: o }, function (r, t) { var o = t[0], i = t[1]; return { $a: function () { var t = Ou(o.square(), i.square()), e = r.mul(i.div(t)), n = mo(o.shape, a); return 0 < n.length && (e = e.sum(n)), e.reshape(o.shape) }, $b: function () { var t = Ou(o.square(), i.square()), e = Zs(r.mul(o.div(t))), n = mo(i.shape, a); return 0 < n.length && (e = e.sum(n)), e.reshape(i.shape) } } }) } }), Wu = wn({ div_: function (t, e) { var n, r = cn(t, "a", "div"), o = cn(e, "b", "div"); if (n = Lt(r, o), r = n[0], o = n[1], "int32" === r.dtype && "int32" === o.dtype) return Vu(r, o); var a = go(r.shape, o.shape); return Kt.runKernelFunc(function (t, e) { var n = t.realDivide(r, o); return e([r, o]), n }, { a: r, b: o }, function (r, t) { var o = t[0], i = t[1]; return { a: function () { var t = r.div(i.toFloat()), e = mo(o.shape, a); return 0 < e.length ? t.sum(e).reshape(o.shape) : t }, b: function () { var t = r.mul(o.toFloat()), e = mo(i.shape, a); 0 < e.length && (t = t.sum(e).reshape(i.shape)); var n = i.square(); return t.div(n.toFloat()).neg() } } }, "Div") } }), zu = wn({ divNoNan_: function (t, e) { var n, r = cn(t, "a", "div"), o = cn(e, "b", "div"); r = (n = Lt(r, o))[0], o = n[1]; var i = Wu(r, o), a = Un(i), s = o.equal(a); return Mu(s, a, i) } }), Uu = wn({ divStrict_: function (t, e) { var n = cn(t, "a", "div"), r = cn(e, "b", "div"); return x(n.shape, r.shape, "Error in divideStrict: "), n.div(r) } }), Vu = wn({ floorDiv_: function (t, e) { var n, r = cn(t, "a", "floorDiv"), o = cn(e, "b", "floorDiv"); n = Lt(r, o), r = n[0], o = n[1]; var a = go(r.shape, o.shape); return Kt.runKernelFunc(function (t, e) { var n = t.floorDiv(r, o); return e([r, o]), n }, { a: r, b: o }, function (r, t) { var o = t[0], i = t[1]; return { a: function () { var t = r.div(i.toFloat()), e = mo(o.shape, a); return 0 < e.length ? t.sum(e).reshape(o.shape) : t }, b: function () { var t = r.mul(o.toFloat()), e = mo(i.shape, a); 0 < e.length && (t = t.sum(e).reshape(i.shape)); var n = i.square(); return t.div(n.toFloat()).neg() } } }, "FloorDiv") } }), Gu = wn({ maximum_: function (t, e) { var n, r = cn(t, "a", "maximum"), o = cn(e, "b", "maximum"); return n = Lt(r, o), r = n[0], o = n[1], "bool" === r.dtype && (r = r.toInt(), o = o.toInt()), go(r.shape, o.shape), Kt.runKernelFunc(function (t, e) { var n = t.maximum(r, o); return e([r, o]), n }, { a: r, b: o }, function (t, e) { var n = e[0], r = e[1]; return { a: function () { return t.mul(n.greaterEqual(r).toFloat()) }, b: function () { return t.mul(n.less(r).toFloat()) } } }, "Maximum") } }), Hu = wn({ maximumStrict_: function (t, e) { var n = cn(t, "a", "maximumStrict"), r = cn(e, "b", "maximumStrict"); return x(n.shape, r.shape, "Error in maximumStrict: "), n.maximum(r) } }), qu = wn({ minimum_: function (t, e) { var n, r = cn(t, "a", "minimum"), o = cn(e, "b", "minimum"); return n = Lt(r, o), r = n[0], o = n[1], "bool" === r.dtype && (r = r.toInt(), o = o.toInt()), go(r.shape, o.shape), Kt.runKernelFunc(function (t, e) { var n = t.minimum(r, o); return e([r, o]), n }, { a: r, b: o }, function (t, e) { var n = e[0], r = e[1]; return { a: function () { return t.mul(n.lessEqual(r).toFloat()) }, b: function () { return t.mul(n.greater(r).toFloat()) } } }, "Minimum") } }), ju = wn({ minimumStrict_: function (t, e) { var n = cn(t, "a", "minimumStrict"), r = cn(e, "b", "minimumStrict"); return x(n.shape, r.shape, "Error in minimumStrict: "), n.minimum(r) } }), Ku = wn({ mod_: function (t, e) { var n, r = cn(t, "a", "mod"), o = cn(e, "b", "mod"); n = Lt(r, o), r = n[0], o = n[1]; var i = go(r.shape, o.shape); return Kt.runKernelFunc(function (t, e) { var n = t.mod(r, o); return e([r, o]), n }, { $a: r, $b: o }, function (n, t) { var r = t[0], o = t[1]; return { $a: function () { var t = mo(r.shape, i); return 0 < t.length ? n.sum(t).reshape(r.shape) : n }, $b: function () { var t = n.mul(r.div(o).floor().neg()), e = mo(o.shape, i); return 0 < e.length ? t.sum(e).reshape(o.shape) : t } } }) } }), Xu = wn({ modStrict_: function (t, e) { var n = cn(t, "a", "modStrict"), r = cn(e, "b", "modStrict"); return x(n.shape, r.shape, "Error in modStrict: "), n.mod(r) } }), Yu = wn({ mul_: function (t, e) { var n, r = cn(t, "a", "mul"), o = cn(e, "b", "mul"); n = Lt(r, o), r = n[0], o = n[1]; var i = go(r.shape, o.shape); return Kt.runKernelFunc(function (t, e) { var n = t.multiply(r, o); return e([r, o]), n }, { a: r, b: o }, function (n, t) { var r = t[0], o = t[1]; return { a: function () { var t = n.mul(o.toFloat()), e = mo(r.shape, i); return 0 < e.length ? t.sum(e).reshape(r.shape) : t }, b: function () { var t = n.mul(r.toFloat()), e = mo(o.shape, i); return 0 < e.length ? t.sum(e).reshape(o.shape) : t } } }, "Mul") } }), $u = wn({ mulStrict_: function (t, e) { var n = cn(t, "a", "mul"), r = cn(e, "b", "mul"); return x(n.shape, r.shape, "Error in multiplyStrict: "), n.mul(r) } }), Ju = wn({ pow_: function (t, e) { var n, r = cn(t, "base", "pow"), o = cn(e, "exp", "pow"); n = Lt(r, o), r = n[0], o = n[1]; var u = go(r.shape, o.shape), i = [r, o]; return Kt.runKernelFunc(function (t, e) { var n = t.pow(r, o); return e([r, o, n]), n }, { a: r, b: o }, function (o, t) { var i = t[0], a = t[1], s = t[2]; return { a: function () { var t = a.toFloat(), e = o.mul(t.mul(i.pow(t.sub(kn(1))))), n = mo(i.shape, u); return 0 < n.length && (e = e.sum(n)), e.reshape(i.shape) }, b: function () { var t = i.greater(0), e = i.log().where(t, Un(i)), n = o.mul(s.mul(e)), r = mo(a.shape, u); return 0 < r.length && (n = n.sum(r)), n.reshape(a.shape) } } }, "Pow", {}, i, [!0]) } }), Qu = wn({ powStrict_: function (t, e) { return x(t.shape, e.shape, "Error in powStrict: "), t.pow(e) } }), Zu = wn({ squaredDifferenceStrict_: function (t, e) { var n = cn(t, "a", "squaredDifferenceStrict"), r = cn(e, "b", "squaredDifferenceStrict"); return x(n.shape, r.shape, "Error in squaredDifferenceStrict: "), n.squaredDifference(r) } }), tc = wn({ sub_: function (t, e) { var n, r = cn(t, "a", "sub"), o = cn(e, "b", "sub"); n = Lt(r, o), r = n[0], o = n[1]; var i = go(r.shape, o.shape); return Kt.runKernelFunc(function (t) { return t.subtract(r, o) }, { a: r, b: o }, function (n) { return { a: function () { var t = n, e = mo(r.shape, i); return 0 < e.length && (t = t.sum(e)), t.reshape(r.shape) }, b: function () { var t = n, e = mo(o.shape, i); return 0 < e.length && (t = t.sum(e)), t.neg().reshape(o.shape) } } }, "Sub") } }), ec = wn({ subStrict_: function (t, e) { var n = cn(t, "a", "subStrict"), r = cn(e, "b", "subStrict"); return x(n.shape, r.shape, "Error in subStrict: "), n.sub(r) } }), nc = wn({ equal_: function (t, e) { var n, r = cn(t, "a", "equal"), o = cn(e, "b", "equal"); return n = Lt(r, o), r = n[0], o = n[1], go(r.shape, o.shape), Kt.runKernelFunc(function (t) { return t.equal(r, o) }, { $a: r, $b: o }) } }), rc = wn({ equalStrict_: function (t, e) { var n = cn(t, "a", "equalStrict"), r = cn(e, "b", "equalStrict"); return x(n.shape, r.shape, "Error in equalStrict: "), n.equal(r) } }), oc = wn({ greater_: function (t, e) { var n, r = cn(t, "a", "greater"), o = cn(e, "b", "greater"); return n = Lt(r, o), r = n[0], o = n[1], go(r.shape, o.shape), Kt.runKernelFunc(function (t) { return t.greater(r, o) }, { a: r, b: o }, null, "Greater") } }), ic = wn({ greaterEqual_: function (t, e) { var n, r = cn(t, "a", "greaterEqual"), o = cn(e, "b", "greaterEqual"); return n = Lt(r, o), r = n[0], o = n[1], go(r.shape, o.shape), Kt.runKernelFunc(function (t, e) { var n = t.greaterEqual(r, o); return e([r, o]), n }, { a: r, b: o }, function (t, e) { var n = e[0], r = e[1]; return { a: function () { return Un(n) }, b: function () { return Un(r) } } }, "GreaterEqual") } }), ac = wn({ greaterEqualStrict_: function (t, e) { var n = cn(t, "a", "greaterEqualStrict"), r = cn(e, "b", "greaterEqualStrict"); return x(n.shape, r.shape, "Error in greaterEqualStrict: "), n.greaterEqual(r) } }), sc = wn({ greaterStrict_: function (t, e) { var n = cn(t, "a", "greaterStrict"), r = cn(e, "b", "greaterStrict"); return x(n.shape, r.shape, "Error in greaterStrict: "), n.greater(r) } }), uc = wn({ less_: function (t, e) { var n, r = cn(t, "a", "less"), o = cn(e, "b", "less"); return n = Lt(r, o), r = n[0], o = n[1], go(r.shape, o.shape), Kt.runKernelFunc(function (t) { return t.less(r, o) }, { a: r, b: o }, null, "Less") } }), cc = wn({ lessEqual_: function (t, e) { var n, r = cn(t, "a", "lessEqual"), o = cn(e, "b", "lessEqual"); return n = Lt(r, o), r = n[0], o = n[1], go(r.shape, o.shape), Kt.runKernelFunc(function (t, e) { var n = t.lessEqual(r, o); return e([r, o]), n }, { a: r, b: o }, null, "LessEqual") } }), lc = wn({ lessEqualStrict_: function (t, e) { var n = cn(t, "a", "lessEqualStrict"), r = cn(e, "b", "lessEqualStrict"); return x(n.shape, r.shape, "Error in lessEqualStrict: "), n.lessEqual(r) } }), hc = wn({ lessStrict_: function (t, e) { var n = cn(t, "a", "lessStrict"), r = cn(e, "b", "lessStrict"); return x(n.shape, r.shape, "Error in lessStrict: "), n.less(r) } }), fc = wn({ notEqual_: function (t, e) { var n, r = cn(t, "a", "notEqual"), o = cn(e, "b", "notEqual"); return n = Lt(r, o), r = n[0], o = n[1], go(r.shape, o.shape), Kt.runKernelFunc(function (t) { return t.notEqual(r, o) }, { a: r, b: o }, null, "NotEqual") } }), pc = wn({ notEqualStrict_: function (t, e) { var n = cn(t, "a", "notEqualStrict"), r = cn(e, "b", "notEqualStrict"); return x(n.shape, r.shape, "Error in notEqualStrict: "), n.notEqual(r) } }); function dc(t, e) { for (var n = [], r = t; r < e; ++r)n.push(r); return n } function vc(t) { for (var e = [], n = 0; n < t.length; ++n)for (var r = 0; r < t[n].length; ++r)e.push(t[n][r]); return e } function mc(d, v, m) { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p; return R(this, function (t) { switch (t.label) { case 0: for (e = cn(d, "tensor", "boolMask"), n = cn(v, "mask", "boolMask", "bool"), r = null == m ? 0 : m, o = n.rank, i = e.shape, P(0 < o, function () { return "mask cannot be scalar" }), x(i.slice(r, r + o), n.shape, "mask's shape must match the first K dimensions of tensor's shape,"), a = 1, s = r; s < r + o; s++)a *= i[s]; return u = i.slice(0, r).concat([a], i.slice(r + o)), c = e.reshape(u), l = n.reshape([-1]), [4, wu(l)]; case 1: return h = t.sent(), f = h.squeeze([1]), p = gc(c, f, r), d !== e && e.dispose(), v !== n && n.dispose(), f.dispose(), c.dispose(), l.dispose(), h.dispose(), [2, p] } }) }) } var gc = wn({ gather_: function (t, e, g) { void 0 === g && (g = 0); var y = cn(t, "x", "gather"), r = cn(e, "indices", "gather", "int32"); g = D(g, y.shape)[0]; var n = function (t, e, n) { for (var r = t.shape[n], o = [], i = 1, a = 1, s = 0; s < n; s++)o.push(t.shape[s]), i *= t.shape[s]; for (s = 0; s < e.rank; s++)o.push(e.shape[s]); for (s = n + 1; s < t.rank; s++)o.push(t.shape[s]), a *= t.shape[s]; return { batchSize: i, sliceSize: a, dimSize: r, outputShape: o } }(y, r, g); return Kt.runKernelFunc(function (t, e) { var n = t.gather(y, r.flatten(), g); return e([r]), n }, { x: y, indices: r }, function (v, t) { var m = t[0]; return { x: function () { var t = y.shape, e = m.size, n = t.slice(0, g), r = n.length, o = t.slice(g, t.length).slice(1), i = o.length, a = dc(0, r), s = dc(r + 1, r + 1 + i), u = vc([n, [e], o]), c = v.reshape(u), l = m.reshape([e]), h = vc([[r], a, s]), f = c.transpose(h), p = yc(f, l, y.shape[g]), d = gn(h); return p.transpose(d) }, indices: function () { return m } } }, "Gather", { axis: g }).reshape(n.outputShape) } }), yc = wn({ unsortedSegmentSum_: function (t, e, r) { var o = cn(t, "x", "unsortedSegmentSum"), i = cn(e, "segmentIds", "unsortedSegmentSum", "int32"); return P(B(r), function () { return "numSegments must be of dtype int" }), Kt.runKernelFunc(function (t, e) { var n = t.unsortedSegmentSum(o, i, r); return e([i]), n }, { $x: o }, function (t, e) { var n = e[0]; return { $x: function () { return function (t, e) { for (var n = Gu(e, Un(e)), r = gc(t, n), o = ic(e, kn(0, "int32")), i = r.rank - o.rank, a = 0; a < i; ++a)o = yr(o, a + 1); o = Au(o, On(r.shape, "bool")); var s = Un(r); return Mu(o, r, s) }(t, n) } } }) } }); function xc(t, e, r, o, i, a, s) { void 0 === a && (a = "NHWC"), P(t.length === e.rank, function () { return "Length of inShape (" + t.length + ") and rank of dy (" + e.rank + ") must match" }); var n = t, u = e, c = !1; 3 === e.rank && (c = !0, u = e.as4D(1, e.shape[0], e.shape[1], e.shape[2]), n = [1, t[0], t[1], t[2]]), P(4 === n.length, function () { return "Error in conv2dDerInput: inShape must be length 4, but got length " + n.length + "." }), P(4 === u.rank, function () { return "Error in conv2dDerInput: dy must be rank 4, but got rank " + u.rank }), P(4 === r.rank, function () { return "Error in conv2dDerInput: filter must be rank 4, but got rank " + r.rank }); var l = "NHWC" === a ? n[3] : n[1], h = "NHWC" === a ? u.shape[3] : u.shape[1]; P(l === r.shape[2], function () { return "Error in conv2dDerInput: depth of input (" + l + ") must match input depth for filter " + r.shape[2] + "." }), P(h === r.shape[3], function () { return "Error in conv2dDerInput: depth of output (" + h + ") must match output depth for filter " + r.shape[3] + "." }), null != s && P(B(i), function () { return "Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode " + s + " but got pad " + i + "." }); var f = Do(a), p = bo(n, r.shape, o, 1, i, s, !1, f), d = Kt.runKernelFunc(function (t, e) { var n = t.conv2dDerInput(u, r, p); return e([r, u]), n }, { dy4D: u, filter: r }, function (t, e) { var n = e[0], r = e[1]; return { dy4D: function () { return Ec(t, n, o, i, a, 1, s) }, filter: function () { return Ic(t, r, n.shape, o, i, a, s) } } }); return c ? d.as3D(d.shape[1], d.shape[2], d.shape[3]) : d } function bc(t) { var e, n = "number" == typeof (e = t) ? [e, e, e] : 2 === e.length ? [e[0], e[1], 1] : e, r = n[0], o = n[1], i = n[2]; return 1 === r && 1 === o && 1 === i } function wc(t, e, n, r, o) { P(t.length === e.rank, function () { return "Length of inShape (" + t.length + ") and rank of dy (" + e.rank + ") must match" }); var i = t, a = e, s = !1; 4 === e.rank && (s = !0, a = e.as5D(1, e.shape[0], e.shape[1], e.shape[2], e.shape[3]), i = [1, t[0], t[1], t[2], t[3]]); var u = i[4], c = a.shape[4]; P(5 === i.length, function () { return "Error in conv3dDerInput: inShape must be length 5, but got length " + i.length + "." }), P(5 === a.rank, function () { return "Error in conv3dDerInput: dy must be rank 5, but got rank " + a.rank }), P(5 === n.rank, function () { return "Error in conv3dDerInput: filter must be rank 5, but got rank " + n.rank }), P(u === n.shape[3], function () { return "Error in conv3dDerInput: depth of input (" + u + ") must match input depth for filter " + n.shape[3] + "." }), P(c === n.shape[4], function () { return "Error in conv3dDerInput: depth of output (" + c + ") must match output depth for filter " + n.shape[4] + "." }); var l = wo(i, n.shape, r, 1, o), h = Kt.runKernelFunc(function (t) { return t.conv3dDerInput(a, n, l) }, { dy5D: a }); return s ? h.as4D(h.shape[1], h.shape[2], h.shape[3], h.shape[4]) : h } var Cc = wn({ conv1d_: function (t, e, n, r, o, i, a) { void 0 === o && (o = "NWC"), void 0 === i && (i = 1); var s = cn(t, "x", "conv1d"), u = cn(e, "filter", "conv1d"), c = s, l = !1; 2 === s.rank && (l = !0, c = s.as3D(1, s.shape[0], s.shape[1])), P(3 === c.rank, function () { return "Error in conv1d: input must be rank 3, but got rank " + c.rank + "." }), P(3 === u.rank, function () { return "Error in conv1d: filter must be rank 3, but got rank " + u.rank + "." }), null != a && P(B(r), function () { return "Error in conv1d: pad must be an integer when using, dimRoundingMode " + a + " but got pad " + r + "." }), P(c.shape[2] === u.shape[1], function () { return "Error in conv1d: depth of input (" + c.shape[2] + ") must match input depth for filter " + u.shape[1] + "." }), P(So(n, i), function () { return "Error in conv1D: Either stride or dilation must be 1. Got stride " + n + " and dilation '" + i + "'" }), P("NWC" === o, function () { return "Error in conv1d: got dataFormat of " + o + " but only NWC is currently supported." }); var h = u.as4D(1, u.shape[0], u.shape[1], u.shape[2]), f = c.as4D(c.shape[0], 1, c.shape[1], c.shape[2]), p = Ec(f, h, [1, n], r, "NHWC", [1, i], a); return l ? p.as2D(p.shape[2], p.shape[3]) : p.as3D(p.shape[0], p.shape[2], p.shape[3]) } }), Ec = wn({ conv2d_: function (t, e, i, a, s, u, n) { void 0 === s && (s = "NHWC"), void 0 === u && (u = [1, 1]); var r = cn(t, "x", "conv2d"), o = cn(e, "filter", "conv2d"), c = r, l = !1; 3 === r.rank && (l = !0, c = r.as4D(1, r.shape[0], r.shape[1], r.shape[2])), P(4 === c.rank, function () { return "Error in conv2d: input must be rank 4, but got rank " + c.rank + "." }), P(4 === o.rank, function () { return "Error in conv2d: filter must be rank 4, but got rank " + o.rank + "." }), null != n && P(B(a), function () { return "Error in conv2d: pad must be an integer when using, dimRoundingMode " + n + " but got pad " + a + "." }); var h = "NHWC" === s ? c.shape[3] : c.shape[1]; P(h === o.shape[2], function () { return "Error in conv2d: depth of input (" + h + ") must match input depth for filter " + o.shape[2] + "." }), P(So(i, u), function () { return "Error in conv2D: Either strides or dilations must be 1. Got strides " + i + " and dilations '" + u + "'" }); var f = Do(s), p = bo(c.shape, o.shape, i, u, a, n, !1, f), d = [o, c], v = Kt.runKernelFunc(function (t, e) { var n = t.conv2d(c, o, p); return e([o, c]), n }, { x: c, filter: o }, function (t, e) { var n = e, r = n[0], o = n[1]; return P(ko(u), function () { return "Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '" + u + "'" }), { x: function () { return Rc(o.shape, t, r, i, a, s) }, filter: function () { return Ic(o, t, r.shape, i, a, s) } } }, "Conv2D", p, d); return l ? v.as3D(v.shape[1], v.shape[2], v.shape[3]) : v } }), _c = wn({ conv3d_: function (t, e, o, i, n, a) { void 0 === n && (n = "NDHWC"), void 0 === a && (a = [1, 1, 1]); var r, s = cn(t, "x", "conv3d"), u = cn(e, "filter", "conv3d"), c = s, l = !1; 4 === s.rank && (l = !0, c = s.as5D(1, s.shape[0], s.shape[1], s.shape[2], s.shape[3])), P(5 === c.rank, function () { return "Error in conv3d: input must be rank 5, but got rank " + c.rank + "." }), P(5 === u.rank, function () { return "Error in conv3d: filter must be rank 5, but got rank " + u.rank + "." }), P(c.shape[4] === u.shape[3], function () { return "Error in conv3d: depth of input (" + c.shape[4] + ") must match input depth for filter " + u.shape[3] + "." }), P((r = a, bc(o) || bc(r)), function () { return "Error in conv3D: Either strides or dilations must be 1. Got strides " + o + " and dilations '" + a + "'" }), P("NDHWC" === n, function () { return "Error in conv3d: got dataFormat of " + n + " but only NDHWC is currently supported." }); var h = wo(c.shape, u.shape, o, a, i), f = Kt.runKernelFunc(function (t, e) { var n = t.conv3d(c, u, h); return e([c, u]), n }, { x: c, $filter: u }, function (t, e) { P(bc(a), function () { return "Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '" + a + "'" }); var n = e[0], r = e[1]; return { x: function () { return wc(n.shape, t, r, o, i) }, $filter: function () { return function (t, e, n, r, o) { var i = t; 4 === t.rank && (i = t.as5D(1, t.shape[0], t.shape[1], t.shape[2], t.shape[3])); var a = e; 4 === a.rank && (a = e.as5D(1, e.shape[0], e.shape[1], e.shape[2], e.shape[3])), P(5 === i.rank, function () { return "Error in conv3dDerFilter: input must be rank 5, but got shape " + i.shape + "." }), P(5 === a.rank, function () { return "Error in conv3dDerFilter: dy must be rank 5, but got shape " + a.shape + "." }), P(5 === n.length, function () { return "Error in conv3dDerFilter: filterShape must be length 5, but got " + n + "." }), P(i.shape[4] === n[3], function () { return "Error in conv3dDerFilter: depth of input " + i.shape[4] + ") must match input depth in filter (" + n[3] + "." }), P(a.shape[4] === n[4], function () { return "Error in conv3dDerFilter: depth of dy (" + a.shape[4] + ") must match output depth for filter (" + n[4] + ")." }); var s = wo(i.shape, n, r, 1, o); return Kt.runKernelFunc(function (t) { return t.conv3dDerFilter(i, a, s) }, { x5D: i, dy5D: a }) }(n, t, r.shape, o, i) } } }); return l ? f.as4D(f.shape[1], f.shape[2], f.shape[3], f.shape[4]) : f } }), Ic = wn({ conv2dDerFilter_: function (t, e, n, r, o, i, a) { void 0 === i && (i = "NHWC"); var s = t; 3 === t.rank && (s = t.as4D(1, t.shape[0], t.shape[1], t.shape[2])); var u = e; 3 === u.rank && (u = e.as4D(1, e.shape[0], e.shape[1], e.shape[2])), P(4 === s.rank, function () { return "Error in conv2dDerFilter: input must be rank 4, but got shape " + s.shape + "." }), P(4 === u.rank, function () { return "Error in conv2dDerFilter: dy must be rank 4, but got shape " + u.shape + "." }), P(4 === n.length, function () { return "Error in conv2dDerFilter: filterShape must be length 4, but got " + n + "." }); var c = "NHWC" === i ? s.shape[3] : s.shape[1], l = "NHWC" === i ? u.shape[3] : u.shape[1]; P(c === n[2], function () { return "Error in conv2dDerFilter: depth of input " + c + ") must match input depth in filter (" + n[2] + "." }), P(l === n[3], function () { return "Error in conv2dDerFilter: depth of dy (" + l + ") must match output depth for filter (" + n[3] + ")." }), null != a && P(B(o), function () { return "Error in conv2dDerFilter: pad must be an integer when using, dimRoundingMode " + a + " but got pad " + o + "." }); var h = Do(i), f = bo(s.shape, n, r, 1, o, a, !1, h); return Kt.runKernelFunc(function (t) { return t.conv2dDerFilter(s, u, f) }, { x4D: s, dy4D: u }) } }), Rc = wn({ conv2dDerInput_: xc }), kc = wn({ depthwiseConv2d_: function (t, e, n, r, o, i, a) { void 0 === i && (i = [1, 1]); var s = cn(t, "x", "depthwiseConv2d"), u = cn(e, "filter", "depthwiseConv2d"), c = s, l = !1; 3 === s.rank && (l = !0, c = s.as4D(1, s.shape[0], s.shape[1], s.shape[2])), P(4 === c.rank, function () { return "Error in depthwiseConv2d: input must be rank 4, but got rank " + c.rank + "." }), P(4 === u.rank, function () { return "Error in depthwiseConv2d: filter must be rank 4, but got rank " + u.rank + "." }), P(c.shape[3] === u.shape[2], function () { return "Error in depthwiseConv2d: number of input channels (" + c.shape[3] + ") must match the inChannels dimension in filter " + u.shape[2] + "." }), null == i && (i = [1, 1]), P(So(n, i), function () { return "Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides " + n + " and dilations '" + i + "'" }), null != a && P(B(r), function () { return "Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode " + a + " but got pad " + r + "." }); var h = bo(c.shape, u.shape, n, i, r, a, !0), f = [c, u], p = Kt.runKernelFunc(function (t, e) { var n = t.depthwiseConv2D(c, u, h); return e([c, u]), n }, { x: c, filter: u }, function (t, e) { P(ko(i), function () { return "Error in gradient of depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '" + i + "'" }); var n = e[0], r = e[1]; return { x: function () { return Sc(n.shape, t, r, h) }, filter: function () { return Dc(n, t, r.shape, h) } } }, "DepthwiseConv2dNative", h, f); return l ? p.as3D(p.shape[1], p.shape[2], p.shape[3]) : p } }), Sc = wn({ depthwiseConv2dDerInput_: function (t, e, n, r) { var o = e, i = !1; 3 === e.rank && (i = !0, o = e.as4D(1, e.shape[0], e.shape[1], e.shape[2])); var a = Kt.runKernelFunc(function (t) { return t.depthwiseConv2DDerInput(o, n, r) }, { dy4D: o }); return i ? a.as3D(a.shape[1], a.shape[2], a.shape[3]) : a } }), Dc = wn({ depthwiseConv2dDerFilter_: function (t, e, n, r) { var o = t; 3 === t.rank && (o = t.as4D(1, t.shape[0], t.shape[1], t.shape[2])); var i = e; return 3 === i.rank && (i = e.as4D(1, e.shape[0], e.shape[1], e.shape[2])), Kt.runKernelFunc(function (t) { return t.depthwiseConv2DDerFilter(o, i, r) }, { x4D: o, dy4D: i }) } }), Ac = wn({ separableConv2d_: function (t, e, n, r, o, i, a) { void 0 === i && (i = [1, 1]), void 0 === a && (a = "NHWC"); var s = cn(t, "x", "separableConv2d"), u = cn(e, "depthwiseFilter", "separableConv2d"), c = cn(n, "pointwiseFilter", "separableConv2d"), l = s, h = !1; if (3 === s.rank && (h = !0, l = s.as4D(1, s.shape[0], s.shape[1], s.shape[2])), "NCHW" === a) throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported"); P(4 === l.rank, function () { return "Error in separableConv2d: input must be rank 4, but got rank " + l.rank + "." }), P(4 === u.rank, function () { return "Error in separableConv2d: depthwise filter must be rank 4, but got rank " + u.rank + "." }), P(4 === c.rank, function () { return "Error in separableConv2d: pointwise filter must be rank 4, but got rank " + u.rank + "." }), P(1 === c.shape[0], function () { return "Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got " + c.shape[0] + "." }), P(1 === c.shape[1], function () { return "Error in separableConv2d: the second dimension of pointwise filter must be 1, but got " + c.shape[1] + "." }); var f = u.shape[2], p = u.shape[3]; P(c.shape[2] === f * p, function () { return "Error in separableConv2d: the third dimension of pointwise filter must be " + f * p + ", but got " + c.shape[2] + "." }); var d = kc(l, u, r, o, a, i), v = Ec(d, c, 1, "valid", a); return h ? v.as3D(v.shape[1], v.shape[2], v.shape[3]) : v } }), Tc = wn({ conv2dTranspose_: function (t, e, n, r, o, i) { return xc(n, cn(t, "x", "conv2dTranspose"), cn(e, "filter", "conv2dTranspose"), r, o, "NHWC", i) } }), Nc = wn({ conv3dTranspose_: function (t, e, n, r, o) { return wc(n, cn(t, "x", "conv3dTranspose"), cn(e, "filter", "conv3dTranspose"), r, o) } }), Fc = wn({ matMul_: function (t, e, i, a) { var n; void 0 === i && (i = !1), void 0 === a && (a = !1); var r = cn(t, "a", "matMul"), o = cn(e, "b", "matMul"); n = Lt(r, o), r = n[0], o = n[1]; var s = i ? r.shape[r.rank - 2] : r.shape[r.rank - 1], u = a ? o.shape[o.rank - 1] : o.shape[o.rank - 2], c = i ? r.shape[r.rank - 1] : r.shape[r.rank - 2], l = a ? o.shape[o.rank - 2] : o.shape[o.rank - 1], h = r.shape.slice(0, -2), f = o.shape.slice(0, -2), p = L(h), d = L(f); P(2 <= r.rank && 2 <= o.rank && r.rank === o.rank, function () { return "Error in matMul: inputs must have the same rank of at least 2, got ranks " + r.rank + " and " + o.rank + "." }), P(A(h, f), function () { return "Error in matMul: outer dimensions (" + h + ") and (" + f + ") of Tensors with shapes " + r.shape + " and " + o.shape + " must match." }), P(s === u, function () { return "Error in matMul: inner shapes (" + s + ") and (" + u + ") of Tensors with shapes " + r.shape + " and " + o.shape + " and transposeA=" + i + " and transposeB=" + a + " must match." }); var v = r.shape.slice(0, -2).concat([c, l]), m = i ? r.as3D(p, s, c) : r.as3D(p, c, s), g = a ? o.as3D(d, l, u) : o.as3D(d, u, l), y = { transposeA: i, transposeB: a }; return Kt.runKernelFunc(function (t, e) { var n = t.batchMatMul(m, g, i, a); return e([m, g]), n }, { a: m, b: g }, function (t, e) { var n = e, r = n[0], o = n[1]; return i || a ? !i && a ? { a: function () { return t.matMul(o, !1, !1) }, b: function () { return t.matMul(r, !0, !1) } } : i && !a ? { a: function () { return o.matMul(t, !1, !0) }, b: function () { return r.matMul(t, !1, !1) } } : { a: function () { return o.matMul(t, !0, !0) }, b: function () { return t.matMul(r, !0, !0) } } : { a: function () { return t.matMul(o, !1, !0) }, b: function () { return r.matMul(t, !0, !1) } } }, "BatchMatMul", y).reshape(v) } }), Mc = wn({ dot_: function (t, e) { var n = cn(t, "t1", "dot"), r = cn(e, "t2", "dot"); P(!(1 !== n.rank && 2 !== n.rank || 1 !== r.rank && 2 !== r.rank), function () { return "Error in dot: inputs must all be rank 1 or 2, but got ranks " + n.rank + " and " + r.rank + "." }); var o = 1 === n.rank ? n.size : n.shape[1], i = 1 === r.rank ? r.size : r.shape[0]; return P(o === i, function () { return "Error in dot: inner dimensions of inputs must match, but got " + o + " and " + i + "." }), 1 === n.rank && 1 === r.rank ? n.as2D(1, -1).matMul(r.as2D(-1, 1)).asScalar() : 1 === n.rank && 2 === r.rank ? n.as2D(1, -1).matMul(r.as2D(r.shape[0], r.shape[1])).as1D() : 2 === n.rank && 1 === r.rank ? n.matMul(r.as2D(-1, 1)).as1D() : n.matMul(r.as2D(r.shape[0], r.shape[1])) } }), Oc = wn({ outerProduct_: function (t, e) { var n = cn(t, "v1", "outerProduct"), r = cn(e, "v2", "outerProduct"); return P(1 === n.rank && 1 === r.rank, function () { return "Error in outerProduct: inputs must be rank 1, but got ranks " + n.rank + " and " + r.rank + "." }), n.as2D(-1, 1).matMul(r.as2D(1, -1)) } }), Pc = wn({ reverse_: function (t, e) { var n = cn(t, "x", "reverse"); if (0 === n.rank) return n.clone(); var r = D(e, n.shape); return Kt.runKernelFunc(function (t) { return t.reverse(n, r) }, { $x: n }, function (t) { return { $x: function () { return t.reverse(r) } } }).reshapeAs(n) } }), Bc = wn({ reverse1d_: function (t) { var e = cn(t, "x", "reverse"); return P(1 === e.rank, function () { return "Error in reverse1D: x must be rank 1 but got rank " + e.rank + "." }), Pc(e, 0) } }), Lc = wn({ reverse2d_: function (t, e) { var n = cn(t, "x", "reverse"); return P(2 === n.rank, function () { return "Error in reverse2D: x must be rank 2 but got rank " + n.rank + "." }), Pc(n, e) } }), Wc = wn({ reverse3d_: function (t, e) { var n = cn(t, "x", "reverse"); return P(3 === n.rank, function () { return "Error in reverse3D: x must be rank 3 but got rank " + n.rank + "." }), Pc(n, e) } }), zc = wn({ reverse4d_: function (t, e) { var n = cn(t, "x", "reverse"); return P(4 === n.rank, function () { return "Error in reverse4D: x must be rank 4 but got rank " + n.rank + "." }), Pc(n, e) } }); function Uc(t, r, o, i, a, e) { var n = cn(t, "x", "maxPool"), s = n, u = !1; 3 === n.rank && (u = !0, s = n.as4D(1, n.shape[0], n.shape[1], n.shape[2])), null == i && (i = [1, 1]), P(4 === s.rank, function () { return "Error in maxPool: input must be rank 4 but got rank " + s.rank + "." }), P(So(o, i), function () { return "Error in maxPool: Either strides or dilations must be 1. Got strides " + o + " and dilations '" + i + "'" }), null != e && P(B(a), function () { return "Error in maxPool: pad must be an integer when using, dimRoundingMode " + e + " but got pad " + a + "." }); var c = yo(s.shape, r, o, i, a, e); if (1 === c.filterWidth && 1 === c.filterHeight && A(c.inShape, c.outShape)) return n.clone(); var l = [s], h = Kt.runKernelFunc(function (t, e) { var n = t.maxPool(s, c); return e([s, n]), n }, { x: s }, function (h, t) { var e = t[0], n = t[1]; return { x: function () { return function (t, e, n, r, o, i, a) { var s = cn(h, "dy", "maxPoolBackprop"), u = cn(e, "input", "maxPoolBackprop"), c = cn(n, "output", "maxPoolBackprop"); P(u.rank === s.rank, function () { return "Rank of input (" + u.rank + ") does not match rank of dy (" + s.rank + ")" }), null == i && (i = [1, 1]), P(So(o, i), function () { return "Error in maxPoolBackProp: Either strides or dilations must be 1. Got strides " + o + " and dilations '" + i + "'" }), P(4 === s.rank, function () { return "Error in maxPoolBackprop: dy must be rank 4 but got rank " + s.rank + "." }), P(4 === u.rank, function () { return "Error in maxPoolBackprop: input must be rank 4 but got rank " + u.rank + "." }); var l = yo(u.shape, r, o, i, a, void 0); return Kt.runKernelFunc(function (t) { return t.maxPoolBackprop(s, u, c, l) }, { $dy: s, $input: u }) }(0, e, n, r, o, i, a) } } }, "MaxPool", c, l); return u ? h.as3D(h.shape[1], h.shape[2], h.shape[3]) : h } function Vc(t, e, n, r, o, i) { var a = cn(t, "x", "avgPool", "float32"); null == r && (r = [1, 1]), P(So(n, r), function () { return "Error in avgPool: Either strides or dilations must be 1. Got strides " + n + " and dilations '" + r + "'" }); var s = a, u = !1; 3 === a.rank && (u = !0, s = a.as4D(1, a.shape[0], a.shape[1], a.shape[2])), P(4 === s.rank, function () { return "Error in avgPool: x must be rank 4 but got rank " + s.rank + "." }), null != i && P(B(o), function () { return "Error in avgPool: pad must be an integer when using, dimRoundingMode " + i + " but got pad " + o + "." }); var c = yo(s.shape, e, n, r, o, i); if (1 === c.filterWidth && 1 === c.filterHeight && A(c.inShape, c.outShape)) return a.clone(); var l = Kt.runKernelFunc(function (t) { return t.avgPool(s, c) }, { x: s }, function (p) { return { x: function () { return function (t, e, n, r, o, i) { var a = cn(p, "dy", "avgPoolBackprop"), s = cn(e, "input", "avgPoolBackprop"); P(s.rank === a.rank, function () { return "Rank of input (" + s.rank + ") does not match rank of dy (" + a.rank + ")" }), null == o && (o = [1, 1]), P(So(r, o), function () { return "Error in avgPoolBackprop: Either strides or dilations must be 1. Got strides " + r + " and dilations '" + o + "'" }); var u = s, c = a, l = !1; 3 === s.rank && (l = !0, u = s.as4D(1, s.shape[0], s.shape[1], s.shape[2]), c = a.as4D(1, a.shape[0], a.shape[1], a.shape[2])), P(4 === c.rank, function () { return "Error in avgPoolBackprop: dy must be rank 4 but got rank " + c.rank + "." }), P(4 === u.rank, function () { return "Error in avgPoolBackprop: input must be rank 4 but got rank " + u.rank + "." }); var h = yo(u.shape, n, r, o, i), f = Kt.runKernelFunc(function (t) { return t.avgPoolBackprop(c, u, h) }, { dy4D: c, input4D: u }); return l ? f.as3D(f.shape[1], f.shape[2], f.shape[3]) : f }(0, s, e, n, r, o) } } }, "AvgPool", c); return l = l.cast(a.dtype), u ? l.as3D(l.shape[1], l.shape[2], l.shape[3]) : l } var Gc = wn({ maxPool_: function (t, e, n, r, o) { return Uc(t, e, n, 1, r, o) } }), Hc = wn({ avgPool_: function (t, e, n, r, o) { return Vc(t, e, n, 1, r, o) } }), qc = wn({ pool_: function (t, e, n, r, o, i) { null == o && (o = [1, 1]), null == i && (i = 1), 0 === r && (r = "valid"); var a = cn(t, "x", "maxPool"), s = a, u = !1; 3 === a.rank && (u = !0, s = a.as4D(1, a.shape[0], a.shape[1], a.shape[2])), P(So(i, o), function () { return "Error in pool: Either strides or dilations must be 1. Got strides " + i + " and dilations '" + o + "'" }); var c, l, h, f, p, d, v = yo(s.shape, e, i, o, r), m = [v.dilationHeight, v.dilationWidth]; c = "same" === r ? (l = [v.filterHeight, v.filterWidth], h = m, f = l.map(function (t, e) { return t + (t - 1) * (h[e] - 1) }).map(function (t) { return t - 1 }), p = f.map(function (t) { return Math.floor(t / 2) }), d = f.map(function (t, e) { return t - p[e] }), f.map(function (t, e) { return [p[e], d[e]] })) : [[0, 0], [0, 0]]; var g, y, x, b, w, C, E, _, I = 1 === m[0] && 1 === m[1], R = (g = [v.inHeight, v.inWidth], y = m, b = (x = c).map(function (t) { return t[0] }), w = x.map(function (t) { return t[1] }), C = g.concat(b, w), E = y.map(function (t, e) { return (t - C[e] % t) % t }), _ = w.map(function (t, e) { return t + E[e] }), [y.map(function (t, e) { return [b[e], _[e]] }), y.map(function (t, e) { return [0, E[e]] })]), k = R[1], S = I ? r : "valid", D = I ? s : Nr(s, m, R[0]), A = ("avg" === n ? function () { return Vc(D, e, i, 1, S) } : function () { return Uc(D, e, i, 1, S) })(), T = I ? A : fr(A, m, k); return u ? T.as3D(T.shape[1], T.shape[2], T.shape[3]) : T } }), jc = wn({ maxPool3d_: function (t, r, o, i, a, e, s) { void 0 === e && (e = "NDHWC"); var n = cn(t, "x", "maxPool3d"), u = n, c = !1; 4 === n.rank && (c = !0, u = n.as5D(1, n.shape[0], n.shape[1], n.shape[2], n.shape[3])), null == s && (s = [1, 1, 1]), P(5 === u.rank, function () { return "Error in maxPool3d: x must be rank 5 but got rank " + u.rank + "." }), P("NDHWC" === e, function () { return "Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of " + e }), P(So(o, s), function () { return "Error in maxPool3d: Either strides or dilations must be 1. Got strides " + o + " and dilations '" + s + "'" }), null != a && P(B(i), function () { return "Error in maxPool3d: pad must be an integer when using, dimRoundingMode " + a + " but got pad " + i + "." }); var l = xo(u.shape, r, o, s, i, a, e), h = Kt.runKernelFunc(function (t, e) { var n = t.maxPool3d(u, l); return e([u, n]), n }, { x: u }, function (g, t) { var e = t[0], n = t[1]; return { x: function () { return function (t, e, n, r, o, i, a, s) { var u = cn(g, "dy", "maxPool3dBackprop"), c = cn(e, "input", "maxPool3dBackprop"), l = cn(n, "output", "maxPool3dBackprop"), h = u, f = c, p = l, d = !1; 4 === c.rank && (d = !0, h = u.as5D(1, u.shape[0], u.shape[1], u.shape[2], u.shape[3]), f = c.as5D(1, c.shape[0], c.shape[1], c.shape[2], c.shape[3]), p = l.as5D(1, l.shape[0], l.shape[1], l.shape[2], l.shape[3])), P(5 === h.rank, function () { return "Error in maxPool3dBackprop: dy must be rank 5 but got rank " + h.rank + "." }), P(5 === f.rank, function () { return "Error in maxPool3dBackprop: input must be rank 5 but got rank " + f.rank + "." }), P(5 === p.rank, function () { return "Error in maxPool3dBackprop: output must be rank 5 but got rank " + p.rank + "." }), null == i && (i = [1, 1, 1]), P(So(o, i), function () { return "Error in maxPool3dBackprop: Either strides or dilations must be 1. Got strides " + o + " and dilations '" + i + "'" }), null != s && P(B(a), function () { return "Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode " + s + " but got pad " + a + "." }); var v = xo(f.shape, r, o, i, a, s), m = Kt.runKernelFunc(function (t) { return t.maxPool3dBackprop(h, f, p, v) }, { dy5D: h, input5D: f }); return d ? m.as4D(m.shape[1], m.shape[2], m.shape[3], m.shape[4]) : m }(0, e, n, r, o, s, i, a) } } }); return c ? h.as4D(h.shape[1], h.shape[2], h.shape[3], h.shape[4]) : h } }), Kc = wn({ avgPool3d_: function (t, e, n, r, o, i, a) { void 0 === i && (i = "NDHWC"); var s = cn(t, "x", "avgPool3d", "float32"), u = s, c = !1; 4 === s.rank && (c = !0, u = s.as5D(1, s.shape[0], s.shape[1], s.shape[2], s.shape[3])), null == a && (a = [1, 1, 1]), P(5 === u.rank, function () { return "Error in avgPool3d: x must be rank 5 but got rank " + u.rank + "." }), P("NDHWC" === i, function () { return "Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of " + i }), P(So(n, a), function () { return "Error in avgPool3d: Either strides or dilations must be 1. Got strides " + n + " and dilations '" + a + "'" }), null != o && P(B(r), function () { return "Error in avgPool3d: pad must be an integer when using, dimRoundingMode " + o + " but got pad " + r + "." }); var l = xo(u.shape, e, n, a, r, o, i), h = Kt.runKernelFunc(function (t) { return t.avgPool3d(u, l) }, { x: u }, function (d) { return { x: function () { return function (t, e, n, r, o, i, a) { var s = cn(d, "dy", "avgPool3dBackprop"), u = cn(e, "input", "avgPool3dBackprop"), c = s, l = u, h = !1; 4 === u.rank && (h = !0, c = s.as5D(1, s.shape[0], s.shape[1], s.shape[2], s.shape[3]), l = u.as5D(1, u.shape[0], u.shape[1], u.shape[2], u.shape[3])), P(5 === c.rank, function () { return "Error in avgPool3dBackprop: dy must be rank 5 but got rank " + c.rank + "." }), P(5 === l.rank, function () { return "Error in avgPool3dBackprop: input must be rank 5 but got rank " + l.rank + "." }), null == o && (o = [1, 1, 1]), P(So(r, o), function () { return "Error in avgPool3dBackprop: Either strides or dilations must be 1. Got strides " + r + " and dilations '" + o + "'" }), null != a && P(B(i), function () { return "Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode " + a + " but got pad " + i + "." }); var f = xo(l.shape, n, r, o, i, a), p = Kt.runKernelFunc(function (t) { return t.avgPool3dBackprop(c, l, f) }, { dy5D: c, input5D: l }); return h ? p.as4D(p.shape[1], p.shape[2], p.shape[3], p.shape[4]) : p }(0, u, e, n, a, r, o) } } }); return h = h.cast(u.dtype), c ? h.as4D(h.shape[1], h.shape[2], h.shape[3], h.shape[4]) : h } }), Xc = wn({ slice_: function (t, e, n) { var r, o, i = cn(t, "x", "slice"); if (0 === i.rank) throw new Error("Slicing scalar is not possible"); (r = "number" == typeof e ? [e].concat(new Array(i.rank - 1).fill(0)) : e.length < i.rank ? e.concat(new Array(i.rank - e.length).fill(0)) : e.slice()).forEach(function (t) { P(-1 !== t, function () { return "slice() does not support negative begin indexing." }) }), o = (o = null == n ? new Array(i.rank).fill(-1) : "number" == typeof n ? [n].concat(new Array(i.rank - 1).fill(-1)) : n.length < i.rank ? n.concat(new Array(i.rank - n.length).fill(-1)) : n).map(function (t, e) { return 0 <= t ? t : (P(-1 === t, function () { return "Negative size values should be exactly -1 but got " + t + " for the slice() size at index " + e + "." }), i.shape[e] - r[e]) }), $r(i, r, o); var a = i.shape, s = { begin: r, size: o }; return Kt.runKernelFunc(function (t) { return t.slice(i, r, o) }, { x: i }, function (t) { for (var e = [], n = 0; n < t.rank; n++)e.push([r[n], a[n] - r[n] - o[n]]); return { x: function () { return t.pad(e) } } }, "Slice", s) } }), Yc = wn({ slice1d_: function (t, e, n) { var r = cn(t, "x", "slice1d"); return P(1 === r.rank, function () { return "slice1d expects a rank-1 tensor, but got a rank-" + r.rank + " tensor" }), Xc(r, [e], [n]) } }), $c = wn({ slice2d_: function (t, e, n) { var r = cn(t, "x", "slice2d"); return P(2 === r.rank, function () { return "slice2d expects a rank-2 tensor, but got a rank-" + r.rank + " tensor" }), Xc(r, e, n) } }), Jc = wn({ slice3d_: function (t, e, n) { var r = cn(t, "x", "slice3d"); return P(3 === r.rank, function () { return "slice3d expects a rank-3 tensor, but got a rank-" + r.rank + " tensor" }), Xc(r, e, n) } }), Qc = wn({ slice4d_: function (t, e, n) { var r = cn(t, "x", "slice4d"); return P(4 === r.rank, function () { return "slice4d expects a rank-4 tensor, but got a rank-" + r.rank + " tensor" }), Xc(r, e, n) } }); function Zc(e, n, r, t, o) { return n.rank < r.rank && (n = n.reshape(dn(n.shape, t))), e.rank < r.rank && (e = e.reshape(dn(e.shape, t))), { x: function () { var t = e.mul(r.equal(n).cast(e.dtype)); return null == o ? t : t.transpose(o) } } } var tl = wn({ all_: function (t, e, n) { void 0 === e && (e = null), void 0 === n && (n = !1); var r = cn(t, "x", "all", "bool"), o = D(e, r.shape), i = o, a = mn(i, r.rank); null != a && (r = r.transpose(a), i = yn(i.length, r.rank)); var s = Kt.runKernelFunc(function (t) { return t.all(r, i) }, { $x: r }); if (n) { var u = dn(s.shape, o); return s.reshape(u) } return s } }), el = wn({ any_: function (t, e, n) { void 0 === e && (e = null), void 0 === n && (n = !1); var r = cn(t, "x", "any", "bool"), o = D(e, r.shape), i = o, a = mn(i, r.rank); null != a && (r = r.transpose(a), i = yn(i.length, r.rank)); var s = Kt.runKernelFunc(function (t) { return t.any(r, i) }, { $x: r }); if (n) { var u = dn(s.shape, o); return s.reshape(u) } return s } }), nl = wn({ argMax_: function (t, e) { void 0 === e && (e = 0); var r = cn(t, "x", "argMax"); null == e && (e = 0); var o = D(e, r.shape), n = mn(o, r.rank); null != n && (r = r.transpose(n), o = yn(o.length, r.rank)); var i = { axis: o[0] }, a = [r]; return Kt.runKernelFunc(function (t, e) { var n = t.argMax(r, o[0]); return e([r]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return Un(n) } } }, "ArgMax", i, a) } }), rl = wn({ argMin_: function (t, e) { void 0 === e && (e = 0); var r = cn(t, "x", "argMin"); null == e && (e = 0); var o = D(e, r.shape), n = mn(o, r.rank); return null != n && (r = r.transpose(n), o = yn(o.length, r.rank)), Kt.runKernelFunc(function (t, e) { var n = t.argMin(r, o[0]); return e([r]), n }, { $x: r }, function (t, e) { var n = e[0]; return { $x: function () { return Un(n) } } }) } }), ol = wn({ logSumExp_: function (t, e, n) { void 0 === e && (e = null), void 0 === n && (n = !1); var r = cn(t, "x", "logSumExp"), o = D(e, r.shape), i = r.max(o, !0), a = r.sub(i).exp().sum(o).log(), s = i.reshape(a.shape).add(a); if (n) { var u = dn(s.shape, o); return s.reshape(u) } return s } }), il = wn({ max_: function (t, e, n) { void 0 === e && (e = null), void 0 === n && (n = !1); var r = cn(t, "x", "max"), o = r, i = D(e, r.shape), a = i, s = mn(a, r.rank); null != s && (r = r.transpose(s), a = yn(a.length, r.rank)); var u = [r], c = Kt.runKernelFunc(function (t, e) { var n = t.max(r, a); return e([o, n]), n }, { x: r }, function (t, e) { return Zc(t, e[1], e[0], i, s) }, "Max", { axes: a }, u, [!0]); if (n) { var l = dn(c.shape, i); c = c.reshape(l) } return c } }), al = wn({ mean_: function (t, e, r) { void 0 === e && (e = null), void 0 === r && (r = !1); var n = cn(t, "x", "mean"), o = D(e, n.shape), i = L(pn(n.shape, o)[1]); return io(function (n) { var t = kn(i); return { value: (t.dtype === n.dtype ? n : n.cast(t.dtype)).div(t).sum(e, r), gradFunc: function (t) { var e = n.shape.slice(); return o.forEach(function (t) { e[t] = 1 }), t.reshape(e).mul(On(n.shape, "float32")).div(i) } } })(n) } }), sl = wn({ min_: function (t, e, n) { void 0 === e && (e = null), void 0 === n && (n = !1); var r = cn(t, "x", "min"), o = r, i = D(e, r.shape), a = i, s = mn(a, r.rank); null != s && (r = r.transpose(s), a = yn(a.length, r.rank)); var u = [r], c = Kt.runKernelFunc(function (t, e) { var n = t.min(r, a); return e([o, n]), n }, { x: r }, function (t, e) { return Zc(t, e[1], e[0], i, s) }, "Min", { axes: a }, u, [!0]); if (n) { var l = dn(c.shape, i); c = c.reshape(l) } return c } }), ul = wn({ moments_: function (t, e, n) { void 0 === e && (e = null), void 0 === n && (n = !1); var r = D(e, (t = cn(t, "x", "moments")).shape), o = t.mean(r, n), i = o.shape; n || (i = dn(o.shape, r)); var a = t.toFloat().sub(o.reshape(i)).square(); return { mean: o, variance: a.mean(r, n) } } }), cl = wn({ sum_: function (t, e, u) { void 0 === e && (e = null), void 0 === u && (u = !1); var n = cn(t, "x", "sum"); "bool" === n.dtype && (n = n.toInt()); var c = D(e, n.shape); return io(function (n) { var t = mn(c, n.rank), e = c, r = n; null != t && (r = n.transpose(t), e = yn(e.length, n.rank)); function o(t) { var e = n.shape.slice(); return c.forEach(function (t) { e[t] = 1 }), t.reshape(e).mul(On(n.shape, "float32")) } var i = { axes: e }, a = Kt.runKernelFunc(function (t) { return t.sum(r, e) }, { x: r }, function (t) { return { x: function () { return o(t) } } }, "Sum", i); if (u) { var s = dn(a.shape, c); a = a.reshape(s) } return { value: a, gradFunc: o } })(n) } }), ll = wn({ prod_: function (t, e, n) { void 0 === e && (e = null), void 0 === n && (n = !1); var r = cn(t, "x", "prod"); "bool" === r.dtype && (r = r.toInt()); var o = D(e, r.shape), i = mn(o, r.rank), a = o, s = r; null != i && (s = r.transpose(i), a = yn(a.length, r.rank)); var u = Kt.runKernelFunc(function (t) { return t.prod(s, a) }, { permutedX: s }); if (n) { var c = dn(u.shape, o); u = u.reshape(c) } return u } }), hl = wn({ elu_: function (t) { var r = cn(t, "x", "elu"); return Kt.runKernelFunc(function (t, e) { var n = t.elu(r); return e([n]), n }, { $x: r }, function (e, t) { var n = t[0]; return { $x: function () { return Kt.runKernelFunc(function (t) { return t.eluDer(e, n) }, { dy: e, y: n }) } } }) } }), fl = wn({ leakyRelu_: function (t, e) { void 0 === e && (e = .2); var n = cn(t, "x", "leakyRelu"); return Gu(kn(e).mul(n), n) } }), pl = wn({ prelu_: function (t, e) { var r = cn(t, "x", "prelu"), o = cn(e, "alpha", "prelu"); return Kt.runKernelFunc(function (t, e) { var n = t.prelu(r, o); return e([r, o]), n }, { x: r, alpha: o }, function (n, t) { var r = t[0], o = t[1], i = r.greater(0); return { x: function () { return Mu(i, n, n.mul(o)) }, alpha: function () { var t = Mu(i, Un(n), n.mul(r)), e = mo(o.shape, n.shape); return 0 < e.length && (t = t.sum(e)), t.reshape(o.shape) } } }, "Prelu") } }), dl = wn({ relu_: function (t) { var r = cn(t, "x", "relu"); return "bool" === r.dtype ? r.toInt() : Kt.runKernelFunc(function (t, e) { var n = t.relu(r); return e([r]), n }, { x: r }, function (t, e) { var n = e[0]; return { x: function () { return t.mulStrict(n.step().toFloat()) } } }, "Relu") } }), vl = wn({ relu6_: function (t) { var r = cn(t, "x", "relu6"); return "bool" === r.dtype ? r.toInt() : Kt.runKernelFunc(function (t, e) { var n = t.relu6(r); return e([r]), n }, { x: r }, function (t, e) { var n = e[0], r = n.lessEqual(6).mul(n.step()); return { x: function () { return t.mulStrict(r.toFloat()) } } }, "Relu6") } }), ml = wn({ selu_: function (t) { var r = cn(t, "x", "selu"); return Kt.runKernelFunc(function (t, e) { var n = t.selu(r); return e([r]), n }, { $x: r }, function (i, t) { var a = t[0]; return { $x: function () { var t = a.greater(kn(0)), e = kn(hs), n = kn(fs), r = i.mul(n), o = i.mul(e).mul(a.toFloat().exp()); return Mu(t, r, o) } } }) } }), gl = wn({ transpose_: function (t, n) { var e = cn(t, "x", "transpose"); if (null == n && (n = e.shape.map(function (t, e) { return e }).reverse()), P(e.rank === n.length, function () { return "Error in transpose: rank of input " + e.rank + " must match length of perm " + n + "." }), n.forEach(function (t) { P(0 <= t && t < e.rank, function () { return "All entries in 'perm' must be between 0 and " + (e.rank - 1) + " but got " + n }) }), e.rank <= 1) return e.clone(); var r = { perm: n }; return Kt.runKernelFunc(function (t) { return t.transpose(e, n) }, { x: e }, function (t) { var e = gn(n); return { x: function () { return t.transpose(e) } } }, "Transpose", r) } }), yl = wn({ localResponseNormalization_: function (t, o, i, a, s) { void 0 === o && (o = 5), void 0 === i && (i = 1), void 0 === a && (a = 1), void 0 === s && (s = .5); var e = cn(t, "x", "localResponseNormalization"); P(4 === e.rank || 3 === e.rank, function () { return "Error in localResponseNormalization: x must be rank 3 or 4 but got\n               rank " + e.rank + "." }), P(B(o), function () { return "Error in localResponseNormalization: depthRadius must be an integer but got depthRadius " + o + "." }); var r = e, n = !1; 3 === e.rank && (n = !0, r = e.as4D(1, e.shape[0], e.shape[1], e.shape[2])); var u = Kt.runKernelFunc(function (t, e) { var n = t.localResponseNormalization4D(r, o, i, a, s); return e([r, n]), n }, { x4D: r }, function (e, t) { var n = t[0], r = t[1]; return { x4D: function () { return Kt.runKernelFunc(function (t) { return t.LRNGrad(e, n, r, o, i, a, s) }, {}) } } }); return n ? u.as3D(u.shape[1], u.shape[2], u.shape[3]) : u } }), xl = wn({ norm_: function (t, e, n, r) { void 0 === e && (e = "euclidean"), void 0 === n && (n = null), void 0 === r && (r = !1); var o = function t(e, n, r) { if (void 0 === r && (r = null), 0 === e.rank) return e.abs(); if (1 !== e.rank && null === r) return t(e.reshape([-1]), n, r); if (1 === e.rank || "number" == typeof r || Array.isArray(r) && 1 === r.length) { if (1 === n) return e.abs().sum(r); if (n === 1 / 0) return e.abs().max(r); if (n === -1 / 0) return e.abs().min(r); if ("euclidean" === n || 2 === n) return e.abs().pow(kn(2, "int32")).sum(r).sqrt(); throw new Error("Error in norm: invalid ord value: " + n) } if (Array.isArray(r) && 2 === r.length) { if (1 === n) return e.abs().sum(r[0]).max(r[1] - 1); if (n === 1 / 0) return e.abs().sum(r[1]).max(r[0]); if (n === -1 / 0) return e.abs().sum(r[1]).min(r[0]); if ("fro" === n || "euclidean" === n) return e.square().sum(r).sqrt(); throw new Error("Error in norm: invalid ord value: " + n) } throw new Error("Error in norm: invalid axis: " + r) }(t = cn(t, "x", "norm"), e, n), i = o.shape; if (r) { var a = D(n, t.shape); i = dn(o.shape, a) } return o.reshape(i) } }), bl = wn({ basicLSTMCell_: function (t, e, n, r, o, i) { var a = cn(t, "forgetBias", "basicLSTMCell"), s = cn(e, "lstmKernel", "basicLSTMCell"), u = cn(n, "lstmBias", "basicLSTMCell"), c = cn(r, "data", "basicLSTMCell"), l = cn(o, "c", "basicLSTMCell"), h = cn(i, "h", "basicLSTMCell"), f = c.concat(h, 1).matMul(s).add(u), p = f.shape[0], d = f.shape[1] / 4, v = [p, d], m = f.slice([0, 0], v), g = f.slice([0, d], v), y = f.slice([0, 2 * d], v), x = f.slice([0, 3 * d], v), b = m.sigmoid().mulStrict(g.tanh()).addStrict(l.mulStrict(a.add(y).sigmoid())), w = b.tanh().mulStrict(x.sigmoid()); return [b, w] } }), wl = wn({ multiRNNCell_: function (t, e, n, r) { for (var o = cn(e, "data", "multiRNNCell"), i = ln(n, "c", "multiRNNCell"), a = ln(r, "h", "multiRNNCell"), s = o, u = [], c = 0; c < t.length; c++) { var l = t[c](s, i[c], a[c]); u.push(l[0]), u.push(l[1]), s = l[1] } var h = [], f = []; for (c = 0; c < u.length; c += 2)h.push(u[c]), f.push(u[c + 1]); return [h, f] } }), Cl = wn({ movingAverage_: function (t, e, n, r, o) { void 0 === o && (o = !0); var i = cn(t, "v", "movingAverage"), a = cn(e, "x", "movingAverage"), s = cn(n, "decay", "movingAverage"); Wt(i, a), P(A(i.shape, a.shape), function () { return "Shape mismatch in v and x" }); var u = kn(1), c = u.sub(s), l = a.sub(i).mul(c); if (o) { P(null != r, function () { return "When using zeroDebias: true, step is required." }); var h = cn(r, "step", "movingAverage"); l = l.div(u.sub(Ju(s, h))) } return i.add(l) } }), El = wn({ stridedSlice_: function (t, e, n, r, o, i, a, s, u) { if (void 0 === o && (o = 0), void 0 === i && (i = 0), void 0 === a && (a = 0), void 0 === s && (s = 0), void 0 === u && (u = 0), null == r && (r = new Array(e.length)), 0 !== a) throw new Error("ellipsis mask is not yet supported"); var c = cn(t, "x", "stridedSlice"), l = Jr(s), h = c.shape.slice(); l.forEach(function (t) { e[t] = 0, n[t] = 1, h.splice(t, 0, 1) }), c = c.reshape(h); for (var f = 0; f < c.rank; f++)e[f] = Zr(o, e, r, c.shape, f), n[f] = to(i, n, r, c.shape, f), r[f] = r[f] || 1; var p = Jr(u); p.forEach(function (t) { n[t] = e[t] + 1, r[t] = 1 }); var d = Qr(e, n, r), v = d.filter(function (t, e) { return -1 === p.indexOf(e) }); return r.every(function (t) { return 1 === t }) ? Xc(c, e, d).reshape(v) : Kt.runKernelFunc(function (t) { return t.stridedSlice(c, e, n, r) }, { $x: c }).reshape(v) } }), _l = wn({ topk_: function (t, e, n) { void 0 === e && (e = 1), void 0 === n && (n = !0); var r = cn(t, "x", "topk"); if (0 === r.rank) throw new Error("topk() expects the input to be of rank 1 or higher"); var o = r.shape[r.shape.length - 1]; if (o < e) throw new Error("'k' passed to topk() must be <= the last dimension (" + o + ") but got " + e); var i = Kt.runKernelFunc(function (t) { return t.topk(r, e, n) }, { $x: r }); return { values: i[0], indices: i[1] } } }), Il = wn({ scatterND_: function (t, e, n) { var r = cn(t, "indices", "scatterND", "int32"), o = cn(e, "updates", "scatterND"); return Kr(o, r, n), Kt.runKernelFunc(function (t) { return t.scatterND(r, o, n) }, { indices: r, updates: o }, null, "ScatterNd", { shape: n }) } }), Rl = wn({ fft_: function (t) { P("complex64" === t.dtype, function () { return "The dtype for tf.spectral.fft() must be complex64 but got " + t.dtype + "." }); var e = t.shape[t.shape.length - 1], n = t.size / e, r = t.as2D(n, e); return Kt.runKernelFunc(function (t) { return t.fft(r) }, { input: t }).reshape(t.shape) } }), kl = wn({ ifft_: function (t) { P("complex64" === t.dtype, function () { return "The dtype for tf.spectral.ifft() must be complex64 but got " + t.dtype + "." }); var e = t.shape[t.shape.length - 1], n = t.size / e, r = t.as2D(n, e); return Kt.runKernelFunc(function (t) { return t.ifft(r) }, { input: t }).reshape(t.shape) } }), Sl = wn({ rfft_: function (t, e) { P("float32" === t.dtype, function () { return "The dtype for rfft() must be real value but got " + t.dtype }); var n, r = t.shape[t.shape.length - 1], o = t.size / r; if (null != e && e < r) { var i = t.shape.map(function (t) { return 0 }), a = t.shape.map(function (t) { return t }); a[t.shape.length - 1] = e, n = t.slice(i, a), r = e } else if (null != e && r < e) { var s = t.shape.map(function (t) { return t }); s[t.shape.length - 1] = e - r, n = t.concat(Pn(s), t.shape.length - 1), r = e } else n = t; var u = n.zerosLike(), c = Cn(n, u).as2D(o, r), l = Rl(c), h = Math.floor(r / 2) + 1, f = En(l), p = _n(l), d = f.split([h, r - h], f.shape.length - 1), v = p.split([h, r - h], p.shape.length - 1), m = n.shape.slice(); return m[n.shape.length - 1] = h, Cn(d[0], v[0]).reshape(m) } }), Dl = wn({ irfft_: function (t) { var e = t.shape[t.shape.length - 1], n = t.size / e; if (e <= 2) { var r = t.as2D(n, e), o = kl(r); return En(o) } var i = [n, 2 * (e - 1)], a = En(t).as2D(n, e), s = _n(t).as2D(n, e), u = a.slice([0, 1], [n, e - 2]).reverse(1), c = s.slice([0, 1], [n, e - 2]).reverse(1).mul(kn(-1)), l = a.concat(u, 1), h = s.concat(c, 1); return r = Cn(l, h).as2D(i[0], i[1]), o = kl(r), En(o) } }), Al = Object.freeze({ fft: Rl, ifft: kl, rfft: Sl, irfft: Dl }), Tl = wn({ sparseToDense_: function (t, e, n, r) { void 0 === r && (r = 0); var o = cn(t, "sparseIndices", "sparseToDense", "int32"), i = cn(e, "sparseValues", "sparseToDense"), a = cn(r, "defaultValue", "sparseToDense", i.dtype); return function (t, e, n, r) { if ("int32" !== t.dtype) throw new Error("tf.sparseToDense() expects the indices to be int32 type, but the dtype was " + t.dtype + "."); if (2 < t.rank) throw new Error("sparseIndices should be a scalar, vector, or matrix, but got shape " + t.shape + "."); var o = 0 < t.rank ? t.shape[0] : 1, i = 1 < t.rank ? t.shape[1] : 1; if (n.length !== i) throw new Error("outputShape has incorrect number of elements:, " + n.length + ", should be: " + i + "."); var a = e.size; if (0 !== e.rank && (1 !== e.rank || a !== o)) throw new Error("sparseValues has incorrect shape " + e.shape + ", should be [] or [" + o + "]"); if (e.dtype !== r.dtype) throw new Error("sparseValues.dtype must match defaultValues.dtype") }(o, i, n, a), Kt.runKernelFunc(function (t) { return t.sparseToDense(o, i, n, a) }, { $sparseIndices: o, $sparseValues: i, $defaultValue: a }) } }), Nl = wn({ gatherND_: function (t, e) { var n = cn(e, "indices", "gatherND", "int32"), r = cn(t, "x", "gatherND"); return Kt.runKernelFunc(function (t) { return t.gatherND(r, n) }, { x: r, indices: n }, null, "GatherNd") } }), Fl = wn({ diag_: function (t) { var e = cn(t, "x", "diag").flatten(), n = t.shape.concat(t.shape); return Kt.runKernelFunc(function (t) { return t.diag(e) }, { $x: e }).reshape(n) } }), Ml = wn({ dropout_: function (t, e, n, r) { var o = cn(t, "x", "dropout"); if (P("float32" === o.dtype, function () { return "x has to be a floating point tensor since it's going to be scaled, but got a " + o.dtype + " tensor instead." }), P(0 <= e && e < 1, function () { return "rate must be a float in the range [0, 1), but got " + e + "." }), 0 === e) return t instanceof bt ? o.clone() : o; var i = function (t, e) { if (null == e) return t.shape.slice(); if (A(t.shape, e)) return e; if (t.shape.length !== e.length) return e; for (var n = [], r = 0; r < t.shape.length; r++)null == e[r] && null != t.shape[r] ? n.push(t.shape[r]) : n.push(e[r]); return n }(o, n), a = 1 - e, s = Ar(i, 0, 1, "float32", r).add(a).floor().div(a); return o.mul(s) } }); function Ol(t, e, n) { for (var r = 1 - t % 2, o = new Float32Array(t), i = 0; i < t; ++i) { var a = 2 * Math.PI * i / (t + r - 1); o[i] = e - n * Math.cos(a) } return Sn(o, "float32") } function Pl(v, m, g) { return void 0 === g && (g = 1), y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p, d; return R(this, function (t) { switch (t.label) { case 0: return e = cn(v, "predictions", "inTopK"), n = cn(m, "targets", "inTopK"), P(1 < e.rank, function () { return "inTopK() expects the predictions to be of rank 2 or higher, but got " + e.rank }), P(e.rank - 1 === n.rank, function () { return "predictions rank should be 1 larger than targets rank, but got predictions rank " + e.rank + " and targets rank " + n.rank }), x(e.shape.slice(0, e.shape.length - 1), n.shape, "predictions's shape should be align with the targets' shape, except the last dimension."), r = e.shape[e.shape.length - 1], P(0 < g && g <= r, function () { return "'k' passed to inTopK() must be > 0 && <= the predictions last dimension (" + r + "), but got " + g }), [4, e.data()]; case 1: return o = t.sent(), [4, n.data()]; case 2: for (i = t.sent(), a = [o.length / r, r], u = a[1], c = N("bool", s = a[0]), l = 0; l < s; l++) { for (h = l * u, f = o.subarray(h, h + u), p = [], d = 0; d < f.length; d++)p.push({ value: f[d], index: d }); for (p.sort(function (t, e) { return e.value - t.value }), c[l] = 0, d = 0; d < g; d++)if (p[d].index === i[l]) { c[l] = 1; break } } return v !== e && e.dispose(), m !== n && n.dispose(), [2, In(c, n.shape, "bool")] } }) }) } var Bl, Ll, Wl = wn({ hannWindow_: function (t) { return Ol(t, .5, .5) } }), zl = wn({ hammingWindow_: function (t) { return Ol(t, .54, .46) } }), Ul = wn({ frame_: function (t, e, n, r, o) { void 0 === r && (r = !1), void 0 === o && (o = 0); for (var i = 0, a = []; i + e <= t.size;)a.push(Xc(t, i, e)), i += n; if (r) for (; i < t.size;) { var s = i + e - t.size, u = Vn([Xc(t, i, e - s), Bn([s], o)]); a.push(u), i += n } return 0 === a.length ? Dn([], [0, e]) : Vn(a).as2D(a.length, e) } }), Vl = wn({ stft_: function (t, e, n, r, o) { var i; void 0 === o && (o = Wl), null == r && (i = e, r = Math.floor(Math.pow(2, Math.ceil(Math.log(i) / Math.log(2))))); for (var a = Ul(t, e, n), s = Yu(a, o(e)), u = [], c = 0; c < a.shape[0]; c++)u.push(Sl(s.slice([c, 0], [1, e]), r)); return Vn(u) } }), Gl = Object.freeze({ hannWindow: Wl, hammingWindow: zl, frame: Ul, stft: Vl }); (Ll = Bl = Bl || {})[Ll.NONE = 0] = "NONE", Ll[Ll.MEAN = 1] = "MEAN", Ll[Ll.SUM = 2] = "SUM", Ll[Ll.SUM_BY_NONZERO_WEIGHTS = 3] = "SUM_BY_NONZERO_WEIGHTS"; var Hl = wn({ absoluteDifference_: function (t, e, n, r) { void 0 === r && (r = Bl.SUM_BY_NONZERO_WEIGHTS); var o = cn(t, "labels", "absoluteDifference"), i = cn(e, "predictions", "absoluteDifference"), a = null; null != n && (a = cn(n, "weights", "absoluteDifference")), x(o.shape, i.shape, "Error in absoluteDifference: "); var s = o.sub(i).abs(); return ql(s, a, r) } }), ql = wn({ computeWeightedLoss_: function (t, e, n) { void 0 === n && (n = Bl.SUM_BY_NONZERO_WEIGHTS); var r = cn(t, "losses", "computeWeightedLoss"), o = null; null != e && (o = cn(e, "weights", "computeWeightedLoss")); var i = null == o ? r : r.mul(o); if (n === Bl.NONE) return i; if (n === Bl.SUM) return i.sum(); if (n === Bl.MEAN) { if (null == o) return i.mean(); var a = r.size / o.size, s = i.sum().div(o.sum()); return 1 < a ? s.div(kn(a)) : s } if (n !== Bl.SUM_BY_NONZERO_WEIGHTS) throw Error("Unknown reduction: " + n); if (null == o) return i.sum().div(kn(r.size)); var u = o.mul(On(r.shape)).notEqual(kn(0)).sum().toFloat(); return i.sum().div(u) } }), jl = wn({ cosineDistance_: function (t, e, n, r, o) { void 0 === o && (o = Bl.SUM_BY_NONZERO_WEIGHTS); var i = cn(t, "labels", "cosineDistance"), a = cn(e, "predictions", "cosineDistance"), s = null; null != r && (s = cn(r, "weights", "cosineDistance")), x(i.shape, a.shape, "Error in cosineDistance: "); var u = kn(1).sub(i.mul(a).sum(n, !0)); return ql(u, s, o) } }), Kl = wn({ hingeLoss_: function (t, e, n, r) { void 0 === r && (r = Bl.SUM_BY_NONZERO_WEIGHTS); var o = cn(t, "labels", "hingeLoss"), i = cn(e, "predictions", "hingeLoss"), a = null; null != n && (a = cn(n, "weights", "hingeLoss")), x(o.shape, i.shape, "Error in hingeLoss: "); var s = kn(1); o = kn(2).mul(o).sub(s); var u = s.sub(o.mul(i)).relu(); return ql(u, a, r) } }), Xl = wn({ huberLoss_: function (t, e, n, r, o) { void 0 === r && (r = 1), void 0 === o && (o = Bl.SUM_BY_NONZERO_WEIGHTS); var i = cn(t, "labels", "huberLoss"), a = cn(e, "predictions", "huberLoss"), s = null; null != n && (s = cn(n, "weights", "huberLoss")), x(i.shape, a.shape, "Error in huberLoss: "); var u = kn(r), c = a.sub(i).abs(), l = qu(c, u), h = c.sub(l), f = kn(.5).mul(l.square()).add(u.mul(h)); return ql(f, s, o) } }), Yl = wn({ logLoss_: function (t, e, n, r, o) { void 0 === r && (r = 1e-7), void 0 === o && (o = Bl.SUM_BY_NONZERO_WEIGHTS); var i = cn(t, "labels", "logLoss"), a = cn(e, "predictions", "logLoss"), s = null; null != n && (s = cn(n, "weights", "logLoss")), x(i.shape, a.shape, "Error in logLoss: "); var u = kn(1), c = kn(r), l = i.mul(a.add(c).log()).neg().sub(u.sub(i).mul(u.sub(a).add(c).log())); return ql(l, s, o) } }), $l = wn({ meanSquaredError_: function (t, e, n, r) { void 0 === r && (r = Bl.SUM_BY_NONZERO_WEIGHTS); var o = cn(t, "labels", "meanSquaredError"), i = cn(e, "predictions", "meanSquaredError"), a = null; null != n && (a = cn(n, "weights", "meanSquaredError")), x(o.shape, i.shape, "Error in meanSquaredError: "); var s = o.squaredDifference(i); return ql(s, a, r) } }), Jl = wn({ sigmoidCrossEntropy_: function (t, e, n, r, o) { void 0 === r && (r = 0), void 0 === o && (o = Bl.SUM_BY_NONZERO_WEIGHTS); var s = cn(t, "multiClassLabels", "sigmoidCrossEntropy"), i = cn(e, "logits", "sigmoidCrossEntropy"), a = null; if (null != n && (a = cn(n, "weights", "sigmoidCrossEntropy")), x(s.shape, i.shape, "Error in sigmoidCrossEntropy: "), 0 < r) { var u = kn(r), c = kn(1), l = kn(.5); s = s.mul(c.sub(u)).add(l.mul(u)) } var h = function (t, e) { var n = cn(s, "labels", "sigmoidCrossEntropyWithLogits"), r = cn(e, "logits", "sigmoidCrossEntropyWithLogits"); x(n.shape, r.shape, "Error in sigmoidCrossEntropyWithLogits: "); var o = r.relu(), i = r.mul(n), a = r.abs().neg().exp().log1p(); return o.sub(i).add(a) }(0, i); return ql(h, a, o) } }), Ql = wn({ softmaxCrossEntropy_: function (t, e, n, r, o) { void 0 === r && (r = 0), void 0 === o && (o = Bl.SUM_BY_NONZERO_WEIGHTS); var i = cn(t, "onehotLabels", "softmaxCrossEntropy"), a = cn(e, "logits", "softmaxCrossEntropy"), s = null; if (null != n && (s = cn(n, "weights", "softmaxCrossEntropy")), x(i.shape, a.shape, "Error in softmaxCrossEntropy: "), 0 < r) { var u = kn(r), c = kn(1), l = kn(i.shape[1]); i = i.mul(c.sub(u)).add(u.div(l)) } var h = function (t, e, i) { if (void 0 === i && (i = -1), -1 === i && (i = e.rank - 1), i !== e.rank - 1) throw Error("Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank " + e.rank + " and dim was " + i); return io(function (t, e, n) { var r = e.logSumExp([i], !0), o = e.toFloat().sub(r); return n([t, o]), { value: o.mul(t).neg().sum([i]), gradFunc: function (t, e) { var n = e[0], r = e[1], o = dn(t.shape, [i]); return [t.reshape(o).mul(n.toFloat().sub(r.exp())), t.reshape(o).mul(r.exp().sub(n.toFloat()))] } } })(t, e) }(i, a); return ql(h, s, o) } }), Zl = Object.freeze({ get Reduction() { return Bl }, absoluteDifference: Hl, computeWeightedLoss: ql, cosineDistance: jl, hingeLoss: Kl, huberLoss: Xl, logLoss: Yl, meanSquaredError: $l, sigmoidCrossEntropy: Jl, softmaxCrossEntropy: Ql }); function th(r, o) { return void 0 === o && (o = !1), Kt.tidy(function () { if (2 !== r.shape.length) throw new Error("qr2d() requires a 2D Tensor, but got a " + r.shape.length + "D Tensor."); for (var p = r.shape[0], d = r.shape[1], v = xr(p), m = r.clone(), g = Dn([[1]], [1, 1]), y = g.clone(), t = d <= p ? d : p, e = function (f) { var t, e = m, n = y, r = v; y = (t = Kt.tidy(function () { var t = m.slice([f, f], [p - f, 1]), e = t.norm(), n = m.slice([f, f], [1, 1]), r = Dn([[-1]]).where(n.greater(0), Dn([[1]])), o = n.sub(r.mul(e)), i = t.div(o); y = 1 === i.shape[0] ? g.clone() : g.concat(i.slice([1, 0], [i.shape[0] - 1, i.shape[1]]), 0); var a = r.matMul(o).div(e).neg(), s = m.slice([f, 0], [p - f, d]), u = a.mul(y); if (0 === f) m = s.sub(u.matMul(y.transpose().matMul(s))); else { var c = s.sub(u.matMul(y.transpose().matMul(s))); m = m.slice([0, 0], [f, d]).concat(c, 0) } var l = v.slice([0, f], [p, v.shape[1] - f]); if (0 === f) v = l.sub(l.matMul(y).matMul(u.transpose())); else { var h = l.sub(l.matMul(y).matMul(u.transpose())); v = v.slice([0, 0], [p, f]).concat(h, 1) } return [y, m, v] }))[0], m = t[1], v = t[2], rn([e, n, r]) }, n = 0; n < t; ++n)e(n); return !o && d < p && (v = v.slice([0, 0], [p, d]), m = m.slice([0, 0], [d, d])), [v, m] }) } var eh = wn({ bandPart_: function (t, e, n) { if (e % 1 != 0) throw new Error("bandPart(): numLower must be an integer, got " + e + "."); if (n % 1 != 0) throw new Error("bandPart(): numUpper must be an integer, got " + n + "."); var r = cn(t, "a", "bandPart"); if (r.rank < 2) throw new Error("bandPart(): Rank must be at least 2, got " + r.rank + "."); var o = r.shape, i = r.shape.slice(-2), a = i[0], s = i[1]; if (!(e <= a)) throw new Error("bandPart(): numLower (" + e + ") must not be greater than the number of rows (" + a + ")."); if (!(n <= s)) throw new Error("bandPart(): numUpper (" + n + ") must not be greater than the number of columns (" + s + ")."); e < 0 && (e = a), n < 0 && (n = s); var u = Wn(0, a, 1, "int32").reshape([-1, 1]), c = Wn(0, s, 1, "int32"), l = tc(u, c), h = Au(l.lessEqual(kn(+e, "int32")), l.greaterEqual(kn(-n, "int32"))), f = Pn([a, s], r.dtype); return Mr(Br(r.reshape([-1, a, s])).map(function (t) { return Mu(h, t, f) })).reshape(o) } }), nh = wn({ gramSchmidt_: function (e) { var t; if (Array.isArray(e)) { t = !1, P(null != e && 0 < e.length, function () { return "Gram-Schmidt process: input must not be null, undefined, or empty" }); for (var n = e[0].shape[0], r = function (t) { P(e[t].shape[0] === n, function () { return "Gram-Schmidt: Non-unique lengths found in the input vectors: (" + e[t].shape[0] + " vs. " + n + ")" }) }, o = 1; o < e.length; ++o)r(o) } else t = !0, e = Kn(e, e.shape[0], 0).map(function (t) { return Fr(t, [0]) }); P(e.length <= e[0].shape[0], function () { return "Gram-Schmidt: Number of vectors (" + e.length + ") exceeds number of dimensions (" + e[0].shape[0] + ")." }); function i(r) { a.push(Kt.tidy(function () { var t = s[r]; if (0 < r) for (var e = 0; e < r; ++e) { var n = cl(a[e].mulStrict(t)).mul(a[e]); t = t.sub(n) } return t.div(xl(t, "euclidean")) })) } var a = [], s = e; for (o = 0; o < e.length; ++o)i(o); return t ? Mr(a, 0) : a } }), rh = wn({ qr_: function (t, o) { if (void 0 === o && (o = !1), t.rank < 2) throw new Error("qr() requires input tensor to have a rank >= 2, but got rank " + t.rank); if (2 === t.rank) return th(t, o); var e = t.shape.slice(0, t.shape.length - 2).reduce(function (t, e) { return t * e }), n = Br(t.reshape([e, t.shape[t.shape.length - 2], t.shape[t.shape.length - 1]]), 0), i = [], a = []; return n.forEach(function (t) { var e = th(t, o), n = e[0], r = e[1]; i.push(n), a.push(r) }), [Mr(i, 0).reshape(t.shape), Mr(a, 0).reshape(t.shape)] } }), oh = Object.freeze({ bandPart: eh, gramSchmidt: nh, qr: rh }); function ih(t, e, n, r, o, i) { null == r && (r = .5), null == o && (o = Number.NEGATIVE_INFINITY), null == i && (i = 0); var a = t.shape[0]; return n = Math.min(n, a), P(0 <= r && r <= 1, function () { return "iouThreshold must be in [0, 1], but was '" + r + "'" }), P(2 === t.rank, function () { return "boxes must be a 2D tensor, but was of rank '" + t.rank + "'" }), P(4 === t.shape[1], function () { return "boxes must have 4 columns, but 2nd dimension was " + t.shape[1] }), P(1 === e.rank, function () { return "scores must be a 1D tensor" }), P(e.shape[0] === a, function () { return "scores has incompatible shape with boxes. Expected " + a + ", but was " + e.shape[0] }), P(0 <= i && i <= 1, function () { return "softNmsSigma must be in [0, 1], but was '" + i + "'" }), { maxOutputSize: n, iouThreshold: r, scoreThreshold: o, softNmsSigma: i } } function ah(t, e) { return !(0 < t) || "linear" === e } function sh(t, e, n) { if (null == n || "linear" === n) return t; if ("relu" === n) return t.mul(e.step()); throw new Error("Gradient for activation " + n + " has not been implemented yet.") } function uh(t, e) { var n = e, r = mo(t.shape, e.shape); return 0 < r.length && (n = n.sum(r)), n.reshape(t.shape) } function ch(t, e, n) { if ("linear" === e) return t; if ("relu" === e) return dl(t); if ("elu" === e) return hl(t); if ("relu6" === e) return vl(t); if ("prelu" === e) return pl(t, n); throw new Error("Unknown fused activation " + e + ".") } var lh = wn({ resizeBilinear_: function (t, e, r) { void 0 === r && (r = !1); var n = cn(t, "images", "resizeBilinear"); P(3 === n.rank || 4 === n.rank, function () { return "Error in resizeBilinear: x must be rank 3 or 4, but got rank " + n.rank + "." }), P(2 === e.length, function () { return "Error in resizeBilinear: new shape must 2D, but got shape " + e + "." }); var o = n, i = !1; 3 === n.rank && (i = !0, o = n.as4D(1, n.shape[0], n.shape[1], n.shape[2])); var a = e[0], s = e[1], u = Kt.runKernelFunc(function (t, e) { return e([o]), t.resizeBilinear(o, a, s, r) }, { x: o }, function (e, n) { return { x: function () { return Kt.runKernelFunc(function (t) { return t.resizeBilinearBackprop(e, n[0], r) }, {}) } } }, "ResizeBilinear", { alignCorners: r, newHeight: a, newWidth: s }); return i ? u.as3D(u.shape[1], u.shape[2], u.shape[3]) : u } }), hh = wn({ resizeNearestNeighbor_: function (t, e, r) { void 0 === r && (r = !1); var n = cn(t, "images", "resizeNearestNeighbor"); P(3 === n.rank || 4 === n.rank, function () { return "Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank " + n.rank + "." }), P(2 === e.length, function () { return "Error in resizeNearestNeighbor: new shape must 2D, but got shape " + e + "." }), P("float32" === n.dtype || "int32" === n.dtype, function () { return "`images` must have `int32` or `float32` as dtype" }); var o = n, i = !1; 3 === n.rank && (i = !0, o = n.as4D(1, n.shape[0], n.shape[1], n.shape[2])); var a = e[0], s = e[1], u = Kt.runKernelFunc(function (t, e) { return e([o]), t.resizeNearestNeighbor(o, a, s, r) }, { batchImages: o }, function (e, n) { return { batchImages: function () { return Kt.runKernelFunc(function (t) { return t.resizeNearestNeighborBackprop(e, n[0], r) }, {}) } } }); return i ? u.as3D(u.shape[1], u.shape[2], u.shape[3]) : u } }), fh = wn({ nonMaxSuppression_: function (t, e, n, r, o) { void 0 === r && (r = .5), void 0 === o && (o = Number.NEGATIVE_INFINITY); var i = cn(t, "boxes", "nonMaxSuppression"), a = cn(e, "scores", "nonMaxSuppression"), s = ih(i, a, n, r, o); n = s.maxOutputSize, r = s.iouThreshold, o = s.scoreThreshold; var u = { maxOutputSize: n, iouThreshold: r, scoreThreshold: o }; return Kt.runKernelFunc(function (t) { return t.nonMaxSuppression(i, a, n, r, o) }, { boxes: i, scores: a }, null, "NonMaxSuppressionV3", u) } }), ph = wn({ nonMaxSuppressionWithScore_: function (t, e, n, r, o, i) { void 0 === r && (r = .5), void 0 === o && (o = Number.NEGATIVE_INFINITY), void 0 === i && (i = 0); var a = cn(t, "boxes", "nonMaxSuppression"), s = cn(e, "scores", "nonMaxSuppression"), u = ih(a, s, n, r, o, i), c = { maxOutputSize: n = u.maxOutputSize, iouThreshold: r = u.iouThreshold, scoreThreshold: o = u.scoreThreshold, softNmsSigma: i = u.softNmsSigma }, l = Kt.runKernel("NonMaxSuppressionV5", { boxes: a, scores: s }, c); return { selectedIndices: l[0], selectedScores: l[1] } } }), dh = wn({ cropAndResize_: function (t, e, n, r, o, i) { var a = cn(t, "image", "cropAndResize"), s = cn(e, "boxes", "cropAndResize", "float32"), u = cn(n, "boxInd", "cropAndResize", "int32"); o = o || "bilinear", i = i || 0; var c = s.shape[0]; return P(4 === a.rank, function () { return "Error in cropAndResize: image must be rank 4,but got rank " + a.rank + "." }), P(2 === s.rank && 4 === s.shape[1], function () { return "Error in cropAndResize: boxes must be have size [" + c + ",4] but had shape " + s.shape + "." }), P(1 === u.rank && u.shape[0] === c, function () { return "Error in cropAndResize: boxInd must be have size [" + c + "] but had shape " + s.shape + "." }), P(2 === r.length, function () { return "Error in cropAndResize: cropSize must be of length 2, but got length " + r.length + "." }), P(1 <= r[0] && 1 <= r[1], function () { return "cropSize must be atleast [1,1], but was " + r }), P("bilinear" === o || "nearest" === o, function () { return "method must be bilinear or nearest, but was " + o }), Kt.runKernelFunc(function (t, e) { return t.cropAndResize(a, s, u, r, o, i) }, { images: a, boxes: s, boxInd: u }, null, "CropAndResize", { method: o, extrapolationValue: i, cropSize: r }) } }), vh = Object.freeze({ resizeBilinear: lh, resizeNearestNeighbor: hh, nonMaxSuppression: fh, nonMaxSuppressionAsync: function (u, c, l, h, f) { return void 0 === h && (h = .5), void 0 === f && (f = Number.NEGATIVE_INFINITY), y(this, void 0, void 0, function () { var e, n, r, o, i, a, s; return R(this, function (t) { switch (t.label) { case 0: return e = cn(u, "boxes", "nonMaxSuppressionAsync"), n = cn(c, "scores", "nonMaxSuppressionAsync"), r = ih(e, n, l, h, f), l = r.maxOutputSize, h = r.iouThreshold, f = r.scoreThreshold, [4, Promise.all([e.data(), n.data()])]; case 1: return o = t.sent(), i = o[0], a = o[1], s = Bo(i, a, l, h, f), e !== u && e.dispose(), n !== c && n.dispose(), [2, s] } }) }) }, nonMaxSuppressionWithScore: ph, nonMaxSuppressionWithScoreAsync: function (u, c, l, h, f, p) { return void 0 === h && (h = .5), void 0 === f && (f = Number.NEGATIVE_INFINITY), void 0 === p && (p = 0), y(this, void 0, void 0, function () { var e, n, r, o, i, a, s; return R(this, function (t) { switch (t.label) { case 0: return e = cn(u, "boxes", "nonMaxSuppressionAsync"), n = cn(c, "scores", "nonMaxSuppressionAsync"), r = ih(e, n, l, h, f, p), l = r.maxOutputSize, h = r.iouThreshold, f = r.scoreThreshold, p = r.softNmsSigma, [4, Promise.all([e.data(), n.data()])]; case 1: return o = t.sent(), i = o[0], a = o[1], s = Lo(i, a, l, h, f, p), e !== u && e.dispose(), n !== c && n.dispose(), [2, s] } }) }) }, cropAndResize: dh }), mh = wn({ fusedMatMul_: function (t) { var e, n = t.a, r = t.b, o = t.transposeA, s = void 0 !== o && o, i = t.transposeB, u = void 0 !== i && i, c = t.bias, a = t.activation, l = void 0 === a ? "linear" : a, h = t.preluActivationWeights; if (!1 === ah(Kt.state.gradientDepth, l)) { var f = Fc(n, r, s, u); return null != c && (f = Ou(f, c)), ch(f, l, h) } var p = cn(n, "a", "fused matMul"), d = cn(r, "b", "fused matMul"); e = Lt(p, d), p = e[0], d = e[1]; var v = s ? p.shape[p.rank - 2] : p.shape[p.rank - 1], m = u ? d.shape[d.rank - 1] : d.shape[d.rank - 2], g = s ? p.shape[p.rank - 1] : p.shape[p.rank - 2], y = u ? d.shape[d.rank - 2] : d.shape[d.rank - 1], x = p.shape.slice(0, -2), b = d.shape.slice(0, -2), w = L(x), C = L(b); P(2 <= p.rank && 2 <= d.rank && p.rank === d.rank, function () { return "Error in fused matMul: inputs must have the same rank of at least 2, got ranks " + p.rank + " and " + d.rank + "." }), P(A(x, b), function () { return "Error in fused matMul: outer dimensions (" + x + ") and (" + b + ") of Tensors with shapes " + p.shape + " and " + d.shape + " must match." }), P(v === m, function () { return "Error in fused matMul: inner shapes (" + v + ") and (" + m + ") of Tensors with shapes " + p.shape + " and " + d.shape + " and transposeA=" + s + " and transposeB=" + u + " must match." }); var E, _, I = p.shape.slice(0, -2).concat([g, y]), R = s ? p.as3D(w, v, g) : p.as3D(w, g, v), k = u ? d.as3D(C, y, m) : d.as3D(C, m, y); null != c && go(I, (E = Lt(E = cn(c, "bias", "fused matMul"), p)[0]).shape), null != h && (_ = cn(h, "prelu weights", "fused matMul")); var S = { a: R, b: k }; null != c && (S.bias = E), null != h && (S.preluActivationWeights = _); var D = [R, k]; return Kt.runKernelFunc(function (t, e) { var n = t.fusedBatchMatMul({ a: R, b: k, transposeA: s, transposeB: u, bias: E, activation: l, preluActivationWeights: _ }); return e([R, k, n]), n }, S, function (t, e) { var n = e[0], r = e[1], o = e[2], i = sh(t, o, l), a = {}; return null != c && (a = { bias: function () { return uh(E, i) } }), s || u ? !s && u ? Object.assign({ a: function () { return i.matMul(r, !1, !1) }, b: function () { return i.matMul(n, !0, !1) } }, a) : s && !u ? Object.assign({ a: function () { return r.matMul(i, !1, !0) }, b: function () { return n.matMul(i, !1, !1) } }, a) : Object.assign({ a: function () { return r.matMul(i, !0, !0) }, b: function () { return i.matMul(n, !0, !0) } }, a) : Object.assign({ a: function () { return i.matMul(r, !1, !0) }, b: function () { return n.matMul(i, !0, !1) } }, a) }, "_FusedMatMul", { transposeA: s, transposeB: u, activation: l }, D, [!0]).reshape(I) } }), gh = wn({ fusedConv2d_: function (t) { var e = t.x, n = t.filter, u = t.strides, c = t.pad, r = t.dataFormat, o = void 0 === r ? "NHWC" : r, i = t.dilations, l = void 0 === i ? [1, 1] : i, a = t.dimRoundingMode, h = t.bias, s = t.activation, f = void 0 === s ? "linear" : s, p = t.preluActivationWeights; if (f = f || "linear", !1 === ah(Kt.state.gradientDepth, f)) { var d = Ec(e, n, u, c, o, l, a); return null != h && (d = Ou(d, h)), ch(d, f, p) } var v = cn(e, "x", "conv2d"), m = cn(n, "filter", "conv2d"), g = v, y = !1; 3 === v.rank && (y = !0, g = v.as4D(1, v.shape[0], v.shape[1], v.shape[2])), P(4 === g.rank, function () { return "Error in fused conv2d: input must be rank 4, but got rank " + g.rank + "." }), P(4 === m.rank, function () { return "Error in fused conv2d: filter must be rank 4, but got rank " + m.rank + "." }), null != a && P(B(c), function () { return "Error in fused conv2d: pad must be an integer when using, dimRoundingMode " + a + " but got pad " + c + "." }), P(g.shape[3] === m.shape[2], function () { return "Error in conv2d: depth of input (" + g.shape[3] + ") must match input depth for filter " + m.shape[2] + "." }), P(So(u, l), function () { return "Error in conv2D: Either strides or dilations must be 1. Got strides " + u + " and dilations '" + l + "'" }), P("NHWC" === o, function () { return "Error in conv2d: got dataFormat of " + o + " but only NHWC is currently supported." }); var x, b, w = bo(g.shape, m.shape, u, l, c, a); null != h && (x = Lt(x = cn(h, "bias", "fused conv2d"), v)[0], go(w.outShape, x.shape)), null != p && (b = cn(p, "prelu weights", "fused conv2d")); var C = { x: g, filter: m }; null != h && (C.bias = x), null != p && (C.preluActivationWeights = b); var E = [m, g], _ = Kt.runKernelFunc(function (t, e) { var n = t.fusedConv2d({ input: g, filter: m, convInfo: w, bias: x, activation: f, preluActivationWeights: b }); return e([m, g, n]), n }, C, function (t, e) { var n = e, r = n[0], o = n[1], i = n[2], a = sh(t, i, f); P(ko(l), function () { return "Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '" + l + "'" }); var s = {}; return null != h && (s = { bias: function () { return uh(x, a) } }), Object.assign({ x: function () { return Rc(o.shape, a, r, u, c) }, filter: function () { return Ic(o, a, r.shape, u, c) } }, s) }, "FusedConv2D", { convInfo: w, activation: f }, E, [!0]); return y ? _.as3D(_.shape[1], _.shape[2], _.shape[3]) : _ } }), yh = wn({ fusedDepthwiseConv2d_: function (t) { var e = t.x, n = t.filter, r = t.strides, o = t.pad, i = t.dataFormat, a = void 0 === i ? "NHWC" : i, s = t.dilations, u = void 0 === s ? [1, 1] : s, c = t.dimRoundingMode, l = t.bias, h = t.activation, f = void 0 === h ? "linear" : h, p = t.preluActivationWeights; if (!1 === ah(Kt.state.gradientDepth, f)) { var d = kc(e, n, r, o, a, u, c); return null != l && (d = Ou(d, l)), ch(d, f, p) } var v = cn(e, "x", "depthwiseConv2d"), m = cn(n, "filter", "depthwiseConv2d"), g = v, y = !1; 3 === v.rank && (y = !0, g = v.as4D(1, v.shape[0], v.shape[1], v.shape[2])), P(4 === g.rank, function () { return "Error in fused depthwiseConv2d: input must be rank 4, but got rank " + g.rank + "." }), P(4 === m.rank, function () { return "Error in fused depthwiseConv2d: filter must be rank 4, but got rank " + m.rank + "." }), P(g.shape[3] === m.shape[2], function () { return "Error in fused depthwiseConv2d: number of input channels (" + g.shape[3] + ") must match the inChannels dimension in filter " + m.shape[2] + "." }), null == u && (u = [1, 1]), P(So(r, u), function () { return "Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides " + r + " and dilations '" + u + "'" }), null != c && P(B(o), function () { return "Error in fused depthwiseConv2d: pad must be an integer when using dimRoundingMode " + c + " but got pad " + o + "." }); var x, b, w = bo(g.shape, m.shape, r, u, o, c, !0); null != l && (x = Lt(x = cn(l, "bias", "fused conv2d"), v)[0], go(w.outShape, x.shape)), null != p && (b = cn(p, "prelu weights", "fused depthwiseConv2d")); var C = { x: g, filter: m }; null != l && (C.bias = x), null != p && (C.preluActivationWeights = b); var E = [m, g], _ = Kt.runKernelFunc(function (t, e) { var n = t.fusedDepthwiseConv2D({ input: g, filter: m, convInfo: w, bias: x, activation: f, preluActivationWeights: b }); return e([m, g, n]), n }, C, function (t, e) { P(ko(u), function () { return "Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '" + u + "'" }); var n = e[0], r = e[1], o = e[2], i = sh(t, o, f), a = {}; return null != l && (a = { bias: function () { return uh(x, i) } }), Object.assign({ x: function () { return Sc(r.shape, i, n, w) }, filter: function () { return Dc(r, i, n.shape, w) } }, a) }, "FusedDepthwiseConv2D", { convInfo: w, activation: f }, E, [!0]); return y ? _.as3D(_.shape[1], _.shape[2], _.shape[3]) : _ } }), xh = Object.freeze({ matMul: mh, conv2d: gh, depthwiseConv2d: yh }), bh = Object.freeze({ image: vh, linalg: oh, losses: Zl, spectral: Al, fused: xh, signal: Gl, square: Ns, squaredDifference: Ms, conv1d: Cc, conv2d: Ec, conv3d: _c, depthwiseConv2d: kc, separableConv2d: Ac, conv2dTranspose: Tc, conv3dTranspose: Nc, op: wn, batchNormalization2d: Cu, batchNormalization3d: Eu, batchNormalization4d: _u, batchNormalization: Iu, batchNorm: Ru, batchNorm2d: ku, batchNorm3d: Su, batchNorm4d: Du, booleanMaskAsync: mc, complex: Cn, real: En, imag: _n, concat: Vn, concat1d: Gn, concat2d: Hn, concat3d: qn, concat4d: jn, split: Kn, matMul: Fc, dot: Mc, outerProduct: Oc, reverse: Pc, reverse1d: Bc, reverse2d: Lc, reverse3d: Wc, reverse4d: zc, maxPool: Gc, avgPool: Hc, pool: qc, maxPool3d: jc, avgPool3d: Kc, slice: Xc, slice1d: Yc, slice2d: $c, slice3d: Jc, slice4d: Qc, abs: Os, acos: Ps, acosh: Bs, asin: Ls, asinh: Ws, atan: zs, atanh: Us, ceil: Vs, clipByValue: Gs, cos: Hs, cosh: qs, erf: js, exp: Ks, expm1: Xs, floor: Ys, log: $s, log1p: Js, logSigmoid: Qs, neg: Zs, reciprocal: tu, round: eu, rsqrt: nu, sigmoid: ru, sign: ou, isNaN: iu, isInf: au, isFinite: su, sin: uu, sinh: cu, softplus: lu, sqrt: hu, step: fu, tan: pu, tanh: du, all: tl, any: el, argMax: nl, argMin: rl, logSumExp: ol, max: il, mean: al, min: sl, moments: ul, sum: cl, prod: ll, equal: nc, equalStrict: rc, greater: oc, greaterEqual: ic, greaterEqualStrict: ac, greaterStrict: sc, less: uc, lessEqual: cc, lessEqualStrict: lc, lessStrict: hc, notEqual: fc, notEqualStrict: pc, add: Ou, addN: Pu, addStrict: Bu, atan2: Lu, div: Wu, divNoNan: zu, divStrict: Uu, floorDiv: Vu, maximum: Gu, maximumStrict: Hu, minimum: qu, minimumStrict: ju, mod: Ku, modStrict: Xu, mul: Yu, mulStrict: $u, pow: Ju, powStrict: Qu, squaredDifferenceStrict: Zu, sub: tc, subStrict: ec, elu: hl, leakyRelu: fl, prelu: pl, relu: dl, relu6: vl, selu: ml, logicalAnd: Au, logicalNot: Tu, logicalOr: Nu, logicalXor: Fu, where: Mu, whereAsync: wu, buffer: cr, print: lr, batchToSpaceND: fr, broadcastTo: pr, cast: dr, clone: vr, cumsum: mr, depthToSpace: gr, expandDims: yr, eye: xr, multinomial: br, oneHot: wr, pad: Cr, pad1d: Er, pad2d: _r, pad3d: Ir, pad4d: Rr, rand: kr, randomNormal: Sr, randomGamma: Dr, randomUniform: Ar, reshape: Tr, spaceToBatchND: Nr, squeeze: Fr, stack: Mr, tile: Or, truncatedNormal: Pr, unstack: Br, setdiff1dAsync: hr, fill: Bn, linspace: Ln, ones: On, range: Wn, scalar: kn, tensor: In, tensor1d: Sn, tensor2d: Dn, tensor3d: An, tensor4d: Tn, tensor5d: Nn, tensor6d: Fn, variable: Mn, zeros: Pn, onesLike: zn, zerosLike: Un, transpose: gl, softmax: so, logSoftmax: uo, localResponseNormalization: yl, norm: xl, gather: gc, unsortedSegmentSum: yc, basicLSTMCell: bl, multiRNNCell: wl, movingAverage: Cl, stridedSlice: El, topk: _l, scatterND: Il, fft: Rl, ifft: kl, rfft: Sl, irfft: Dl, sparseToDense: Tl, gatherND: Nl, diag: Fl, dropout: Ml, hannWindow: Wl, hammingWindow: zl, frame: Ul, stft: Vl, inTopKAsync: Pl }); function wh(t, e) { Array.isArray(t) || (t = [t]), t.forEach(function (t) { null != t && P("complex64" !== t.dtype, function () { return e + " does not support complex64 tensors." }) }) } function Ch(t, e, n, r) { if ("linear" === n) return t.linear(e); if ("relu" === n) return t.relu(e); if ("elu" === n) return t.elu(e); if ("relu6" === n) return t.relu6(e); if ("prelu" === n) return t.prelu(e, r); throw new Error("Activation " + n + " has not been implemented for the CPU backend.") } var Eh, _h = (t(Ih, Eh = lo), Ih.prototype.write = function (t, e, n) { this.firstUse && (this.firstUse = !1, _().get("IS_NODE") && an("\n============================\nHi there 👋. Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. Visit https://github.com/tensorflow/tfjs-node for more details.\n============================")); var r = {}; return this.data.set(r, { values: t, dtype: n }), r }, Ih.prototype.move = function (t, e, n, r) { this.data.set(t, { values: e, dtype: r }) }, Ih.prototype.numDataIds = function () { return this.data.numDataIds() }, Ih.prototype.read = function (e) { return y(this, void 0, void 0, function () { return R(this, function (t) { return [2, this.readSync(e)] }) }) }, Ih.prototype.readSync = function (t) { var e = this.data.get(t), n = e.dtype, r = e.complexTensors; return "complex64" === n ? Mo(this.readSync(r.real.dataId), this.readSync(r.imag.dataId)) : this.data.get(t).values }, Ih.prototype.bufferSync = function (t) { var e = this.readSync(t.dataId), n = e; if ("string" === t.dtype) try { n = e.map(function (t) { return rt(t) }) } catch (t) { throw new Error("Failed to decode encoded string bytes into utf-8") } return cr(t.shape, t.dtype, n) }, Ih.prototype.makeOutput = function (t, e, n) { var r = this.write(t, e, n); return Kt.makeTensorFromDataId(r, e, n, this) }, Ih.prototype.disposeData = function (t) { if (this.data.has(t)) { var e = this.data.get(t).complexTensors; null != e && (e.real.dispose(), e.imag.dispose()), this.data.delete(t) } }, Ih.prototype.time = function (n) { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { return e = tt(), n(), [2, { kernelMs: tt() - e }] }) }) }, Ih.prototype.memory = function () { return { unreliable: !0, reasons: ["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."] } }, Ih.prototype.complex = function (t, e) { var n = this.makeOutput(null, t.shape, "complex64"); return this.data.get(n.dataId).complexTensors = { real: Kt.keep(t.clone()), imag: Kt.keep(e.clone()) }, n }, Ih.prototype.real = function (t) { return this.data.get(t.dataId).complexTensors.real.clone() }, Ih.prototype.imag = function (t) { return this.data.get(t.dataId).complexTensors.imag.clone() }, Ih.prototype.slice = function (t, n, e) { if (wh(t, "slice"), eo(t.shape, n, e)) { var r = no(n, t.strides), o = L(e); return In(this.readSync(t.dataId).subarray(r, r + o), e, t.dtype) } for (var i = cr(e, t.dtype), a = this.bufferSync(t), s = 0; s < i.size; ++s) { var u = i.indexToLoc(s).map(function (t, e) { return t + n[e] }); i.values[s] = a.get.apply(a, u) } return i.toTensor() }, Ih.prototype.stridedSlice = function (t, e, n, r) { wh(t, "stridedSlice"); var o = Qr(e, n, r); if (o.some(function (t) { return 0 === t })) return In([], o); for (var i = cr(o, t.dtype), a = this.bufferSync(t), s = 0; s < i.size; s++) { for (var u = i.indexToLoc(s), c = new Array(u.length), l = 0; l < c.length; l++)c[l] = u[l] * r[l] + e[l]; i.set.apply(i, [a.get.apply(a, c)].concat(u)) } return i.toTensor() }, Ih.prototype.diag = function (t) { for (var e = this.readSync(t.dataId), n = cr([t.size, t.size], t.dtype), r = n.values, o = 0; o < e.length; o++)r[o * t.size + o] = e[o]; return n.toTensor() }, Ih.prototype.unstack = function (t, e) { for (var n = t.shape[e], r = new Array(t.rank - 1), o = 0, i = 0; i < t.rank; i++)i !== e && (r[o++] = t.shape[i]); var a = new Array(t.rank).fill(0), s = t.shape.slice(); s[e] = 1; var u = new Array(n); for (i = 0; i < u.length; i++)u[a[e] = i] = this.slice(t, a, s).reshape(r); return u }, Ih.prototype.reverse = function (r, o) { wh(r, "reverse"); for (var i = cr(r.shape, r.dtype), a = this.bufferSync(r), t = function (t) { var e = i.indexToLoc(t), n = e.slice(); o.forEach(function (t) { return n[t] = r.shape[t] - 1 - n[t] }), i.set.apply(i, [a.get.apply(a, n)].concat(e)) }, e = 0; e < i.size; e++)t(e); return i.toTensor() }, Ih.prototype.concat = function (t, n) { var a = this; if ("complex64" === t[0].dtype) { var e = t.map(function (t) { return En(t) }), r = t.map(function (t) { return _n(t) }); return Cn(this.concat(e, n), this.concat(r, n)) } var o = t.map(function (t) { var e = L(t.shape.slice(n)); return t.as2D(-1, e) }), s = bn(o.map(function (t) { return t.shape }), 1), u = cr(s, t[0].dtype).values; if (1 === o[0].shape[0]) { var i = 0; o.forEach(function (t) { u.set(a.readSync(t.dataId), i), i += t.size }) } else { var c = 0; o.forEach(function (t) { for (var e = a.readSync(t.dataId), n = 0, r = 0; r < t.shape[0]; ++r)for (var o = r * s[1] + c, i = 0; i < t.shape[1]; ++i)u[o + i] = e[n++]; c += t.shape[1] }) } var l = bn(t.map(function (t) { return t.shape }), n); return In(u, l, t[0].dtype) }, Ih.prototype.neg = function (t) { return wh(t, "neg"), this.multiply(kn(-1), t) }, Ih.prototype.add = function (t, e) { return "complex64" === t.dtype || "complex64" === e.dtype ? this.broadcastedBinaryComplexOp(t.cast("complex64"), e.cast("complex64"), function (t, e, n, r) { return { real: t + n, imag: e + r } }) : this.broadcastedBinaryOp(t, e, Pt(t.dtype, e.dtype), function (t, e) { return t + e }) }, Ih.prototype.addN = function (t) { var e = this; wh(t, "addN"); for (var n = t.map(function (t) { return e.readSync(t.dataId) }), r = cr(t[0].shape, t[0].dtype), o = r.values, i = 0; i < t.length; i++)for (var a = n[i], s = 0; s < o.length; s++)o[s] += a[s]; return r.toTensor() }, Ih.prototype.softmax = function (t, e) { var n = D([e], t.shape), r = this.max(t, n), o = dn(r.shape, n), i = this.subtract(t, r.reshape(o)), a = this.exp(i), s = this.sum(a, n).reshape(o); return this.realDivide(a, s) }, Ih.prototype.subtract = function (t, e) { return "complex64" === t.dtype || "complex64" === e.dtype ? this.broadcastedBinaryComplexOp(t.cast("complex64"), e.cast("complex64"), function (t, e, n, r) { return { real: t - n, imag: e - r } }) : this.broadcastedBinaryOp(t, e, Pt(t.dtype, e.dtype), function (t, e) { return t - e }) }, Ih.prototype.pow = function (t, e) { return wh([t, e], "pow"), this.broadcastedBinaryOp(t, e, t.dtype, function (t, e) { return Math.pow(t, e) }) }, Ih.prototype.batchMatMul = function (t, e, n, r) { wh([t, e], "matMul"); for (var o = n ? t.shape[1] : t.shape[2], i = n ? t.shape[2] : t.shape[1], a = r ? e.shape[1] : e.shape[2], s = t.shape[0], u = this.readSync(t.dataId), c = this.readSync(e.dataId), l = n ? [t.strides[0], 1, t.strides[1]] : [t.strides[0], t.strides[1], 1], h = l[0], f = l[1], p = l[2], d = r ? [1, e.strides[1], e.strides[0]] : [e.strides[1], 1, e.strides[0]], v = d[0], m = d[1], g = d[2], y = i * a, x = cr([s, i, a], t.dtype), b = x.values, w = this.blockSize, C = 0; C < s; C++)for (var E = 0; E < i; E += w)for (var _ = 0; _ < a; _ += w)for (var I = 0; I < o; I += w)for (var R = Math.min(E + w, i), k = Math.min(_ + w, a), S = Math.min(I + w, o), D = E; D < R; D++)for (var A = _; A < k; A++) { for (var T = 0, N = I; N < S; N++)T += u[C * h + D * f + N * p] * c[N * v + A * m + C * g]; b[C * y + (D * a + A)] += T } return x.toTensor() }, Ih.prototype.fusedBatchMatMul = function (t) { var e = t.a, n = t.b, r = t.transposeA, o = t.transposeB, i = t.bias, a = t.activation, s = t.preluActivationWeights, u = this.batchMatMul(e, n, r, o); return i && (u = this.add(u, i)), a && (u = Ch(this, u, a, s)), u }, Ih.prototype.multiply = function (t, e) { return "complex64" === t.dtype || "complex64" === e.dtype ? this.broadcastedBinaryComplexOp(t.cast("complex64"), e.cast("complex64"), function (t, e, n, r) { return { real: t * n - e * r, imag: t * r + e * n } }) : this.broadcastedBinaryOp(t, e, Pt(t.dtype, e.dtype), function (t, e) { return t * e }) }, Ih.prototype.realDivide = function (t, e) { return wh([t, e], "realDivide"), this.broadcastedBinaryOp(t, e, "float32", function (t, e) { return t / e }) }, Ih.prototype.floorDiv = function (t, e) { return wh([t, e], "floorDiv"), this.broadcastedBinaryOp(t, e, "int32", function (t, e) { return Math.floor(t / e) }) }, Ih.prototype.sum = function (t, e) { wh(t, "sum"), vn("sum", e, t.rank); for (var n = pn(t.shape, e), r = n[0], o = n[1], i = Pn(r, Pt(t.dtype, "int32")), a = L(o), s = this.readSync(i.dataId), u = this.readSync(t.dataId), c = 0; c < s.length; ++c) { for (var l = c * a, h = 0, f = 0; f < a; ++f)h += u[l + f]; s[c] = h } return i }, Ih.prototype.prod = function (t, e) { wh(t, "sum"); for (var n = pn(t.shape, e), r = n[0], o = n[1], i = Pn(r, Pt(t.dtype, "int32")), a = L(o), s = this.readSync(i.dataId), u = this.readSync(t.dataId), c = 0; c < s.length; ++c) { for (var l = c * a, h = 1, f = 0; f < a; ++f)h *= u[l + f]; s[c] = h } return i }, Ih.prototype.unsortedSegmentSum = function (t, e, n) { wh(t, "unsortedSegmentSum"); for (var r = [], o = t.rank - e.rank, i = 0; i < o; ++i)e = e.expandDims(i + 1); for (i = 0; i < n; ++i) { var a = kn(i, "int32"), s = nc(a, e).asType("float32").mul(t).sum(0); r.push(s) } return Mr(r) }, Ih.prototype.argMin = function (t, e) { wh(t, "argMin"); var n = [e]; vn("argMin", n, t.rank); for (var r = pn(t.shape, n), o = r[0], i = r[1], a = Pn(o, "int32"), s = L(i), u = this.readSync(a.dataId), c = this.readSync(t.dataId), l = 0; l < u.length; ++l) { for (var h = l * s, f = c[h], p = 0, d = 0; d < s; ++d) { var v = c[h + d]; v < f && (f = v, p = d) } u[l] = p } return a }, Ih.prototype.argMax = function (t, e) { wh(t, "argMax"); var n = [e]; vn("argMax", n, t.rank); for (var r = pn(t.shape, n), o = r[0], i = r[1], a = Pn(o, "int32"), s = L(i), u = this.readSync(a.dataId), c = this.readSync(t.dataId), l = 0; l < u.length; ++l) { for (var h = l * s, f = c[h], p = 0, d = 0; d < s; ++d) { var v = c[h + d]; f < v && (f = v, p = d) } u[l] = p } return a }, Ih.prototype.cumsum = function (t, e, n, r) { if (wh(t, "cumsum"), e !== t.rank - 1) throw new Error("backend.cumsum in CPU expects an inner-most axis=" + (t.rank - 1) + " but got axis=" + e); for (var o = Pt(t.dtype, "int32"), i = Pn(t.shape, o), a = this.readSync(i.dataId), s = this.readSync(t.dataId), u = t.shape[t.rank - 1], c = r ? function (t, e) { return t + u - e - 1 } : function (t, e) { return t + e }, l = 0; l < s.length; l += u)for (var h = 0; h < u; h++) { var f = c(l, h); if (0 === h) a[f] = n ? 0 : s[f]; else { var p = c(l, h - 1); a[f] = n ? s[p] + a[p] : s[f] + a[p] } } return i }, Ih.prototype.equal = function (t, e) { return wh([t, e], "equal"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return t === e ? 1 : 0 }) }, Ih.prototype.notEqual = function (t, e) { return wh([t, e], "notEqual"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return t !== e ? 1 : 0 }) }, Ih.prototype.less = function (t, e) { return wh([t, e], "less"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return t < e ? 1 : 0 }) }, Ih.prototype.lessEqual = function (t, e) { return wh([t, e], "lessEqual"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return t <= e ? 1 : 0 }) }, Ih.prototype.greater = function (t, e) { return wh([t, e], "greater"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return e < t ? 1 : 0 }) }, Ih.prototype.greaterEqual = function (t, e) { return wh([t, e], "greaterEqual"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return e <= t ? 1 : 0 }) }, Ih.prototype.logicalNot = function (t) { wh(t, "logicalNot"); for (var e = this.readSync(t.dataId), n = new Uint8Array(e.length), r = 0; r < e.length; ++r)n[r] = e[r] ? 0 : 1; return this.makeOutput(n, t.shape, "bool") }, Ih.prototype.logicalAnd = function (t, e) { return wh([t, e], "logicalAnd"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return t && e }) }, Ih.prototype.logicalOr = function (t, e) { return wh([t, e], "logicalOr"), this.broadcastedBinaryOp(t, e, "bool", function (t, e) { return t || e }) }, Ih.prototype.select = function (t, e, n) { wh([t, e, n], "select"); for (var r = this.readSync(t.dataId), o = this.readSync(e.dataId), i = this.readSync(n.dataId), a = Pn(e.shape, Pt(e.dtype, n.dtype)), s = this.readSync(a.dataId), u = 0, c = 0 === t.rank || 1 < t.rank || 1 === e.rank ? 1 : L(e.shape.slice(1)), l = 0; l < r.length; l++)for (var h = 0; h < c; h++)1 === r[l] ? s[u++] = o[l] : s[u++] = i[l]; return a }, Ih.prototype.where = function (t) { wh([t], "where"); var e = this.readSync(t.dataId); return qo(t.shape, e) }, Ih.prototype.topk = function (t, e, n) { return wh(t, "topk"), Ho(this.readSync(t.dataId), t.shape, t.dtype, e) }, Ih.prototype.min = function (t, e) { wh(t, "min"), vn("min", e, t.rank); for (var n = pn(t.shape, e), r = n[0], o = n[1], i = Pn(r, t.dtype), a = L(o), s = this.readSync(i.dataId), u = this.readSync(t.dataId), c = 0; c < s.length; ++c) { for (var l = c * a, h = u[l], f = 0; f < a; ++f) { var p = u[l + f]; p < h && (h = p) } s[c] = h } return i }, Ih.prototype.minimum = function (t, e) { return wh([t, e], "minimum"), this.broadcastedBinaryOp(t, e, t.dtype, function (t, e) { return Math.min(t, e) }) }, Ih.prototype.mod = function (t, e) { return wh([t, e], "mod"), this.broadcastedBinaryOp(t, e, t.dtype, function (t, e) { var n = t % e; return t < 0 && e < 0 || 0 <= t && 0 <= e ? n : (n + e) % e }) }, Ih.prototype.max = function (t, e) { wh(t, "max"), vn("max", e, t.rank); for (var n = pn(t.shape, e), r = n[0], o = n[1], i = Pn(r, t.dtype), a = L(o), s = this.readSync(i.dataId), u = this.readSync(t.dataId), c = 0; c < s.length; ++c) { for (var l = c * a, h = u[l], f = 0; f < a; ++f) { var p = u[l + f]; h < p && (h = p) } s[c] = h } return i }, Ih.prototype.maximum = function (t, e) { return wh([t, e], "maximum"), this.broadcastedBinaryOp(t, e, t.dtype, function (t, e) { return Math.max(t, e) }) }, Ih.prototype.all = function (t, e) { wh(t, "all"), vn("all", e, t.rank); for (var n = pn(t.shape, e), r = n[0], o = n[1], i = Pn(r, t.dtype), a = L(o), s = this.readSync(i.dataId), u = this.readSync(t.dataId), c = 0; c < s.length; ++c) { for (var l = c * a, h = u[l], f = 0; f < a; ++f) { var p = u[l + f]; h = h && p } s[c] = h } return i }, Ih.prototype.any = function (t, e) { wh(t, "any"), vn("any", e, t.rank); for (var n = pn(t.shape, e), r = n[0], o = n[1], i = Pn(r, t.dtype), a = L(o), s = this.readSync(i.dataId), u = this.readSync(t.dataId), c = 0; c < s.length; ++c) { for (var l = c * a, h = u[l], f = 0; f < a; ++f) { var p = u[l + f]; h = h || p } s[c] = h } return i }, Ih.prototype.squaredDifference = function (t, e) { return wh([t, e], "squaredDifference"), this.broadcastedBinaryOp(t, e, t.dtype, function (t, e) { var n = t - e; return n * n }) }, Ih.prototype.ceil = function (t) { wh(t, "ceil"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r)n[r] = Math.ceil(e[r]); return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.floor = function (t) { wh(t, "floor"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r)n[r] = Math.floor(e[r]); return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.sign = function (t) { wh(t, "x"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r)e[r] < 0 ? n[r] = -1 : 0 < e[r] ? n[r] = 1 : n[r] = 0; return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.isNaN = function (t) { wh(t, "x"); for (var e = this.readSync(t.dataId), n = new Uint8Array(e.length), r = 0; r < e.length; ++r)Number.isNaN(e[r]) && (n[r] = 1); return this.makeOutput(n, t.shape, "bool") }, Ih.prototype.isInf = function (t) { wh(t, "x"); for (var e = this.readSync(t.dataId), n = new Uint8Array(e.length), r = 0; r < e.length; ++r)Math.abs(e[r]) === 1 / 0 && (n[r] = 1); return this.makeOutput(n, t.shape, "bool") }, Ih.prototype.isFinite = function (t) { wh(t, "x"); for (var e = this.readSync(t.dataId), n = new Uint8Array(e.length), r = 0; r < e.length; ++r)Number.isFinite(e[r]) && (n[r] = 1); return this.makeOutput(n, t.shape, "bool") }, Ih.prototype.round = function (t) { wh(t, "round"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r) { var o = Math.floor(e[r]); e[r] - o < .5 ? n[r] = Math.floor(e[r]) : .5 < e[r] - o ? n[r] = Math.ceil(e[r]) : n[r] = o % 2 == 0 ? o : o + 1 } return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.exp = function (t) { wh(t, "exp"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r)n[r] = Math.exp(e[r]); return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.expm1 = function (t) { wh(t, "expm1"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r)n[r] = Math.expm1(e[r]); return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.log = function (t) { wh(t, "log"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r) { var o = e[r]; n[r] = Math.log(o) } return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.log1p = function (t) { wh(t, "log1p"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r) { var o = e[r]; n[r] = Math.log1p(o) } return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.sqrt = function (t) { wh(t, "sqrt"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r) { var o = e[r]; n[r] = Math.sqrt(o) } return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.rsqrt = function (t) { wh(t, "rsqrt"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r) { var o = e[r]; n[r] = 1 / Math.sqrt(o) } return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.reciprocal = function (t) { wh(t, "reciprocal"); for (var e = this.readSync(t.dataId), n = new Float32Array(e.length), r = 0; r < e.length; ++r)n[r] = 1 / e[r]; return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.linear = function (t) { return t }, Ih.prototype.relu = function (t) { wh(t, "relu"); for (var e = Pn(t.shape, t.dtype), n = this.readSync(e.dataId), r = this.readSync(t.dataId), o = 0; o < r.length; ++o)n[o] = Math.max(0, r[o]); return e }, Ih.prototype.relu6 = function (t) { wh(t, "relu"); for (var e = Pn(t.shape, t.dtype), n = this.readSync(e.dataId), r = this.readSync(t.dataId), o = 0; o < r.length; ++o)n[o] = Math.min(Math.max(0, r[o]), 6); return e }, Ih.prototype.prelu = function (t, e) { return wh([t, e], "prelu"), this.broadcastedBinaryOp(t, e, t.dtype, function (t, e) { return t < 0 ? e * t : t }) }, Ih.prototype.elu = function (t) { wh(t, "elu"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r) { var o = n[r]; e[r] = 0 <= o ? o : Math.exp(o) - 1 } return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.eluDer = function (t, e) { wh([t, e], "eluDer"); for (var n = new Float32Array(e.size), r = this.readSync(e.dataId), o = this.readSync(t.dataId), i = 0; i < r.length; ++i) { var a = r[i]; n[i] = 1 <= a ? o[i] : o[i] * (a + 1) } return this.makeOutput(n, e.shape, "float32") }, Ih.prototype.selu = function (t) { wh(t, "selu"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r) { var o = n[r]; e[r] = 0 <= o ? 1.0507009873554805 * o : 1.7580993408473768 * (Math.exp(o) - 1) } return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.clip = function (t, e, n) { wh(t, "clip"); for (var r = new Float32Array(t.size), o = this.readSync(t.dataId), i = 0; i < o.length; ++i) { var a = o[i]; r[i] = n < a ? n : a < e ? e : a } return this.makeOutput(r, t.shape, "float32") }, Ih.prototype.abs = function (t) { for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.abs(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.complexAbs = function (t) { for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < t.size; ++r) { var o = n[2 * r], i = n[2 * r + 1]; e[r] = Math.hypot(o, i) } return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.int = function (t) { wh(t, "int"); for (var e = new Int32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = n[r]; return this.makeOutput(e, t.shape, "int32") }, Ih.prototype.sigmoid = function (t) { wh(t, "sigmoid"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = 1 / (1 + Math.exp(-n[r])); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.softplus = function (t) { wh(t, "softplus"); for (var e = Math.log(1.1920928955078125e-7) + 2, n = new Float32Array(t.size), r = this.readSync(t.dataId), o = 0; o < r.length; ++o) { var i, a = r[o] > -e, s = r[o] < e, u = Math.exp(r[o]); i = s ? u : a ? r[o] : Math.log(1 + u), n[o] = i } return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.sin = function (t) { wh(t, "sin"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.sin(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.cos = function (t) { wh(t, "cos"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.cos(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.tan = function (t) { wh(t, "tan"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.tan(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.asin = function (t) { wh(t, "asin"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.asin(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.acos = function (t) { wh(t, "acos"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.acos(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.atan = function (t) { wh(t, "atan"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.atan(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.atan2 = function (t, e) { return wh([t, e], "atan2"), this.broadcastedBinaryOp(t, e, t.dtype, function (t, e) { return Math.atan2(t, e) }) }, Ih.prototype.sinh = function (t) { wh(t, "sinh"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.sinh(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.cosh = function (t) { wh(t, "cosh"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.cosh(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.tanh = function (t) { wh(t, "tanh"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = w(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.asinh = function (t) { wh(t, "asinh"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.asinh(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.acosh = function (t) { wh(t, "acosh"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.acosh(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.atanh = function (t) { wh(t, "atanh"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r)e[r] = Math.atanh(n[r]); return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.erf = function (t) { wh(t, "erf"); for (var e = new Float32Array(t.size), n = this.readSync(t.dataId), r = 0; r < n.length; ++r) { var o = Math.sign(n[r]), i = Math.abs(n[r]), a = 1 / (1 + .3275911 * i); e[r] = o * (1 - ((((1.061405429 * a - 1.453152027) * a + 1.421413741) * a - .284496736) * a + .254829592) * a * Math.exp(-i * i)) } return this.makeOutput(e, t.shape, "float32") }, Ih.prototype.step = function (t, e) { void 0 === e && (e = 0), wh(t, "step"); for (var n = new Float32Array(t.size), r = this.readSync(t.dataId), o = 0; o < r.length; ++o) { var i = r[o]; isNaN(i) ? n[o] = NaN : n[o] = 0 < i ? 1 : e } return this.makeOutput(n, t.shape, "float32") }, Ih.prototype.fusedConv2d = function (t) { var e = t.input, n = t.filter, r = t.convInfo, o = t.bias, i = t.activation, a = t.preluActivationWeights, s = this.conv2d(e, n, r); return o && (s = this.add(s, o)), i && (s = Ch(this, s, i, a)), s }, Ih.prototype.conv2d = function (t, e, n) { wh([t, e], "conv2d"); for (var r = n.filterHeight, o = n.filterWidth, i = n.dilationHeight, a = n.dilationWidth, s = n.padInfo.left, u = n.padInfo.top, c = "channelsLast" === n.dataFormat, l = cr(n.outShape, t.dtype), h = t.strides[0], f = c ? t.strides[1] : t.strides[2], p = c ? t.strides[2] : 1, d = c ? 1 : t.strides[1], v = l.strides[0], m = c ? l.strides[1] : l.strides[2], g = c ? l.strides[2] : 1, y = c ? 1 : l.strides[1], x = this.readSync(t.dataId), b = this.readSync(e.dataId), w = l.values, C = 0; C < n.batchSize; ++C)for (var E = C * h, _ = C * v, I = 0; I < n.outHeight; ++I)for (var R = _ + I * m, k = I * n.strideHeight - u, S = 0; S < r; S++) { var D = k + S * i; if (!(D < 0 || D >= n.inHeight)) for (var A = S * e.strides[0], T = E + D * f, N = 0; N < n.outWidth; ++N)for (var F = R + N * g, M = N * n.strideWidth - s, O = 0; O < o; O++) { var P = M + O * a; if (!(P < 0 || P >= n.inWidth)) for (var B = T + P * p, L = A + O * e.strides[1], W = 0; W < n.inChannels; ++W) { for (var z = x[B + W * d], U = 0; U < n.outChannels; ++U)w[F + U * y] += z * b[L + U]; L += n.outChannels } } } return l.toTensor() }, Ih.prototype.conv3d = function (t, e, n) { for (var r = n.filterDepth, o = n.filterHeight, i = n.filterWidth, a = n.dilationDepth, s = n.dilationHeight, u = n.dilationWidth, c = n.padInfo.front, l = n.padInfo.left, h = n.padInfo.top, f = cr(n.outShape, t.dtype), p = this.readSync(t.dataId), d = this.readSync(e.dataId), v = f.values, m = 0; m < n.batchSize; ++m)for (var g = m * t.strides[0], y = m * f.strides[0], x = 0; x < n.outDepth; ++x)for (var b = y + x * f.strides[1], w = x * n.strideDepth - c, C = 0; C < r; C++) { var E = w + C * a; if (!(E < 0 || E >= n.inDepth)) for (var _ = C * e.strides[0], I = g + E * t.strides[1], R = 0; R < n.outHeight; ++R)for (var k = b + R * f.strides[2], S = R * n.strideHeight - h, D = 0; D < o; D++) { var A = S + D * s; if (!(A < 0 || A >= n.inHeight)) for (var T = _ + D * e.strides[1], N = I + A * t.strides[2], F = 0; F < n.outWidth; ++F)for (var M = k + F * n.outChannels, O = F * n.strideWidth - l, P = 0; P < i; P++) { var B = O + P * u; if (!(B < 0 || B >= n.inWidth)) for (var L = T + P * e.strides[2], W = N + B * n.inChannels, z = L, U = 0; U < n.inChannels; ++U) { for (var V = p[W + U], G = 0; G < n.outChannels; ++G)v[M + G] += V * d[z + G]; z += n.outChannels } } } } return f.toTensor() }, Ih.prototype.conv2dDerInput = function (t, e, n) { wh([t, e], "conv2dDerInput"); for (var r = cr(n.inShape, "float32"), o = r.values, i = this.readSync(t.dataId), a = this.readSync(e.dataId), s = e.strides, u = s[0], c = s[1], l = s[2], h = n.batchSize, f = n.filterHeight, p = n.filterWidth, d = n.inChannels, v = n.inHeight, m = n.inWidth, g = n.outChannels, y = n.outHeight, x = n.outWidth, b = n.strideHeight, w = n.strideWidth, C = n.dataFormat, E = f - 1 - n.padInfo.top, _ = p - 1 - n.padInfo.left, I = "channelsLast" === C, R = r.strides[0], k = I ? r.strides[1] : r.strides[2], S = I ? r.strides[2] : 1, D = I ? 1 : r.strides[1], A = t.strides[0], T = I ? t.strides[1] : t.strides[2], N = I ? t.strides[2] : 1, F = I ? 1 : t.strides[1], M = 0; M < h; ++M)for (var O = 0; O < d; ++O)for (var P = 0; P < v; ++P)for (var B = P - E, L = Math.max(0, Math.ceil(B / b)), W = Math.min(y, (f + B) / b), z = 0; z < m; ++z) { for (var U = z - _, V = Math.max(0, Math.ceil(U / w)), G = Math.min(x, (p + U) / w), H = 0, q = L; q < W; ++q)for (var j = q * b - B, K = V; K < G; ++K)for (var X = A * M + T * q + N * K, Y = u * (f - 1 - j) + c * (p - 1 - (K * w - U)) + l * O, $ = 0; $ < g; ++$)H += i[X + F * $] * a[Y + $]; o[R * M + k * P + S * z + D * O] = H } return r.toTensor() }, Ih.prototype.conv3dDerInput = function (t, e, n) { for (var r = cr(n.inShape, "float32"), o = r.values, i = r.strides, a = i[0], s = i[1], u = i[2], c = i[3], l = this.readSync(t.dataId), h = t.strides, f = h[0], p = h[1], d = h[2], v = h[3], m = this.readSync(e.dataId), g = e.strides, y = g[0], x = g[1], b = g[2], w = g[3], C = n.batchSize, E = n.filterDepth, _ = n.filterHeight, I = n.filterWidth, R = n.inChannels, k = n.inDepth, S = n.inHeight, D = n.inWidth, A = n.outChannels, T = n.outDepth, N = n.outHeight, F = n.outWidth, M = n.strideDepth, O = n.strideHeight, P = n.strideWidth, B = E - 1 - n.padInfo.front, L = _ - 1 - n.padInfo.top, W = I - 1 - n.padInfo.left, z = 0; z < C; ++z)for (var U = 0; U < R; ++U)for (var V = 0; V < k; ++V)for (var G = V - B, H = Math.max(0, Math.ceil(G / M)), q = Math.min(T, (E + G) / M), j = 0; j < S; ++j)for (var K = j - L, X = Math.max(0, Math.ceil(K / O)), Y = Math.min(N, (_ + K) / O), $ = 0; $ < D; ++$) { for (var J = $ - W, Q = Math.max(0, Math.ceil(J / P)), Z = Math.min(F, (I + J) / P), tt = 0, et = H; et < q; ++et)for (var nt = et * M - G, rt = X; rt < Y; ++rt)for (var ot = rt * O - K, it = Q; it < Z; ++it)for (var at = f * z + p * et + d * rt + v * it, st = y * (E - 1 - nt) + x * (_ - 1 - ot) + b * (I - 1 - (it * P - J)) + w * U, ut = 0; ut < A; ++ut)tt += l[at + ut] * m[st + ut]; o[a * z + s * V + u * j + c * $ + U] = tt } return r.toTensor() }, Ih.prototype.conv2dDerFilter = function (t, e, n) { wh([t, e], "conv2dDerFilter"); for (var r = n.strideHeight, o = n.strideWidth, i = n.filterHeight, a = n.filterWidth, s = "channelsLast" === n.dataFormat, u = cr(n.filterShape, "float32"), c = n.padInfo.left, l = n.padInfo.top, h = this.bufferSync(t), f = this.bufferSync(e), p = 0; p < i; ++p)for (var d = Math.max(0, Math.ceil((l - p) / r)), v = Math.min(n.outHeight, (n.inHeight + l - p) / r), m = 0; m < a; ++m)for (var g = Math.max(0, Math.ceil((c - m) / o)), y = Math.min(n.outWidth, (n.inWidth + c - m) / o), x = 0; x < n.inChannels; ++x)for (var b = 0; b < n.outChannels; ++b) { for (var w = 0, C = 0; C < n.batchSize; ++C)for (var E = d; E < v; ++E)for (var _ = p + E * r - l, I = g; I < y; ++I) { var R = m + I * o - c; w += s ? h.get(C, _, R, x) * f.get(C, E, I, b) : h.get(C, x, _, R) * f.get(C, b, E, I) } u.set(w, p, m, x, b) } return u.toTensor() }, Ih.prototype.conv3dDerFilter = function (t, e, n) { for (var r = n.strideDepth, o = n.strideHeight, i = n.strideWidth, a = n.filterDepth, s = n.filterHeight, u = n.filterWidth, c = cr(n.filterShape, "float32"), l = c.values, h = c.strides, f = h[0], p = h[1], d = h[2], v = h[3], m = this.readSync(e.dataId), g = e.strides, y = g[0], x = g[1], b = g[2], w = g[3], C = this.readSync(t.dataId), E = t.strides, _ = E[0], I = E[1], R = E[2], k = E[3], S = n.padInfo.front, D = n.padInfo.left, A = n.padInfo.top, T = 0; T < a; ++T)for (var N = Math.max(0, Math.ceil((S - T) / r)), F = Math.min(n.outDepth, (n.inDepth + S - T) / r), M = T * f, O = 0; O < s; ++O)for (var P = Math.max(0, Math.ceil((A - O) / o)), B = Math.min(n.outHeight, (n.inHeight + A - O) / o), L = O * p + M, W = 0; W < u; ++W)for (var z = Math.max(0, Math.ceil((D - W) / i)), U = Math.min(n.outWidth, (n.inWidth + D - W) / i), V = W * d + L, G = 0; G < n.inChannels; ++G)for (var H = G * v + V, q = 0; q < n.outChannels; ++q) { for (var j = 0, K = 0; K < n.batchSize; ++K)for (var X = K * _, Y = K * y, $ = N; $ < F; ++$)for (var J = (T + $ * r - S) * I + X, Q = $ * x + Y, Z = P; Z < B; ++Z)for (var tt = (O + Z * o - A) * R + J, et = Z * b + Q, nt = z; nt < U; ++nt) { var rt = nt * w + et; j += C[(W + nt * i - D) * k + tt + G] * m[rt + q] } l[H + q] = j } return c.toTensor() }, Ih.prototype.fusedDepthwiseConv2D = function (t) { var e = t.input, n = t.filter, r = t.convInfo, o = t.bias, i = t.activation, a = t.preluActivationWeights, s = this.depthwiseConv2D(e, n, r); return o && (s = this.add(s, o)), i && (s = Ch(this, s, i, a)), s }, Ih.prototype.depthwiseConv2D = function (t, e, n) { wh([t, e], "depthwiseConv2D"); for (var r = n.filterHeight, o = n.filterWidth, i = n.dilationHeight, a = n.dilationWidth, s = n.padInfo.left, u = n.padInfo.top, c = n.outChannels / n.inChannels, l = cr(n.outShape, t.dtype), h = this.readSync(t.dataId), f = this.readSync(e.dataId), p = l.values, d = 0; d < n.batchSize; ++d)for (var v = d * t.strides[0], m = d * l.strides[0], g = 0; g < n.outHeight; ++g)for (var y = m + g * l.strides[1], x = g * n.strideHeight - s, b = 0; b < r; ++b) { var w = x + b * i; if (!(w < 0 || w >= n.inHeight)) for (var C = b * e.strides[0], E = v + w * t.strides[1], _ = 0; _ < n.outWidth; ++_)for (var I = y + _ * l.strides[2], R = _ * n.strideWidth - u, k = 0; k < o; ++k) { var S = R + k * a; if (!(S < 0 || S >= n.inWidth)) for (var D = C + k * e.strides[1], A = E + S * n.inChannels, T = I, N = D, F = 0; F < n.inChannels; ++F) { for (var M = h[A + F], O = 0; O < c; ++O)p[T + O] += M * f[N + O]; T += c, N += c } } } return l.toTensor() }, Ih.prototype.depthwiseConv2DDerInput = function (t, e, n) { wh([t, e], "depthwiseConv2DDerInput"); for (var r = cr(n.inShape, "float32"), o = r.values, i = r.strides, a = i[0], s = i[1], u = i[2], c = this.readSync(t.dataId), l = t.strides, h = l[0], f = l[1], p = l[2], d = this.readSync(e.dataId), v = e.strides, m = v[0], g = v[1], y = v[2], x = n.batchSize, b = n.filterHeight, w = n.filterWidth, C = n.inChannels, E = n.inHeight, _ = n.inWidth, I = n.outChannels, R = n.outHeight, k = n.outWidth, S = n.strideHeight, D = n.strideWidth, A = b - 1 - n.padInfo.top, T = w - 1 - n.padInfo.left, N = I / C, F = 0; F < x; ++F)for (var M = 0; M < C; ++M)for (var O = 0; O < E; ++O)for (var P = O - A, B = Math.max(0, Math.ceil(P / S)), L = Math.min(R, (b + P) / S), W = 0; W < _; ++W) { for (var z = W - T, U = Math.max(0, Math.ceil(z / D)), V = Math.min(k, (w + z) / D), G = 0, H = B; H < L; ++H)for (var q = H * S - P, j = U; j < V; ++j)for (var K = h * F + f * H + p * j, X = m * (b - 1 - q) + g * (w - 1 - (j * D - z)) + y * M, Y = 0; Y < N; ++Y)G += c[K + (M * N + Y)] * d[X + Y]; o[a * F + s * O + u * W + M] = G } return r.toTensor() }, Ih.prototype.depthwiseConv2DDerFilter = function (t, e, n) { wh([t, e], "depthwiseConv2DDerFilter"); for (var r = n.strideHeight, o = n.strideWidth, i = n.filterHeight, a = n.filterWidth, s = cr(n.filterShape, "float32"), u = n.padInfo.left, c = n.padInfo.top, l = n.outChannels / n.inChannels, h = this.bufferSync(t), f = this.bufferSync(e), p = 0; p < i; ++p)for (var d = Math.max(0, Math.ceil((c - p) / r)), v = Math.min(n.outHeight, (n.inHeight + c - p) / r), m = 0; m < a; ++m)for (var g = Math.max(0, Math.ceil((u - m) / o)), y = Math.min(n.outWidth, (n.inWidth + u - m) / o), x = 0; x < n.outChannels; ++x) { for (var b = Math.trunc(x / l), w = x % l, C = 0, E = 0; E < n.batchSize; ++E)for (var _ = d; _ < v; ++_)for (var I = p + _ * r - c, R = g; R < y; ++R) { var k = m + R * o - u; C += h.get(E, I, k, b) * f.get(E, _, R, x) } s.set(C, p, m, b, w) } return s.toTensor() }, Ih.prototype.tile = function (t, e) { return wh(t, "tile"), Go(this.bufferSync(t), e) }, Ih.prototype.pad = function (n, t, e) { wh(n, "pad"); var r = t.map(function (t, e) { return t[0] + n.shape[e] + t[1] }), o = t.map(function (t) { return t[0] }), i = this.bufferSync(n), a = cr(r, n.dtype); 0 !== e && a.values.fill(e); for (var s = 0; s < n.size; s++) { var u = i.indexToLoc(s), c = u.map(function (t, e) { return t + o[e] }); a.set.apply(a, [i.get.apply(i, u)].concat(c)) } return a.toTensor() }, Ih.prototype.transpose = function (t, e) { wh(t, "transpose"); for (var n = new Array(t.rank), r = 0; r < n.length; r++)n[r] = t.shape[e[r]]; var o = this.readSync(t.dataId), i = cr(n, t.dtype), a = this.bufferSync(t); for (r = 0; r < t.size; ++r) { for (var s = a.indexToLoc(r), u = new Array(s.length), c = 0; c < u.length; c++)u[c] = s[e[c]]; var l = i.locToIndex(u); i.values[l] = o[r] } return i.toTensor() }, Ih.prototype.gather = function (t, e, n) { wh([t, e], "gather"); var r = t.shape.slice(), o = this.readSync(e.dataId); r[n] = o.length; for (var i = cr(r, t.dtype), a = this.bufferSync(t), s = 0; s < i.size; ++s) { var u = i.indexToLoc(s), c = u.slice(); c[n] = o[u[n]]; var l = a.locToIndex(c); i.values[s] = a.values[l] } return i.toTensor() }, Ih.prototype.batchToSpaceND = function (t, e, n) { wh([t], "batchToSpaceND"); var r = e.reduce(function (t, e) { return t * e }), o = Lr(t.shape, e, r), i = Wr(o.length, e.length), a = zr(t.shape, e, r), s = Ur(n, e.length), u = Vr(a, n, e.length); return t.reshape(o).transpose(i).reshape(a).slice(s, u) }, Ih.prototype.spaceToBatchND = function (t, e, n) { wh([t], "spaceToBatchND"); var r = e.reduce(function (t, e) { return t * e }), o = [[0, 0]]; o.push.apply(o, n); for (var i = 1 + e.length; i < t.shape.length; ++i)o.push([0, 0]); var a = t.pad(o), s = Lr(a.shape, e, r, !1), u = Wr(s.length, e.length, !1), c = zr(a.shape, e, r, !1); return a.reshape(s).transpose(u).reshape(c) }, Ih.prototype.pool = function (t, e, n) { wh(t, "pool"); for (var r = e.strideHeight, o = e.strideWidth, i = e.dilationHeight, a = e.dilationWidth, s = e.effectiveFilterHeight, u = e.effectiveFilterWidth, c = e.padInfo.top, l = e.padInfo.left, h = "max" === n ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY, f = this.readSync(t.dataId), p = cr(e.outShape, t.dtype), d = p.values, v = e.outShape[1] * e.outShape[2] * e.outShape[3], m = e.outShape[2] * e.outShape[3], g = e.outShape[3], y = 0; y < e.batchSize; ++y)for (var x = y * v, b = y * t.strides[0], w = 0; w < e.inChannels; ++w)for (var C = 0; C < e.outHeight; ++C)for (var E = C * r - c, _ = Math.max(0, E), I = Math.min(e.inHeight, s + E), R = x + C * m, k = 0; k < e.outWidth; ++k) { for (var S = k * o - l, D = Math.max(0, S), A = Math.min(e.inWidth, u + S), T = h, N = 0, F = 0, M = _; M < I; M += i) { for (var O = b + M * t.strides[1], P = D; P < A; P += a) { var B = f[O + P * t.strides[2] + w]; "max" === n && T < B ? T = B : "avg" === n && (N += B, F++) } if (isNaN(T)) break } d[R + k * g + w] = "avg" === n ? N / F : T } return p.toTensor() }, Ih.prototype.maxPool = function (t, e) { return this.pool(t, e, "max") }, Ih.prototype.maxPoolPositions = function (t, e) { for (var n = cr(e.outShape, "int32"), r = e.strideHeight, o = e.strideWidth, i = e.dilationHeight, a = e.dilationWidth, s = e.effectiveFilterHeight, u = e.effectiveFilterWidth, c = e.padInfo.top, l = e.padInfo.left, h = this.bufferSync(t), f = 0; f < e.batchSize; ++f)for (var p = 0; p < e.inChannels; ++p)for (var d = 0; d < e.outHeight; ++d) { for (var v = d * r - c, m = v; m < 0;)m += i; for (var g = Math.min(e.inHeight, s + v), y = 0; y < e.outWidth; ++y) { for (var x = y * o - l, b = x; b < 0;)b += a; for (var w = Math.min(e.inWidth, u + x), C = Number.NEGATIVE_INFINITY, E = -1, _ = m; _ < g; _ += i)for (var I = _ - v, R = b; R < w; R += a) { var k = R - x, S = h.get(f, _, R, p); C < S && (C = S, E = I * u + k) } n.set(E, f, d, y, p) } } return n.toTensor() }, Ih.prototype.maxPoolBackprop = function (t, e, n, r) { wh([e, n], "maxPoolBackprop"); for (var o = this.maxPoolPositions(e, r), i = r.strideHeight, a = r.strideWidth, s = r.dilationHeight, u = r.dilationWidth, c = r.effectiveFilterHeight, l = r.effectiveFilterWidth, h = l - 1 - r.padInfo.left, f = c - 1 - r.padInfo.top, p = cr(e.shape, "float32"), d = this.bufferSync(o), v = this.bufferSync(t), m = 0; m < r.batchSize; ++m)for (var g = 0; g < r.inChannels; ++g)for (var y = 0; y < r.inHeight; ++y)for (var x = 0; x < r.inWidth; ++x) { for (var b = y - f, w = x - h, C = 0, E = 0; E < c; E += s) { var _ = (b + E) / i; if (!(_ < 0 || _ >= r.outHeight || Math.floor(_) !== _)) for (var I = 0; I < l; I += u) { var R = (w + I) / a; if (!(R < 0 || R >= r.outWidth || Math.floor(R) !== R)) { var k = c * l - 1 - d.get(m, _, R, g) === E * l + I ? 1 : 0; 0 != k && (C += v.get(m, _, R, g) * k) } } } p.set(C, m, y, x, g) } return p.toTensor() }, Ih.prototype.avgPoolBackprop = function (t, e, n) { wh([t, e], "avgPoolBackprop"); for (var r = n.strideHeight, o = n.strideWidth, i = n.filterHeight, a = n.filterWidth, s = n.dilationHeight, u = n.dilationWidth, c = n.effectiveFilterHeight, l = n.effectiveFilterWidth, h = l - 1 - n.padInfo.left, f = c - 1 - n.padInfo.top, p = cr(e.shape, "float32"), d = 1 / (i * a), v = this.bufferSync(t), m = 0; m < n.batchSize; ++m)for (var g = 0; g < n.inChannels; ++g)for (var y = 0; y < n.inHeight; ++y)for (var x = 0; x < n.inWidth; ++x) { for (var b = y - f, w = x - h, C = 0, E = 0; E < c; E += s) { var _ = (b + E) / r; if (!(_ < 0 || _ >= n.outHeight || Math.floor(_) !== _)) for (var I = 0; I < l; I += u) { var R = (w + I) / o; R < 0 || R >= n.outWidth || Math.floor(R) !== R || (C += v.get(m, _, R, g)) } } p.set(C * d, m, y, x, g) } return p.toTensor() }, Ih.prototype.pool3d = function (t, e, n) { wh(t, "pool3d"); for (var r = e.strideDepth, o = e.strideHeight, i = e.strideWidth, a = e.dilationDepth, s = e.dilationHeight, u = e.dilationWidth, c = e.effectiveFilterDepth, l = e.effectiveFilterHeight, h = e.effectiveFilterWidth, f = e.padInfo.front, p = e.padInfo.top, d = e.padInfo.left, v = "max" === n ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY, m = this.readSync(t.dataId), g = cr(e.outShape, t.dtype), y = g.values, x = e.outShape[1] * e.outShape[2] * e.outShape[3] * e.outShape[4], b = e.outShape[2] * e.outShape[3] * e.outShape[4], w = e.outShape[3] * e.outShape[4], C = e.outShape[4], E = 0; E < e.batchSize; ++E)for (var _ = E * x, I = E * t.strides[0], R = 0; R < e.inChannels; ++R)for (var k = 0; k < e.outDepth; ++k) { for (var S = k * r - f, D = S; D < 0;)D += a; for (var A = Math.min(e.inDepth, c + S), T = _ + k * b, N = 0; N < e.outHeight; ++N) { for (var F = N * o - p, M = F; M < 0;)M += s; for (var O = Math.min(e.inHeight, l + F), P = T + N * w, B = 0; B < e.outWidth; ++B) { for (var L = B * i - d, W = L; W < 0;)W += u; for (var z = Math.min(e.inWidth, h + L), U = P + B * C, V = v, G = 0, H = 0, q = D; q < A; q += a) { for (var j = I + q * t.strides[1], K = M; K < O; K += s) { for (var X = j + K * t.strides[2], Y = W; Y < z; Y += u) { var $ = m[X + Y * t.strides[3] + R]; if ("max" === n && V < $ ? V = $ : "avg" === n && (G += $, H++), isNaN(V)) break } if (isNaN(V)) break } if (isNaN(V)) break } y[U + R] = "avg" === n ? G / H : V } } } return g.toTensor() }, Ih.prototype.avgPool3d = function (t, e) { return wh(t, "avgPool3d"), this.pool3d(t, e, "avg").toFloat() }, Ih.prototype.avgPool3dBackprop = function (t, e, n) { wh([t, e], "avgPool3dBackprop"); for (var r = n.strideDepth, o = n.strideHeight, i = n.strideWidth, a = n.filterDepth, s = n.filterHeight, u = n.filterWidth, c = n.dilationDepth, l = n.dilationHeight, h = n.dilationWidth, f = n.effectiveFilterDepth, p = n.effectiveFilterHeight, d = n.effectiveFilterWidth, v = f - 1 - n.padInfo.front, m = d - 1 - n.padInfo.left, g = p - 1 - n.padInfo.top, y = cr(e.shape, "float32"), x = 1 / (a * s * u), b = this.bufferSync(t), w = 0; w < n.batchSize; ++w)for (var C = 0; C < n.inChannels; ++C)for (var E = 0; E < n.inDepth; ++E)for (var _ = 0; _ < n.inHeight; ++_)for (var I = 0; I < n.inWidth; ++I) { for (var R = E - v, k = _ - g, S = I - m, D = 0, A = 0; A < f; A += c) { var T = (R + A) / r; if (!(T < 0 || T >= n.outDepth || Math.floor(T) !== T)) for (var N = 0; N < p; N += l) { var F = (k + N) / o; if (!(F < 0 || F >= n.outHeight || Math.floor(F) !== F)) for (var M = 0; M < d; M += h) { var O = (S + M) / i; O < 0 || O >= n.outWidth || Math.floor(O) !== O || (D += b.get(w, T, F, O, C)) } } } y.set(D * x, w, E, _, I, C) } return y.toTensor() }, Ih.prototype.maxPool3d = function (t, e) { return wh(t, "maxPool3d"), this.pool3d(t, e, "max").toFloat() }, Ih.prototype.maxPool3dPositions = function (t, e) { for (var n = cr(e.outShape, "int32"), r = e.strideDepth, o = e.strideHeight, i = e.strideWidth, a = e.dilationDepth, s = e.dilationHeight, u = e.dilationWidth, c = e.effectiveFilterDepth, l = e.effectiveFilterHeight, h = e.effectiveFilterWidth, f = e.padInfo.front, p = e.padInfo.top, d = e.padInfo.left, v = this.bufferSync(t), m = 0; m < e.batchSize; ++m)for (var g = 0; g < e.inChannels; ++g)for (var y = 0; y < e.outDepth; ++y) { for (var x = y * r - f, b = x; b < 0;)b += a; for (var w = Math.min(e.inDepth, c + x), C = 0; C < e.outHeight; ++C) { for (var E = C * o - p, _ = E; _ < 0;)_ += s; for (var I = Math.min(e.inHeight, l + E), R = 0; R < e.outWidth; ++R) { for (var k = R * i - d, S = k; S < 0;)S += u; for (var D = Math.min(e.inWidth, h + k), A = Number.NEGATIVE_INFINITY, T = -1, N = b; N < w; N += a)for (var F = N - x, M = _; M < I; M += s)for (var O = M - E, P = S; P < D; P += u) { var B = P - k, L = v.get(m, N, M, P, g); A <= L && (A = L, T = F * l * h + O * l + B) } n.set(T, m, y, C, R, g) } } } return n.toTensor() }, Ih.prototype.maxPool3dBackprop = function (t, e, n, r) { wh([e, n], "maxPool3dBackprop"); for (var o = this.maxPool3dPositions(e, r), i = r.strideDepth, a = r.strideHeight, s = r.strideWidth, u = r.dilationDepth, c = r.dilationHeight, l = r.dilationWidth, h = r.effectiveFilterDepth, f = r.effectiveFilterHeight, p = r.effectiveFilterWidth, d = h - 1 - r.padInfo.front, v = p - 1 - r.padInfo.left, m = f - 1 - r.padInfo.top, g = cr(e.shape, "float32"), y = this.bufferSync(o), x = this.bufferSync(t), b = 0; b < r.batchSize; ++b)for (var w = 0; w < r.inChannels; ++w)for (var C = 0; C < r.inDepth; ++C)for (var E = 0; E < r.inHeight; ++E)for (var _ = 0; _ < r.inWidth; ++_) { for (var I = C - d, R = E - m, k = _ - v, S = 0, D = 0; D < h; D += u) { var A = (I + D) / i; if (!(A < 0 || A >= r.outDepth || Math.floor(A) !== A)) for (var T = 0; T < f; T += c) { var N = (R + T) / a; if (!(N < 0 || N >= r.outHeight || Math.floor(N) !== N)) for (var F = 0; F < p; F += l) { var M = (k + F) / s; if (!(M < 0 || M >= r.outWidth || Math.floor(M) !== M)) { var O = h * f * p - 1 - y.get(b, A, N, M, w) === D * f * p + T * p + F ? 1 : 0; 0 != O && (S += x.get(b, A, N, M, w) * O) } } } } g.set(S, b, C, E, _, w) } return g.toTensor() }, Ih.prototype.cast = function (t, e) { return Ao(t, e, this) }, Ih.prototype.reshape = function (t, e) { return To(t, e) }, Ih.prototype.avgPool = function (t, e) { return wh(t, "avgPool"), this.pool(t, e, "avg").toFloat() }, Ih.prototype.resizeBilinear = function (t, e, n, r) { wh(t, "resizeBilinear"); for (var o = t.shape, i = o[0], a = o[1], s = o[2], u = o[3], c = this.readSync(t.dataId), l = new Float32Array(L([i, e, n, u])), h = [r && 1 < e ? a - 1 : a, r && 1 < n ? s - 1 : s], f = [r && 1 < e ? e - 1 : e, r && 1 < n ? n - 1 : n], p = 0, d = h[0] / f[0], v = h[1] / f[1], m = 0; m < i; m++)for (var g = 0; g < e; g++)for (var y = d * g, x = Math.floor(y), b = y - x, w = Math.min(a - 1, Math.ceil(y)), C = m * t.strides[0] + x * t.strides[1], E = m * t.strides[0] + w * t.strides[1], _ = 0; _ < n; _++)for (var I = v * _, R = Math.floor(I), k = I - R, S = Math.min(s - 1, Math.ceil(I)), D = C + R * t.strides[2], A = E + R * t.strides[2], T = C + S * t.strides[2], N = E + S * t.strides[2], F = 0; F < u; F++) { var M = c[D + F], O = c[A + F], P = M + (c[T + F] - M) * k, B = P + (O + (c[N + F] - O) * k - P) * b; l[p++] = B } return In(l, [i, e, n, u]) }, Ih.prototype.resizeBilinearBackprop = function (t, e, n) { wh([t, e], "resizeBilinearBackprop"); for (var r = e.shape, o = r[0], i = r[1], a = r[2], s = r[3], u = t.shape, c = u[1], l = u[2], h = new Float32Array(o * i * a * s), f = [n && 1 < c ? i - 1 : i, n && 1 < l ? a - 1 : a], p = [n && 1 < c ? c - 1 : c, n && 1 < l ? l - 1 : l], d = f[0] / p[0], v = f[1] / p[1], m = this.readSync(t.dataId), g = 0, y = 0; y < o; y++)for (var x = y * e.strides[0], b = 0; b < c; b++)for (var w = b * d, C = Math.floor(w), E = Math.min(Math.ceil(w), i - 1), _ = x + C * e.strides[1], I = x + E * e.strides[1], R = w - C, k = 1 - R, S = 0; S < l; S++)for (var D = S * v, A = Math.floor(D), T = Math.min(Math.ceil(D), a - 1), N = D - A, F = 1 - N, M = _ + A * e.strides[2], O = _ + T * e.strides[2], P = I + A * e.strides[2], B = I + T * e.strides[2], L = k * F, W = k * N, z = R * F, U = R * N, V = 0; V < s; V++) { var G = m[g++]; h[M + V] += G * L, h[O + V] += G * W, h[P + V] += G * z, h[B + V] += G * U } return Tn(h, [o, a, i, s], e.dtype) }, Ih.prototype.resizeNearestNeighbor = function (t, e, n, r) { wh(t, "resizeNearestNeighbor"); for (var o = t.shape, i = o[0], a = o[1], s = o[2], u = o[3], c = this.readSync(t.dataId), l = new Float32Array(i * e * n * u), h = [r && 1 < e ? a - 1 : a, r && 1 < n ? s - 1 : s], f = [r && 1 < e ? e - 1 : e, r && 1 < n ? n - 1 : n], p = h[0] / f[0], d = h[1] / f[1], v = 0, m = 0; m < i; m++)for (var g = m * t.strides[0], y = 0; y < e; y++)for (var x = p * y, b = g + Math.min(a - 1, r ? Math.round(x) : Math.floor(x)) * t.strides[1], w = 0; w < n; w++)for (var C = d * w, E = b + Math.min(s - 1, r ? Math.round(C) : Math.floor(C)) * t.strides[2], _ = 0; _ < u; _++) { var I = c[E + _]; l[v++] = I } return In(l, [i, e, n, u], t.dtype) }, Ih.prototype.resizeNearestNeighborBackprop = function (t, e, n) { wh([t, e], "resizeNearestNeighborBackprop"); for (var r = e.shape, o = r[0], i = r[1], a = r[2], s = r[3], u = t.shape, c = u[1], l = u[2], h = new Float32Array(o * i * a * s), f = this.readSync(t.dataId), p = [n && 1 < c ? i - 1 : i, n && 1 < l ? a - 1 : a], d = [n && 1 < c ? c - 1 : c, n && 1 < l ? l - 1 : l], v = p[0] / d[0], m = p[1] / d[1], g = 1 / v, y = 1 / m, x = 2 * Math.ceil(g) + 2, b = 2 * Math.ceil(y) + 2, w = 0; w < o; w++)for (var C = w * e.strides[0], E = 0; E < i; E++)for (var _ = C + E * e.strides[1], I = Math.floor(E * g), R = Math.floor(I - x / 2), k = 0; k < a; k++)for (var S = _ + k * e.strides[2], D = Math.floor(k * y), A = Math.floor(D - b / 2), T = 0; T < s; T++) { for (var N = 0, F = 0; F < x; F++) { var M = F + R; if (!(M < 0 || c <= M)) { var O = C + M * t.strides[1], P = M * v; if (E === Math.min(i - 1, n ? Math.round(P) : Math.floor(P))) for (var B = 0; B < b; B++) { var L = B + A; if (!(L < 0 || l <= L)) { var W = O + L * t.strides[2], z = L * m; k === Math.min(a - 1, n ? Math.round(z) : Math.floor(z)) && (N += f[W + T]) } } } } h[S + T] = N } return Tn(h, e.shape, e.dtype) }, Ih.prototype.batchNormalization = function (t, e, n, r, o, i) { wh([t, e, n, o, i], "batchNorm"); for (var a = this.readSync(t.dataId), s = this.readSync(e.dataId), u = this.readSync(n.dataId), c = o ? this.readSync(o.dataId) : new Float32Array([1]), l = i ? this.readSync(i.dataId) : new Float32Array([0]), h = new Float32Array(a.length), f = l.length, p = c.length, d = u.length, v = s.length, m = 0, g = 0, y = 0, x = 0, b = 0; b < a.length; ++b)h[b] = l[m++] + (a[b] - s[g++]) * c[y++] / Math.sqrt(u[x++] + r), f <= m && (m = 0), v <= g && (g = 0), p <= y && (y = 0), d <= x && (x = 0); return Tn(h, t.shape) }, Ih.prototype.localResponseNormalization4D = function (t, a, e, n, r) { wh(t, "localResponseNormalization4D"); var s = t.shape[3], u = s - 1, c = this.readSync(t.dataId), o = t.size, i = new Float32Array(o); function l(t) { for (var e = t % s, n = t - e + Math.max(0, e - a), r = t - e + Math.min(e + a, u), o = 0; n <= r; n++) { var i = c[n]; o += i * i } return o } for (var h = 0; h < o; h++) { var f = l(h), p = c[h] * Math.pow(e + n * f, -r); i[h] = p } return Tn(i, t.shape) }, Ih.prototype.LRNGrad = function (t, e, n, r, o, i, a) { wh(t, "LRNGrad"); for (var s = t.shape[3], u = this.readSync(t.dataId), c = this.readSync(e.dataId), l = this.readSync(n.dataId), h = new Float32Array(t.size), f = t.size, p = 0; p < f; p++) { for (var d = p % s, v = p - d + Math.max(0, d - r), m = p - d + Math.min(s, d + r + 1), g = 0, y = v; y < m; y++)g += Math.pow(c[y], 2); for (g = i * g + o, y = v; y < m; y++) { var x = -2 * i * a * c[y] * l[p] / g; p === y && (x += Math.pow(g, -a)), x *= u[p], h[y] += x } } return Tn(h, t.shape) }, Ih.prototype.multinomial = function (t, e, n, r) { wh(t, "multinomial"); for (var o = e ? t : so(t), i = o.shape[0], a = o.shape[1], s = Pn([i, n], "int32"), u = this.readSync(s.dataId), c = this.readSync(o.dataId), l = 0; l < i; ++l) { var h = l * a, f = new Float32Array(a - 1); f[0] = c[h]; for (var p = 1; p < f.length; ++p)f[p] = f[p - 1] + c[h + p]; for (var d = nr(r.toString()), v = l * n, m = 0; m < n; ++m) { var g = d(); u[v + m] = f.length; for (var y = 0; y < f.length; y++)if (g < f[y]) { u[v + m] = y; break } } } return s }, Ih.prototype.oneHot = function (t, e, n, r) { wh(t, "oneHot"); var o = new Float32Array(t.size * e); o.fill(r); for (var i = this.readSync(t.dataId), a = 0; a < t.size; ++a)0 <= i[a] && i[a] < e && (o[a * e + i[a]] = n); return Dn(o, [t.size, e], "int32") }, Ih.prototype.nonMaxSuppression = function (t, e, n, r, o) { return wh(t, "nonMaxSuppression"), Bo(this.readSync(t.dataId), this.readSync(e.dataId), n, r, o) }, Ih.prototype.fft = function (t) { return this.fftBatch(t, !1) }, Ih.prototype.ifft = function (t) { return this.fftBatch(t, !0) }, Ih.prototype.fftBatch = function (t, e) { for (var n = t.shape[0], r = t.shape[1], o = cr(t.shape, "float32"), i = cr(t.shape, "float32"), a = En(t).as2D(n, r), s = _n(t).as2D(n, r), u = 0; u < n; u++)for (var c = a.slice([u, 0], [1, r]), l = s.slice([u, 0], [1, r]), h = Cn(c, l), f = this.readSync(this.fftImpl(h, e).dataId), p = 0; p < r; p++) { var d = Oo(f, p); o.values[u * r + p] = d.real, i.values[u * r + p] = d.imag } return Cn(o.toTensor(), i.toTensor()).as2D(n, r) }, Ih.prototype.fftImpl = function (t, e) { var n = t.as1D(), r = n.size; if (this.isExponentOf2(r)) { var o = this.fftRadix2(n, r, e).as2D(t.shape[0], t.shape[1]); return e && (o = Cn(En(o).div(kn(r)), _n(o).div(kn(r)))), o } var i = this.readSync(t.dataId), a = function (t) { for (var e = new Float32Array(t.length / 2), n = new Float32Array(t.length / 2), r = 0; r < t.length; r += 2)e[r / 2] = t[r], n[r / 2] = t[r + 1]; return { real: e, imag: n } }(this.fourierTransformByMatmul(i, r, e)); return Cn(a.real, a.imag).as2D(t.shape[0], t.shape[1]) }, Ih.prototype.isExponentOf2 = function (t) { return 0 == (t & t - 1) }, Ih.prototype.fftRadix2 = function (t, e, n) { if (1 === e) return t; var r = this.readSync(t.dataId), o = e / 2, i = function (t) { for (var e = Math.ceil(t.length / 4), n = new Float32Array(e), r = new Float32Array(e), o = 0; o < t.length; o += 4)n[Math.floor(o / 4)] = t[o], r[Math.floor(o / 4)] = t[o + 1]; return { real: n, imag: r } }(r), a = Cn(i.real, i.imag).as1D(), s = function (t) { for (var e = Math.floor(t.length / 4), n = new Float32Array(e), r = new Float32Array(e), o = 2; o < t.length; o += 4)n[Math.floor(o / 4)] = t[o], r[Math.floor(o / 4)] = t[o + 1]; return { real: n, imag: r } }(r), u = Cn(s.real, s.imag).as1D(); a = this.fftRadix2(a, o, n), u = this.fftRadix2(u, o, n); var c = function (t, e) { for (var n = new Float32Array(t / 2), r = new Float32Array(t / 2), o = 0; o < Math.ceil(t / 2); o++) { var i = (e ? 2 : -2) * Math.PI * (o / t); n[o] = Math.cos(i), r[o] = Math.sin(i) } return { real: n, imag: r } }(e, n), l = Cn(c.real, c.imag).mul(u), h = a.add(l), f = a.sub(l), p = En(h).concat(En(f)), d = _n(h).concat(_n(f)); return Cn(p, d).as1D() }, Ih.prototype.fourierTransformByMatmul = function (t, e, n) { for (var r = new Float32Array(2 * e), o = 0; o < e; o++) { for (var i = 0, a = 0, s = 0; s < e; s++) { var u = (d = o * s, v = e, m = (n ? 2 : -2) * Math.PI * (d / v), { real: Math.cos(m), imag: Math.sin(m) }), c = Oo(t, s); i += c.real * u.real - c.imag * u.imag, a += c.real * u.imag + c.imag * u.real } n && (i /= e, a /= e), h = i, f = a, (l = r)[2 * (p = o)] = h, l[2 * p + 1] = f } var l, h, f, p, d, v, m; return r }, Ih.prototype.depthToSpace = function (t, e, n) { P("NHWC" === n, function () { return "Only NHWC dataFormat supported on CPU for depthToSpace. Got " + n }), P(1 < e, function () { return "blockSize should be > 1 for depthToSpace, but was: " + e }); for (var r = t.shape[0], o = t.shape[1], i = t.shape[2], a = t.shape[3], s = o * e, u = i * e, c = a / (e * e), l = this.readSync(t.dataId), h = new Float32Array(r * s * u * c), f = 0, p = 0; p < r; ++p)for (var d = 0; d < s; ++d)for (var v = Math.floor(d / e), m = d % e, g = 0; g < u; ++g)for (var y = Math.floor(g / e), x = (m * e + g % e) * c, b = 0; b < c; ++b) { var w = b + x + a * (y + i * (v + o * p)); h[f++] = l[w] } return Tn(h, [r, s, u, c]) }, Ih.prototype.broadcastedBinaryOp = function (a, s, t, u) { var e = go(a.shape, s.shape), c = cr(e, t), l = this.readSync(a.dataId), h = this.readSync(s.dataId), f = vo(a.shape, e), p = vo(s.shape, e), d = c.values; if (f.length + p.length === 0) for (var n = 0; n < d.length; ++n)d[n] = u(l[n % l.length], h[n % h.length]); else { var v = this.bufferSync(a), m = this.bufferSync(s), r = function (t) { var e = c.indexToLoc(t), n = e.slice(-a.rank); f.forEach(function (t) { return n[t] = 0 }); var r = v.locToIndex(n), o = e.slice(-s.rank); p.forEach(function (t) { return o[t] = 0 }); var i = m.locToIndex(o); d[t] = u(l[r], h[i]) }; for (n = 0; n < d.length; ++n)r(n) } return c.toTensor() }, Ih.prototype.broadcastedBinaryComplexOp = function (s, u, c) { var t = go(s.shape, u.shape), l = cr(t, "float32"), e = cr(t, "float32"), h = this.readSync(s.dataId), f = this.readSync(u.dataId), p = vo(s.shape, t), d = vo(u.shape, t), v = l.values, m = e.values; if (p.length + d.length === 0) for (var n = 0; n < v.length; n++) { var r = n % h.length, o = n % f.length, i = c(h[2 * r], h[2 * r + 1], f[2 * o], f[2 * o + 1]); v[n] = i.real, m[n] = i.imag } else { var g = this.bufferSync(this.data.get(s.dataId).complexTensors.real), y = this.bufferSync(this.data.get(u.dataId).complexTensors.real), a = function (t) { var e = l.indexToLoc(t), n = e.slice(-s.rank); p.forEach(function (t) { return n[t] = 0 }); var r = g.locToIndex(n), o = e.slice(-u.rank); d.forEach(function (t) { return o[t] = 0 }); var i = y.locToIndex(o), a = c(h[2 * r], h[2 * r + 1], f[2 * i], f[2 * i + 1]); v[t] = a.real, m[t] = a.imag }; for (n = 0; n < v.length; n++)a(n) } return this.complex(l.toTensor(), e.toTensor()) }, Ih.prototype.split = function (t, e, n) { return Vo(t, e, n) }, Ih.prototype.dispose = function () { }, Ih.prototype.floatPrecision = function () { return 32 }, Ih.prototype.epsilon = function () { return 1e-7 }, Ih.prototype.cropAndResize = function (t, e, n, r, o, i) { for (var a = t.shape, s = a[0], u = a[1], c = a[2], l = a[3], h = e.shape[0], f = r[0], p = r[1], d = cr([h, f, p, l], "float32"), v = this.readSync(e.dataId), m = this.readSync(n.dataId), g = this.readSync(t.dataId), y = t.strides, x = d.strides, b = 0; b < h; b++) { var w = 4 * b, C = v[w], E = v[1 + w], _ = v[2 + w], I = v[3 + w], R = m[b]; if (!(s <= R)) for (var k = 1 < f ? (_ - C) * (u - 1) / (f - 1) : 0, S = 1 < p ? (I - E) * (c - 1) / (p - 1) : 0, D = 0; D < f; D++) { var A = 1 < f ? C * (u - 1) + D * k : .5 * (C + _) * (u - 1); if (A < 0 || u - 1 < A) for (var T = 0; T < p; T++)for (var N = 0; N < l; N++) { var F = N + T * x[2] + D * x[1] + b * x[0]; d.values[F] = i } else if ("bilinear" === o) { var M = Math.floor(A), O = Math.ceil(A), P = A - M; for (T = 0; T < p; T++)if ((q = 1 < p ? E * (c - 1) + T * S : .5 * (E + I) * (c - 1)) < 0 || c - 1 < q) for (N = 0; N < l; N++)F = N + T * x[2] + D * x[1] + b * x[0], d.values[F] = i; else { var B = Math.floor(q), L = Math.ceil(q), W = q - B; for (N = 0; N < l; N++) { var z = g[F = N + B * y[2] + M * y[1] + R * y[0]], U = g[F = N + L * y[2] + M * y[1] + R * y[0]], V = g[F = N + B * y[2] + O * y[1] + R * y[0]], G = z + (U - z) * W, H = V + (g[F = N + L * y[2] + O * y[1] + R * y[0]] - V) * W; F = N + T * x[2] + D * x[1] + b * x[0], d.values[F] = G + (H - G) * P } } } else for (T = 0; T < p; ++T) { var q; if ((q = 1 < p ? E * (c - 1) + T * S : .5 * (E + I) * (c - 1)) < 0 || c - 1 < q) for (N = 0; N < l; N++)F = N + T * x[2] + D * x[1] + b * x[0], d.values[F] = i; else { var j = Math.round(q), K = Math.round(A); for (N = 0; N < l; N++) { var X = N + j * y[2] + K * y[1] + R * y[0], Y = N + T * x[2] + D * x[1] + b * x[0]; d.values[Y] = g[X] } } } } } return d.toTensor() }, Ih.prototype.sparseToDense = function (t, e, n, r) { var o = Xr(0, t, n), i = o.sliceRank, a = o.numUpdates, s = o.sliceSize, u = o.strides, c = o.outputSize; return this.scatter(t, e, n, c, s, a, i, u, r, !1) }, Ih.prototype.gatherND = function (t, e) { var n = e.shape, r = n[n.length - 1], o = Gr(t, e), i = o[0], a = o[1], s = o[2], u = o[3]; if (0 === a) return In([], i, t.dtype); for (var c = new vt([a, s], t.dtype), l = this.readSync(e.dataId), h = this.readSync(t.dataId), f = 0; f < a; f++) { for (var p = [], d = 0, v = 0; v < r; v++) { var m = l[f * r + v]; d += m * u[v], p.push(m) } if (d < 0 || d >= t.size / s) throw new Error("Invalid indices: " + p + " does not index into " + t.shape); for (var g = 0; g < s; g++)c.values[f * s + g] = h[d * s + g] } return c.toTensor().reshape(i) }, Ih.prototype.scatterND = function (t, e, n) { var r = Xr(0, t, n), o = r.sliceRank, i = r.numUpdates, a = r.sliceSize, s = r.strides, u = r.outputSize, c = kn(0); return this.scatter(t, e, n, u, a, i, o, s, c, !0) }, Ih.prototype.fill = function (t, e, n) { var r = F(n = n || j(e), L(t)); return r.fill(e), Kt.makeTensor(r, t, n, this) }, Ih.prototype.onesLike = function (t) { if ("string" === t.dtype) throw new Error("onesLike is not supported for string tensors"); return this.fill(t.shape, 1, t.dtype) }, Ih.prototype.zerosLike = function (t) { var e = F(t.dtype, L(t.shape)); return this.makeOutput(e, t.shape, t.dtype) }, Ih.prototype.linspace = function (t, e, n) { return No(t, e, n) }, Ih.prototype.scatter = function (t, e, n, r, o, i, a, s, u, c) { var l = [r / o, o], h = this.readSync(t.dataId), f = this.readSync(e.dataId); if (0 === r) return In([], n, e.dtype); var p = new vt(l, e.dtype); p.values.fill(this.readSync(u.dataId)[0]); for (var d = 0; d < i; d++) { for (var v = [], m = 0, g = 0; g < a; g++) { var y = h[d * a + g]; v.push(y), m += y * s[g] } if (m < 0 || r / o <= m) throw new Error("Invalid indices: " + v + " does not index into " + n); for (var x = 0; x < o; x++)c ? p.values[m * o + x] += f[d * o + x] : p.values[m * o + x] = 0 === e.rank ? f[0] : f[d * o + x] } return p.toTensor().reshape(n) }, Ih); function Ih() { var t = Eh.call(this) || this; return t.blockSize = 48, t.firstUse = !0, t.data = new co(t, Kt), t } Kt.registerBackend("cpu", function () { return new _h }, 1); for (var Rh = 0, kh = [{ kernelName: "NonMaxSuppressionV5", backendName: "cpu", kernelFunc: function (t) { var e = t.inputs, n = t.backend, r = t.attrs, o = e, i = o.boxes, a = o.scores, s = r, u = s.maxOutputSize, c = s.iouThreshold, l = s.scoreThreshold, h = s.softNmsSigma, f = n; wh(i, "NonMaxSuppressionWithScore"); var p = Lo(f.data.get(i.dataId).values, f.data.get(a.dataId).values, u, c, l, h); return [p.selectedIndices, p.selectedScores] } }, { kernelName: "Square", backendName: "cpu", kernelFunc: function (t) { var e = t.inputs, n = t.backend, r = e.x, o = n; wh(r, "square"); for (var i = o.data.get(r.dataId).values, a = new Float32Array(i.length), s = 0; s < i.length; ++s) { var u = i[s]; a[s] = u * u } return { dataId: o.write(a, r.shape, r.dtype), shape: r.shape, dtype: r.dtype } } }, { kernelName: Fs, backendName: "cpu", kernelFunc: function (t) { var e = t.inputs, n = t.backend, r = e, o = r.a, i = r.b, a = n; wh([o, i], Fs); var s = a.data.get(o.dataId).values, u = a.data.get(i.dataId).values, c = function (t, e, a, s, n, u) { var r = go(t, e), c = r.length, l = Y(r), h = N(n, L(r)), f = t.length, p = e.length, d = Y(t), v = Y(e), m = vo(t, r), g = vo(e, r); if (m.length + g.length === 0) for (var o = 0; o < h.length; ++o)h[o] = u(a[o % a.length], s[o % s.length]); else { var i = function (t) { var e = it(t, c, l), n = e.slice(-f); m.forEach(function (t) { return n[t] = 0 }); var r = ot(n, f, d), o = e.slice(-p); g.forEach(function (t) { return o[t] = 0 }); var i = ot(o, p, v); h[t] = u(a[r], s[i]) }; for (o = 0; o < h.length; ++o)i(o) } return [h, r] }(o.shape, i.shape, s, u, o.dtype, function (t, e) { var n = t - e; return n * n }), l = c[0], h = c[1]; return { dataId: a.write(l, h, o.dtype), shape: h, dtype: o.dtype } } }]; Rh < kh.length; Rh++)s(kh[Rh]); for (var Sh, Dh = function (t) { this.variableNames = ["A"]; var e = Jo(), n = t[0], r = t[1]; this.outputShape = t, this.userCode = "\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(" + r + ".0, " + n + ".0);\n\n        vec4 values = " + e.texture2D + "(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    " }, Ah = function (t) { this.variableNames = ["A"], this.packedInputs = !1, this.packedOutput = !0; var e = Jo(), n = t[0], r = t[1]; this.outputShape = t, this.userCode = "\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) /\n                       vec2(" + r + ".0, " + n + ".0);\n            vec4 values = " + e.texture2D + "(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        " + e.output + " = result;\n      }\n    " }, Th = 0, Nh = [{ kernelName: "FromPixels", backendName: "webgl", kernelFunc: function (t) { var e = t.inputs, n = t.backend, r = t.attrs, o = e.pixels, i = r.numChannels, a = "undefined" != typeof HTMLVideoElement && o instanceof HTMLVideoElement, s = "undefined" != typeof HTMLImageElement && o instanceof HTMLImageElement, u = a ? [o.videoWidth, o.videoHeight] : [o.width, o.height], c = u[0], l = u[1], h = [l, c], f = [l, c, i]; (s || a) && (null == Sh && (Sh = document.createElement("canvas").getContext("2d")), Sh.canvas.width = c, Sh.canvas.height = l, Sh.drawImage(o, 0, 0, c, l), o = Sh.canvas); var p = n.makeTensorInfo(h, "int32"); n.texData.get(p.dataId).usage = Jt.PIXELS, n.gpgpu.uploadPixelDataToTexture(n.getTexture(p.dataId), o); var d = _().getBool("WEBGL_PACK") ? new Ah(f) : new Dh(f), v = n.runWebGLProgram(d, [p], "int32"); return n.disposeData(p.dataId), v } }, { kernelName: "NonMaxSuppressionV5", backendName: "webgl", kernelFunc: function (t) { var e = t.inputs, n = t.backend, r = t.attrs; an("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead"); var o = e, i = o.boxes, a = o.scores, s = r, u = s.maxOutputSize, c = s.iouThreshold, l = s.scoreThreshold, h = s.softNmsSigma, f = n, p = Lo(f.readSync(i.dataId), f.readSync(a.dataId), u, c, l, h); return [p.selectedIndices, p.selectedScores] } }, { kernelName: "Square", backendName: "webgl", kernelFunc: function (t) { var e = t.inputs, n = t.backend, r = e.x, o = n, i = new us(r.shape, "return x * x;"); return o.runWebGLProgram(i, [r], r.dtype) } }, { kernelName: Fs, backendName: "webgl", kernelFunc: function (t) { var e = t.inputs, n = t.backend, r = e, o = r.a, i = r.b, a = n, s = _().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new di("return (a - b) * (a - b);", o.shape, i.shape) : new pi("return (a - b) * (a - b);", o.shape, i.shape); return a.compileAndRun(s, [o, i]) } }]; Th < Nh.length; Th++)s(Nh[Th]); for (var Fh = 0, Mh = [{ kernelName: "Square", gradFunc: function (t, e) { var n = e[0]; return { x: function () { return t.mul(n.toFloat().mul(2)) } } } }, { kernelName: Fs, gradFunc: function (t, e) { var n = e[0], r = e[1], o = kn(2); return { a: function () { return Yu(t, Yu(o, tc(n, r))) }, b: function () { return Yu(t, Yu(o, tc(r, n))) } } } }]; Fh < Mh.length; Fh++)h(Mh[Fh]); var Oh = (Ph.prototype.fetch = function (t, e) { return fetch(t, e) }, Ph.prototype.now = function () { return performance.now() }, Ph.prototype.encode = function (t, e) { if ("utf-8" !== e && "utf8" !== e) throw new Error("Browser's encoder only supports utf-8, but got " + e); return null == this.textEncoder && (this.textEncoder = new TextEncoder), this.textEncoder.encode(t) }, Ph.prototype.decode = function (t, e) { return new TextDecoder(e).decode(t) }, Ph); function Ph() { } _().get("IS_BROWSER") && _().setPlatform("browser", new Oh); var Bh, Lh = (Wh.prototype.fetch = function (t, e) { return null != _().global.fetch ? _().global.fetch(t, e) : (null == Bh && (Bh = require("node-fetch")), Bh(t, e)) }, Wh.prototype.now = function () { var t = process.hrtime(); return 1e3 * t[0] + t[1] / 1e6 }, Wh.prototype.encode = function (t, e) { if ("utf-8" !== e && "utf8" !== e) throw new Error("Node built-in encoder only supports utf-8, but got " + e); return this.textEncoder.encode(t) }, Wh.prototype.decode = function (t, e) { return 0 === t.length ? "" : new this.util.TextDecoder(e).decode(t) }, Wh); function Wh() { this.util = require("util"), this.textEncoder = new this.util.TextEncoder } _().get("IS_NODE") && _().setPlatform("node", new Lh); var zh = { float32: 4, int32: 4, uint16: 2, uint8: 1, bool: 1 }, Uh = 4; function Vh(v, t) { for (var m = {}, g = 0, e = function (t) { var e = t.name, n = t.dtype, r = t.shape, o = L(r), i = void 0; if ("quantization" in t) { var a = t.quantization; if ("uint8" !== a.dtype && "uint16" !== a.dtype) throw new Error("Weight " + t.name + " has unknown quantization dtype " + a.dtype + ". Supported quantization dtypes are: 'uint8' and 'uint16'."); var s = zh[a.dtype], u = v.slice(g, g + o * s), c = "uint8" === a.dtype ? new Uint8Array(u) : new Uint16Array(u); if ("float32" === n) i = Float32Array.from(c, function (t) { return t * a.scale + a.min }); else { if ("int32" !== n) throw new Error("Unsupported dtype in weight '" + e + "': " + n); i = Int32Array.from(c, function (t) { return Math.round(t * a.scale + a.min) }) } g += o * s } else if ("string" === n) { var l = L(t.shape); i = []; for (var h = 0; h < l; h++) { var f = new Uint32Array(v.slice(g, g + Uh))[0]; g += Uh; var p = new Uint8Array(v.slice(g, g + f)); i.push(p), g += f } } else { var d = zh[n]; if (u = v.slice(g, g + o * d), "float32" === n) i = new Float32Array(u); else if ("int32" === n) i = new Int32Array(u); else { if ("bool" !== n) throw new Error("Unsupported dtype in weight '" + e + "': " + n); i = new Uint8Array(u) } g += o * d } m[e] = In(i, r, n) }, n = 0, r = t; n < r.length; n++)e(r[n]); return m } var Gh = "undefined" != typeof Buffer && ("undefined" == typeof Blob || "undefined" == typeof atob || "undefined" == typeof btoa); function Hh(t) { return Gh ? Buffer.byteLength(t) : new Blob([t]).size } function qh(t) { var e = 0; t.forEach(function (t) { e += t.byteLength }); var n = new Uint8Array(e), r = 0; return t.forEach(function (t) { n.set(new Uint8Array(t), r), r += t.byteLength }), n.buffer } function jh(t) { for (t = t.trim(); t.endsWith("/");)t = t.slice(0, t.length - 1); var e = t.split("/"); return e[e.length - 1] } function Kh(t) { if (t.modelTopology instanceof ArrayBuffer) throw new Error("Expected JSON model topology, received ArrayBuffer."); return { dateSaved: new Date, modelTopologyType: "JSON", modelTopologyBytes: null == t.modelTopology ? 0 : Hh(JSON.stringify(t.modelTopology)), weightSpecsBytes: null == t.weightSpecs ? 0 : Hh(JSON.stringify(t.weightSpecs)), weightDataBytes: null == t.weightData ? 0 : t.weightData.byteLength } } var Xh = (Qh.getInstance = function () { return null == Qh.instance && (Qh.instance = new Qh), Qh.instance }, Qh.registerSaveRouter = function (t) { Qh.getInstance().saveRouters.push(t) }, Qh.registerLoadRouter = function (t) { Qh.getInstance().loadRouters.push(t) }, Qh.getSaveHandlers = function (t) { return Qh.getHandlers(t, "save") }, Qh.getLoadHandlers = function (t, e) { return Qh.getHandlers(t, "load", e) }, Qh.getHandlers = function (n, t, r) { var o = []; return ("load" === t ? Qh.getInstance().loadRouters : Qh.getInstance().saveRouters).forEach(function (t) { var e = t(n, r); null !== e && o.push(e) }), o }, Qh), Yh = "://", $h = (Jh.getInstance = function () { return null == Jh.instance && (Jh.instance = new Jh), Jh.instance }, Jh.registerManager = function (t, e) { P(null != t, function () { return "scheme must not be undefined or null." }), t.endsWith(Yh) && (t = t.slice(0, t.indexOf(Yh))), P(0 < t.length, function () { return "scheme must not be an empty string." }); var n = Jh.getInstance(); P(null == n.managers[t], function () { return "A model store manager is already registered for scheme '" + t + "'." }), n.managers[t] = e }, Jh.getManager = function (t) { var e = this.getInstance().managers[t]; if (null == e) throw new Error("Cannot find model manager for scheme '" + t + "'"); return e }, Jh.getSchemes = function () { return Object.keys(this.getInstance().managers) }, Jh); function Jh() { this.managers = {} } function Qh() { this.saveRouters = [], this.loadRouters = [] } function Zh(t) { if (-1 === t.indexOf(Yh)) throw new Error("The url string provided does not contain a scheme. Supported schemes are: " + $h.getSchemes().join(",")); return { scheme: t.split(Yh)[0], path: t.split(Yh)[1] } } function tf(l, h, f) { return void 0 === f && (f = !1), y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c; return R(this, function (t) { switch (t.label) { case 0: return P(l !== h, function () { return "Old path and new path are the same: '" + l + "'" }), P(0 < (e = Xh.getLoadHandlers(l)).length, function () { return "Copying failed because no load handler is found for source URL " + l + "." }), P(e.length < 2, function () { return "Copying failed because more than one (" + e.length + ") load handlers for source URL " + l + "." }), n = e[0], P(0 < (r = Xh.getSaveHandlers(h)).length, function () { return "Copying failed because no save handler is found for destination URL " + h + "." }), P(r.length < 2, function () { return "Copying failed because more than one (" + e.length + ") save handlers for destination URL " + h + "." }), o = r[0], i = Zh(l).scheme, a = Zh(l).path, s = i === Zh(l).scheme, [4, n.load()]; case 1: return u = t.sent(), f && s ? [4, $h.getManager(i).removeModel(a)] : [3, 3]; case 2: t.sent(), t.label = 3; case 3: return [4, o.save(u)]; case 4: return c = t.sent(), !f || s ? [3, 6] : [4, $h.getManager(i).removeModel(a)]; case 5: t.sent(), t.label = 6; case 6: return [2, c.modelArtifactsInfo] } }) }) } var ef = "models_store", nf = "model_info_store"; function rf() { if (!_().getBool("IS_BROWSER")) throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser."); var t = window || self, e = t.indexedDB || t.mozIndexedDB || t.webkitIndexedDB || t.msIndexedDB || t.shimIndexedDB; if (null == e) throw new Error("The current browser does not appear to support IndexedDB."); return e } function of(t) { var e = t.result; e.createObjectStore(ef, { keyPath: "modelPath" }), e.createObjectStore(nf, { keyPath: "modelPath" }) } function af(t) { return _().getBool("IS_BROWSER") && !Array.isArray(t) && t.startsWith(sf.URL_SCHEME) ? (e = t.slice(sf.URL_SCHEME.length), new sf(e)) : null; var e } var sf = (uf.prototype.save = function (e) { return y(this, void 0, void 0, function () { return R(this, function (t) { if (e.modelTopology instanceof ArrayBuffer) throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet."); return [2, this.databaseAction(this.modelPath, e)] }) }) }, uf.prototype.load = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { return [2, this.databaseAction(this.modelPath)] }) }) }, uf.prototype.databaseAction = function (t, h) { var f = this; return new Promise(function (u, c) { var l = f.indexedDB.open("tensorflowjs", 1); l.onupgradeneeded = function () { return of(l) }, l.onsuccess = function () { var r = l.result; if (null == h) { var t = r.transaction(ef, "readonly"), e = t.objectStore(ef).get(f.modelPath); e.onsuccess = function () { if (null == e.result) return r.close(), c(new Error("Cannot find model with path '" + f.modelPath + "' in IndexedDB.")); u(e.result.modelArtifacts) }, e.onerror = function (t) { return r.close(), c(e.error) }, t.oncomplete = function () { return r.close() } } else { var o, i = Kh(h), a = r.transaction(nf, "readwrite"), s = a.objectStore(nf), n = s.put({ modelPath: f.modelPath, modelArtifactsInfo: i }); n.onsuccess = function () { var n = (o = r.transaction(ef, "readwrite")).objectStore(ef).put({ modelPath: f.modelPath, modelArtifacts: h, modelArtifactsInfo: i }); n.onsuccess = function () { return u({ modelArtifactsInfo: i }) }, n.onerror = function (t) { var e = (s = a.objectStore(nf)).delete(f.modelPath); e.onsuccess = function () { return r.close(), c(n.error) }, e.onerror = function (t) { return r.close(), c(n.error) } } }, n.onerror = function (t) { return r.close(), c(n.error) }, a.oncomplete = function () { null == o ? r.close() : o.oncomplete = function () { return r.close() } } } }, l.onerror = function (t) { return c(l.error) } }) }, uf.URL_SCHEME = "indexeddb://", uf); function uf(t) { if (this.indexedDB = rf(), null == t || !t) throw new Error("For IndexedDB, modelPath must not be null, undefined or empty."); this.modelPath = t } Xh.registerSaveRouter(af), Xh.registerLoadRouter(af); var cf = (lf.prototype.listModels = function () { return y(this, void 0, void 0, function () { var e = this; return R(this, function (t) { return [2, new Promise(function (i, n) { var r = e.indexedDB.open("tensorflowjs", 1); r.onupgradeneeded = function () { return of(r) }, r.onsuccess = function () { var e = r.result, t = e.transaction(nf, "readonly"), o = t.objectStore(nf).getAll(); o.onsuccess = function () { for (var t = {}, e = 0, n = o.result; e < n.length; e++) { var r = n[e]; t[r.modelPath] = r.modelArtifactsInfo } i(t) }, o.onerror = function (t) { return e.close(), n(o.error) }, t.oncomplete = function () { return e.close() } }, r.onerror = function (t) { return n(r.error) } })] }) }) }, lf.prototype.removeModel = function (u) { return y(this, void 0, void 0, function () { var n = this; return R(this, function (t) { var e; return u = (e = u).startsWith(sf.URL_SCHEME) ? e.slice(sf.URL_SCHEME.length) : e, [2, new Promise(function (a, s) { var e = n.indexedDB.open("tensorflowjs", 1); e.onupgradeneeded = function () { return of(e) }, e.onsuccess = function () { var n, r = e.result, t = r.transaction(nf, "readwrite"), o = t.objectStore(nf), i = o.get(u); i.onsuccess = function () { if (null == i.result) return r.close(), s(new Error("Cannot find model with path '" + u + "' in IndexedDB.")); function e() { var t = (n = r.transaction(ef, "readwrite")).objectStore(ef).delete(u); t.onsuccess = function () { return a(i.result.modelArtifactsInfo) }, t.onerror = function (t) { return s(i.error) } } var t = o.delete(u); t.onsuccess = e, t.onerror = function (t) { return e(), r.close(), s(i.error) } }, i.onerror = function (t) { return r.close(), s(i.error) }, t.oncomplete = function () { null == n ? r.close() : n.oncomplete = function () { return r.close() } } }, e.onerror = function (t) { return s(e.error) } })] }) }) }, lf); function lf() { this.indexedDB = rf() } if (_().getBool("IS_BROWSER")) try { $h.registerManager(sf.URL_SCHEME, new cf) } catch (r) { } var hf = "/", ff = "tensorflowjs_models", pf = "info", df = "model_topology", vf = "weight_specs", mf = "weight_data", gf = "model_metadata"; function yf(t) { return { info: [ff, t, pf].join(hf), topology: [ff, t, df].join(hf), weightSpecs: [ff, t, vf].join(hf), weightData: [ff, t, mf].join(hf), modelMetadata: [ff, t, gf].join(hf) } } function xf(t) { var e = t.split(hf); if (e.length < 3) throw new Error("Invalid key format: " + t); return e.slice(1, e.length - 1).join(hf) } function bf(t) { return _().getBool("IS_BROWSER") && !Array.isArray(t) && t.startsWith(wf.URL_SCHEME) ? (e = t.slice(wf.URL_SCHEME.length), new wf(e)) : null; var e } var wf = (Cf.prototype.save = function (o) { return y(this, void 0, void 0, function () { var e, n, r; return R(this, function (t) { if (o.modelTopology instanceof ArrayBuffer) throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet."); e = JSON.stringify(o.modelTopology), n = JSON.stringify(o.weightSpecs), r = Kh(o); try { return this.LS.setItem(this.keys.info, JSON.stringify(r)), this.LS.setItem(this.keys.topology, e), this.LS.setItem(this.keys.weightSpecs, n), this.LS.setItem(this.keys.weightData, function (t) { if (Gh) return Buffer.from(t).toString("base64"); for (var e = new Uint8Array(t), n = "", r = 0, o = e.length; r < o; r++)n += String.fromCharCode(e[r]); return btoa(n) }(o.weightData)), this.LS.setItem(this.keys.modelMetadata, JSON.stringify({ format: o.format, generatedBy: o.generatedBy, convertedBy: o.convertedBy, userDefinedMetadata: o.userDefinedMetadata })), [2, { modelArtifactsInfo: r }] } catch (t) { throw this.LS.removeItem(this.keys.info), this.LS.removeItem(this.keys.topology), this.LS.removeItem(this.keys.weightSpecs), this.LS.removeItem(this.keys.weightData), this.LS.removeItem(this.keys.modelMetadata), new Error("Failed to save model '" + this.modelPath + "' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=" + r.modelTopologyBytes + ", weightSpecsBytes=" + r.weightSpecsBytes + ", weightDataBytes=" + r.weightDataBytes + ".") } return [2] }) }) }, Cf.prototype.load = function () { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s; return R(this, function (t) { if (null == (e = JSON.parse(this.LS.getItem(this.keys.info)))) throw new Error("In local storage, there is no model with name '" + this.modelPath + "'"); if ("JSON" !== e.modelTopologyType) throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet."); if (n = {}, null == (r = JSON.parse(this.LS.getItem(this.keys.topology)))) throw new Error("In local storage, the topology of model '" + this.modelPath + "' is missing."); if (n.modelTopology = r, null == (o = JSON.parse(this.LS.getItem(this.keys.weightSpecs)))) throw new Error("In local storage, the weight specs of model '" + this.modelPath + "' are missing."); if (n.weightSpecs = o, null != (i = this.LS.getItem(this.keys.modelMetadata)) && (a = JSON.parse(i), n.format = a.format, n.generatedBy = a.generatedBy, n.convertedBy = a.convertedBy, n.userDefinedMetadata = a.userDefinedMetadata), null == (s = this.LS.getItem(this.keys.weightData))) throw new Error("In local storage, the binary weight values of model '" + this.modelPath + "' are missing."); return n.weightData = function (t) { if (Gh) { var e = Buffer.from(t, "base64"); return e.buffer.slice(e.byteOffset, e.byteOffset + e.byteLength) } for (var n = atob(t), r = new Uint8Array(n.length), o = 0; o < n.length; ++o)r.set([n.charCodeAt(o)], o); return r.buffer }(s), [2, n] }) }) }, Cf.URL_SCHEME = "localstorage://", Cf); function Cf(t) { if (!_().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 == t || !t) throw new Error("For local storage, modelPath must not be null, undefined or empty."); this.modelPath = t, this.keys = yf(this.modelPath) } Xh.registerSaveRouter(bf), Xh.registerLoadRouter(bf); var Ef = (_f.prototype.listModels = function () { return y(this, void 0, void 0, function () { var e, n, r, o, i, a; return R(this, function (t) { for (e = {}, n = ff + hf, r = hf + pf, o = 0; o < this.LS.length; ++o)(i = this.LS.key(o)).startsWith(n) && i.endsWith(r) && (a = xf(i), e[a] = JSON.parse(this.LS.getItem(i))); return [2, e] }) }) }, _f.prototype.removeModel = function (o) { return y(this, void 0, void 0, function () { var n, r; return R(this, function (t) { var e; if (o = (e = o).startsWith(wf.URL_SCHEME) ? e.slice(wf.URL_SCHEME.length) : e, n = yf(o), null == this.LS.getItem(n.info)) throw new Error("Cannot find model at path '" + o + "'"); return r = JSON.parse(this.LS.getItem(n.info)), this.LS.removeItem(n.info), this.LS.removeItem(n.topology), this.LS.removeItem(n.weightSpecs), this.LS.removeItem(n.weightData), [2, r] }) }) }, _f); function _f() { P(_().getBool("IS_BROWSER"), function () { return "Current environment is not a web browser" }), P("undefined" == typeof window || void 0 !== window.localStorage, function () { return "Current browser does not appear to support localStorage" }), this.LS = window.localStorage } if (_().getBool("IS_BROWSER")) try { $h.registerManager(wf.URL_SCHEME, new Ef) } catch (r) { } function If(t) { return new Promise(function (t) { return setTimeout(t) }).then(t) } var Rf = (Df.prototype.save = function (s) { return y(this, void 0, void 0, function () { var e, n, r, o, i, a; return R(this, function (t) { switch (t.label) { case 0: if ("undefined" == typeof document) throw new Error("Browser downloads are not supported in this environment since `document` is not present"); if (e = window.URL.createObjectURL(new Blob([s.weightData], { type: "application/octet-stream" })), !(s.modelTopology instanceof ArrayBuffer)) return [3, 1]; throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet."); case 1: return n = [{ paths: ["./" + this.weightDataFileName], weights: s.weightSpecs }], r = { modelTopology: s.modelTopology, format: s.format, generatedBy: s.generatedBy, convertedBy: s.convertedBy, weightsManifest: n }, o = window.URL.createObjectURL(new Blob([JSON.stringify(r)], { type: "application/json" })), (i = null == this.jsonAnchor ? document.createElement("a") : this.jsonAnchor).download = this.modelTopologyFileName, i.href = o, [4, If(function () { return i.dispatchEvent(new MouseEvent("click")) })]; case 2: return t.sent(), null == s.weightData ? [3, 4] : ((a = null == this.weightDataAnchor ? document.createElement("a") : this.weightDataAnchor).download = this.weightDataFileName, a.href = e, [4, If(function () { return a.dispatchEvent(new MouseEvent("click")) })]); case 3: t.sent(), t.label = 4; case 4: return [2, { modelArtifactsInfo: Kh(s) }] } }) }) }, Df.URL_SCHEME = "downloads://", Df), kf = (Sf.prototype.load = function () { return y(this, void 0, void 0, function () { var r, h, f = this; return R(this, function (t) { return r = this.files[0], h = this.files.slice(1), [2, new Promise(function (c, l) { var t = new FileReader; t.onload = function (t) { var o = JSON.parse(t.target.result), i = o.modelTopology; if (null != i) { 0 === h.length && c({ modelTopology: i }); var e = o.weightsManifest; if (null != e) { var n; try { n = f.checkManifestAndWeightFiles(e, h) } catch (t) { return void l(t) } var a = [], s = [], u = []; e.forEach(function (t) { t.paths.forEach(function (t) { s.push(t), u.push(null) }), a.push.apply(a, t.weights) }), e.forEach(function (t) { t.paths.forEach(function (r) { var t = new FileReader; t.onload = function (t) { var e = t.target.result, n = s.indexOf(r); u[n] = e, -1 === u.indexOf(null) && c({ modelTopology: i, weightSpecs: a, weightData: qh(u), format: o.format, generatedBy: o.generatedBy, convertedBy: o.convertedBy, userDefinedMetadata: o.userDefinedMetadata }) }, t.onerror = function (t) { return l("Failed to weights data from file of path '" + r + "'.") }, t.readAsArrayBuffer(n[r]) }) }) } else l(new Error("weightManifest field is missing from file " + r.name)) } else l(new Error("modelTopology field is missing from file " + r.name)) }, t.onerror = function (t) { return l("Failed to read model topology and weights manifest JSON from file '" + r.name + "'. BrowserFiles supports loading Keras-style tf.Model artifacts only.") }, t.readAsText(r) })] }) }) }, Sf.prototype.checkManifestAndWeightFiles = function (t, n) { for (var r = [], o = n.map(function (t) { return jh(t.name) }), i = {}, e = 0, a = t; e < a.length; e++)a[e].paths.forEach(function (t) { var e = jh(t); if (-1 !== r.indexOf(e)) throw new Error("Duplicate file basename found in weights manifest: '" + e + "'"); if (r.push(e), -1 === o.indexOf(e)) throw new Error("Weight file with basename '" + e + "' is not provided."); i[t] = n[o.indexOf(e)] }); if (r.length !== n.length) throw new Error("Mismatch in the number of files in weights manifest (" + r.length + ") and the number of weight files provided (" + n.length + ")."); return i }, Sf); function Sf(t) { if (null == t || t.length < 1) throw new Error("When calling browserFiles, at least 1 file is required, but received " + t); this.files = t } function Df(t) { if (!_().getBool("IS_BROWSER")) throw new Error("browserDownloads() cannot proceed because the current environment is not a browser."); t.startsWith(Df.URL_SCHEME) && (t = t.slice(Df.URL_SCHEME.length)), null != t && 0 !== t.length || (t = "model"), this.modelTopologyFileName = t + ".json", this.weightDataFileName = t + ".weights.bin" } function Af(n, r, o, i) { var t, e, a; P(null != (a = n) && Array.isArray(a) && 0 < a.length, function () { return "promises must be a none empty array" }), t = o = null == o ? 0 : o, e = i = null == i ? 1 : i, P(0 <= t && t <= 1, function () { return "Progress fraction must be in range [0, 1], but got startFraction " + t }), P(0 <= e && e <= 1, function () { return "Progress fraction must be in range [0, 1], but got endFraction " + e }), P(t <= e, function () { return "startFraction must be no more than endFraction, but got startFraction " + t + " and endFraction " + e }); var s = 0; return Promise.all(n.map(function (t) { return t.then(function (t) { var e = o + ++s / n.length * (i - o); return r(e), t }), t })) } function Tf(l, h) { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c; return R(this, function (t) { switch (t.label) { case 0: return null == h && (h = {}), e = null == h.fetchFunc ? _().platform.fetch : h.fetchFunc, n = l.map(function (t) { return e(t, h.requestInit, { isBinary: !0 }) }), r = 0, o = .5, null != h.onProgress ? [3, 2] : [4, Promise.all(n)]; case 1: return i = t.sent(), [3, 4]; case 2: return [4, Af(n, h.onProgress, r, o)]; case 3: i = t.sent(), t.label = 4; case 4: return a = i.map(function (t) { return t.arrayBuffer() }), s = .5, u = 1, null != h.onProgress ? [3, 6] : [4, Promise.all(a)]; case 5: return c = t.sent(), [3, 8]; case 6: return [4, Af(a, h.onProgress, s, u)]; case 7: c = t.sent(), t.label = 8; case 8: return [2, c] } }) }) } function Nf(i) { var t = this; return function (p, o, d) { return void 0 === o && (o = ""), y(t, void 0, void 0, function () { var a, c, s, u, e, n, r, l, h, f; return R(this, function (t) { switch (t.label) { case 0: if (a = p.map(function () { return !1 }), c = {}, s = null != d ? d.map(function () { return !1 }) : [], u = [], p.forEach(function (t, o) { var i = 0; t.weights.forEach(function (n) { function r() { a[o] = !0, null == c[o] && (c[o] = []), c[o].push({ manifestEntry: n, groupOffset: i, sizeBytes: e }) } var t = "quantization" in n ? n.quantization.dtype : n.dtype, e = zh[t] * L(n.shape); null != d ? d.forEach(function (t, e) { t === n.name && (r(), s[e] = !0) }) : r(), u.push(n.name), i += e }) }), !s.every(function (t) { return t })) throw e = d.filter(function (t, e) { return !s[e] }), new Error("Could not find weights in manifest with names: " + e.join(", ") + ". \nManifest JSON has weights with names: " + u.join(", ") + "."); return n = a.reduce(function (t, e, n) { return e && t.push(n), t }, []), r = [], n.forEach(function (t) { p[t].paths.forEach(function (t) { var e = o + (o.endsWith("/") ? "" : "/") + t; r.push(e) }) }), [4, i(r)]; case 1: return l = t.sent(), h = {}, f = 0, n.forEach(function (t) { for (var e = p[t].paths.length, n = 0, r = 0; r < e; r++)n += l[f + r].byteLength; for (var o = new ArrayBuffer(n), i = new Uint8Array(o), a = 0, s = 0; s < e; s++) { var u = new Uint8Array(l[f + s]); i.set(u, a), a += u.byteLength } c[t].forEach(function (t) { var e = Vh(o.slice(t.groupOffset, t.groupOffset + t.sizeBytes), [t.manifestEntry]); for (var n in e) h[n] = e[n] }), f += e }), [2, h] } }) }) } } Xh.registerSaveRouter(function (t) { return _().getBool("IS_BROWSER") && !Array.isArray(t) && t.startsWith(Rf.URL_SCHEME) ? (void 0 === (e = t.slice(Rf.URL_SCHEME.length)) && (e = "model"), new Rf(e)) : null; var e }); var Ff = (Mf.prototype.save = function (i) { return y(this, void 0, void 0, function () { var e, n, r, o; return R(this, function (t) { switch (t.label) { case 0: if (i.modelTopology instanceof ArrayBuffer) throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet."); return (e = Object.assign({ method: this.DEFAULT_METHOD }, this.requestInit)).body = new FormData, n = [{ paths: ["./model.weights.bin"], weights: i.weightSpecs }], r = { modelTopology: i.modelTopology, format: i.format, generatedBy: i.generatedBy, convertedBy: i.convertedBy, userDefinedMetadata: i.userDefinedMetadata, weightsManifest: n }, e.body.append("model.json", new Blob([JSON.stringify(r)], { type: "application/json" }), "model.json"), null != i.weightData && e.body.append("model.weights.bin", new Blob([i.weightData], { type: "application/octet-stream" }), "model.weights.bin"), [4, this.fetch(this.path, e)]; case 1: if ((o = t.sent()).ok) return [2, { modelArtifactsInfo: Kh(i), responses: [o] }]; throw new Error("BrowserHTTPRequest.save() failed due to HTTP response status " + o.status + ".") } }) }) }, Mf.prototype.load = function () { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f; return R(this, function (t) { switch (t.label) { case 0: return [4, this.fetch(this.path, this.requestInit)]; case 1: if (!(e = t.sent()).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."); t.label = 2; case 2: return t.trys.push([2, 4, , 5]), [4, e.json()]; case 3: return n = t.sent(), [3, 5]; case 4: throw t.sent(), r = "Failed to parse model JSON of response from " + this.path + ".", this.path.endsWith(".pb") ? r += " 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." : r += " Please make sure the server is serving valid JSON for this request.", new Error(r); case 5: if (o = n.modelTopology, i = n.weightsManifest, a = n.generatedBy, s = n.convertedBy, u = n.format, c = n.userDefinedMetadata, null == o && null == i) throw new Error("The JSON from HTTP path " + this.path + " contains neither model topology or manifest for weights."); return null == i ? [3, 7] : [4, this.loadWeights(i)]; case 6: f = t.sent(), l = f[0], h = f[1], t.label = 7; case 7: return [2, { modelTopology: o, weightSpecs: l, weightData: h, userDefinedMetadata: c, generatedBy: a, convertedBy: s, format: u }] } }) }) }, Mf.prototype.loadWeights = function (v) { return y(this, void 0, void 0, function () { var o, i, a, s, u, c, l, h, f, p, d; return R(this, function (t) { switch (t.label) { case 0: for (o = Array.isArray(this.path) ? this.path[1] : this.path, n = (e = o).lastIndexOf("/"), r = e.lastIndexOf("?"), i = [e.substring(0, n) + "/", n < r ? e.substring(r) : ""], a = i[0], s = i[1], u = this.weightPathPrefix || a, c = [], l = 0, h = v; l < h.length; l++)f = h[l], c.push.apply(c, f.weights); return p = [], v.forEach(function (t) { t.paths.forEach(function (t) { p.push(u + t + s) }) }), [4, Tf(p, { requestInit: this.requestInit, fetchFunc: this.fetch, onProgress: this.onProgress })]; case 1: return d = t.sent(), [2, [c, qh(d)]] }var e, n, r }) }) }, Mf.URL_SCHEME_REGEX = /^https?:\/\//, Mf); function Mf(t, e) { if (this.DEFAULT_METHOD = "POST", null == e && (e = {}), this.weightPathPrefix = e.weightPathPrefix, this.onProgress = e.onProgress, null != e.fetchFunc ? (P("function" == typeof e.fetchFunc, function () { return "Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)" }), this.fetch = e.fetchFunc) : this.fetch = _().platform.fetch, P(null != t && 0 < t.length, function () { return "URL path for http must not be null, undefined or empty." }), Array.isArray(t) && P(2 === t.length, function () { return "URL paths for http must have a length of 2, (actual length is " + t.length + ")." }), this.path = t, null != e.requestInit && null != e.requestInit.body) throw new Error("requestInit is expected to have no pre-existing body, but has one."); this.requestInit = e.requestInit || {} } function Of(t) { return null != t.match(Ff.URL_SCHEME_REGEX) } function Pf(t, e) { return "undefined" == typeof fetch ? null : (Array.isArray(t) ? t.every(function (t) { return Of(t) }) : Of(t)) ? Bf(t, { onProgress: e }) : null } function Bf(t, e) { return new Ff(t, e) } Xh.registerSaveRouter(Pf), Xh.registerLoadRouter(Pf); var Lf = (Uf.prototype.load = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { return [2, this.modelArtifacts] }) }) }, Uf), Wf = (zf.prototype.save = function (e) { return y(this, void 0, void 0, function () { return R(this, function (t) { return [2, this.saveHandler(e)] }) }) }, zf); function zf(t) { this.saveHandler = t } function Uf(t) { this.modelArtifacts = t } var Vf, Gf = Object.freeze({ browserFiles: function (t) { return new kf(t) }, browserHTTPRequest: function (t, e) { return Bf(t, e) }, concatenateArrayBuffers: qh, decodeWeights: Vh, encodeWeights: function (u, l) { return y(this, void 0, void 0, function () { var o, i, a, e, n, s = this; return R(this, function (t) { switch (t.label) { case 0: for (o = [], i = [], a = Array.isArray(u) ? u.map(function (t) { return t.name }) : Object.keys(u), e = function (t) { var e = a[t], c = Array.isArray(u) ? u[t].tensor : u[e]; if ("float32" !== c.dtype && "int32" !== c.dtype && "bool" !== c.dtype && "string" !== c.dtype) throw new Error("Unsupported dtype in weight '" + e + "': " + c.dtype); var n = { name: e, shape: c.shape, dtype: c.dtype }; if ("string" === c.dtype) { var r = new Promise(function (u) { return y(s, void 0, void 0, function () { var e, n, r, o, i, a, s; return R(this, function (t) { switch (t.label) { case 0: return [4, c.bytes()]; case 1: for (e = t.sent(), n = e.reduce(function (t, e) { return t + e.length }, 0) + Uh * e.length, r = new Uint8Array(n), i = o = 0; i < e.length; i++)a = e[i], s = new Uint8Array(new Uint32Array([a.length]).buffer), r.set(s, o), o += Uh, r.set(a, o), o += a.length; return u(r), [2] } }) }) }); i.push(r) } else i.push(c.data()); null != l && (n.group = l), o.push(n) }, n = 0; n < a.length; ++n)e(n); return [4, Promise.all(i)]; case 1: return [2, { data: function (t) { if (null === t) throw new Error("Invalid input value: " + JSON.stringify(t)); var e = 0, n = []; t.forEach(function (t) { if (e += t.byteLength, n.push(t.byteLength === t.buffer.byteLength ? t : new t.constructor(t)), !(t instanceof Float32Array || t instanceof Int32Array || t instanceof Uint8Array)) throw new Error("Unsupported TypedArray subtype: " + t.constructor.name) }); var r = new Uint8Array(e), o = 0; return n.forEach(function (t) { r.set(new Uint8Array(t.buffer), o), o += t.byteLength }), r.buffer }(t.sent()), specs: o }] } }) }) }, fromMemory: function (t, e, n, r) { return 1 === arguments.length ? null != t.modelTopology || null != t.weightSpecs ? new Lf(t) : (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 Lf({ modelTopology: t })) : (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 Lf({ modelTopology: t, weightSpecs: e, weightData: n, trainingConfig: r })) }, getLoadHandlers: function (t, e) { return Xh.getLoadHandlers(t, e) }, getModelArtifactsInfoForJSON: Kh, getSaveHandlers: function (t) { return Xh.getSaveHandlers(t) }, http: Bf, isHTTPScheme: Of, loadWeights: function (e, n, r, o) { return void 0 === n && (n = ""), y(this, void 0, void 0, function () { return R(this, function (t) { return [2, Nf(function (t) { return Tf(t, { requestInit: o }) })(e, n, r)] }) }) }, registerLoadRouter: function (t) { return Xh.registerLoadRouter(t) }, registerSaveRouter: function (t) { return Xh.registerSaveRouter(t) }, weightsLoaderFactory: Nf, withSaveHandler: function (t) { return new Wf(t) }, copyModel: function (e, n) { return y(this, void 0, void 0, function () { return R(this, function (t) { return [2, tf(e, n, !1)] }) }) }, listModels: function () { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s; return R(this, function (t) { switch (t.label) { case 0: e = $h.getSchemes(), n = {}, r = 0, o = e, t.label = 1; case 1: return r < o.length ? (i = o[r], [4, $h.getManager(i).listModels()]) : [3, 4]; case 2: for (s in a = t.sent()) n[i + Yh + s] = a[s]; t.label = 3; case 3: return r++, [3, 1]; case 4: return [2, n] } }) }) }, moveModel: function (e, n) { return y(this, void 0, void 0, function () { return R(this, function (t) { return [2, tf(e, n, !0)] }) }) }, removeModel: function (n) { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { return e = Zh(n), [2, $h.getManager(e.scheme).removeModel(e.path)] }) }) } }), Hf = wn({ confusionMatrix_: function (t, e, n) { var r = cn(t, "labels", "confusionMatrix"), o = cn(e, "predictions", "confusionMatrix"); P(null == n || 0 < n && Number.isInteger(n), function () { return "If provided, numClasses must be a positive integer, but got " + n }), P(1 === r.rank, function () { return "Expected the rank of labels to be 1, but got " + r.rank }), P(1 === o.rank, function () { return "Expected the rank of predictions to be 1, but got " + o.rank }), P(r.shape[0] === o.shape[0], function () { return "Mismatch in the number of examples: " + r.shape[0] + " vs. " + o.shape[0] + ". Labels and predictions should have the same number of elements." }), P(0 < n && Number.isInteger(n), function () { return "numClasses is required to be a positive integer, but got " + n }); var i = wr(r.asType("int32"), n), a = wr(o.asType("int32"), n); return i.transpose().matMul(a).asType("int32") } }), qf = Object.freeze({ confusionMatrix: Hf }), jf = wn({ fromPixels_: function (t, e) { if (void 0 === e && (e = 3), 4 < e) throw new Error("Cannot construct Tensor with more than 4 channels from pixels."); if (null == t) throw new Error("pixels passed to tf.browser.fromPixels() can not be null"); var n = !1, r = !1, o = !1, i = !1, a = !1; if (t.data instanceof Uint8Array) n = !0; else if ("undefined" != typeof ImageData && t instanceof ImageData) r = !0; else if ("undefined" != typeof HTMLVideoElement && t instanceof HTMLVideoElement) o = !0; else if ("undefined" != typeof HTMLImageElement && t instanceof HTMLImageElement) i = !0; else { if (null == t.getContext) 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 " + t.constructor.name); a = !0 } if (o && o && t.readyState < 2) throw new Error("The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element."); if (null != g("FromPixels", Kt.backendName)) return Kt.runKernel("FromPixels", { pixels: t }, { numChannels: e }); var s, u, c = o ? [t.videoWidth, t.videoHeight] : [t.width, t.height], l = c[0], h = c[1]; if (a ? s = t.getContext("2d").getImageData(0, 0, l, h).data : r || n ? s = t.data : (i || o) && (null == Vf && (Vf = document.createElement("canvas").getContext("2d")), Vf.canvas.width = l, Vf.canvas.height = h, Vf.drawImage(t, 0, 0, l, h), s = Vf.getImageData(0, 0, l, h).data), 4 === e) u = new Int32Array(s); else { var f = l * h; u = new Int32Array(f * e); for (var p = 0; p < f; p++)for (var d = 0; d < e; ++d)u[p * e + d] = s[4 * p + d] } return An(u, [h, l, e], "int32") } }), Kf = Object.freeze({ toPixels: function (_, I) { return y(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p, d, v, m, g, y, x, b, w, C, E; return R(this, function (t) { switch (t.label) { case 0: if (e = cn(_, "img", "toPixels"), _ instanceof bt || (e = e.toInt()), 2 !== e.rank && 3 !== e.rank) throw new Error("toPixels only supports rank 2 or 3 tensors, got rank " + e.rank + "."); if (n = e.shape.slice(0, 2), r = n[0], o = n[1], 4 < (i = 2 === e.rank ? 1 : e.shape[2]) || 2 === i) throw new Error("toPixels only supports depth of size 1, 3 or 4 but got " + i); return [4, e.data()]; case 1: return a = t.sent(), s = e.min(), u = e.max(), [4, Promise.all([s.data(), u.data()])]; case 2: if (c = t.sent(), l = c[0], h = c[1], f = l[0], p = h[0], s.dispose(), u.dispose(), "float32" === e.dtype) { if (f < 0 || 1 < p) throw new Error("Tensor values for a float32 Tensor must be in the range [0 - 1] but got range [" + f + " - " + p + "].") } else { if ("int32" !== e.dtype) throw new Error("Unsupported type for toPixels: " + e.dtype + ". Please use float32 or int32 tensors."); if (f < 0 || 255 < p) throw new Error("Tensor values for a int32 Tensor must be in the range [0 - 255] but got range [" + f + " - " + p + "].") } for (d = "float32" === e.dtype ? 255 : 1, v = new Uint8ClampedArray(o * r * 4), m = 0; m < r * o; ++m)b = x = y = g = void 0, 1 === i ? (g = a[m] * d, y = a[m] * d, x = a[m] * d, b = 255) : 3 === i ? (g = a[3 * m] * d, y = a[3 * m + 1] * d, x = a[3 * m + 2] * d, b = 255) : 4 === i && (g = a[4 * m] * d, y = a[4 * m + 1] * d, x = a[4 * m + 2] * d, b = a[4 * m + 3] * d), v[0 + (w = 4 * m)] = Math.round(g), v[1 + w] = Math.round(y), v[2 + w] = Math.round(x), v[3 + w] = Math.round(b); return null != I && (I.width = o, I.height = r, C = I.getContext("2d"), E = new ImageData(v, o, r), C.putImageData(E, 0, 0)), e !== _ && e.dispose(), [2, v] } }) }) }, fromPixels: jf }), Xf = (Jf.prototype.getClassName = function () { return this.constructor.className }, Jf.fromConfig = function (t, e) { return new t(e) }, Jf), Yf = ($f.getMap = function () { return null == $f.instance && ($f.instance = new $f), $f.instance }, $f.register = function (t) { $f.getMap().classNameMap[t.className] = [t, t.fromConfig] }, $f); function $f() { this.classNameMap = {} } function Jf() { } function Qf(t) { P(null != t.className, function () { return "Class being registered does not have the static className property defined." }), P("string" == typeof t.className, function () { return "className is required to be a string, but got type " + typeof t.className }), P(0 < t.className.length, function () { return "Class being registered has an empty-string as its className, which is disallowed." }), Yf.register(t) } var Zf = Object.freeze({ Serializable: Xf, SerializationMap: Yf, registerClass: Qf }); function tp() { return 32 === Kt.backend.floatPrecision() ? .001 : .1 } function ep(t, e, n) { var r = !0; if ((z(t) || z(e)) && (r = !1), z(t) && z(e) && (r = !0), r) { var o = t.constructor.name, i = e.constructor.name; if (o !== i) throw new Error("Arrays are of different type. Actual: " + o + ". Expected: " + i) } if (Array.isArray(t) && Array.isArray(e)) { var a = sn(t), s = sn(e); if (!A(a, s)) throw new Error("Arrays have different shapes. Actual: [" + a + "]. Expected: [" + s + "]") } var u = z(t) ? t : b(t), c = z(e) ? e : b(e); if (u.length !== c.length) throw new Error("Arrays have different lengths actual: " + u.length + " vs expected: " + c.length + ".\nActual:   " + u + ".\nExpected: " + c + "."); for (var l = 0; l < c.length; ++l) { var h = u[l], f = c[l]; if (!n(h, f)) throw new Error("Arrays differ: actual[" + l + "] = " + h + ", expected[" + l + "] = " + f + ".\nActual:   " + u + ".\nExpected: " + c + ".") } } function np(t, e, n) { return !isFinite(t) && !isFinite(e) || !(isNaN(t) || isNaN(e) || Math.abs(t - e) > n) } var rp, op = Object.freeze({ TEST_EPSILON_FLOAT16: .1, expectArraysClose: function (t, e, n) { return null == n && (n = tp()), ep(t, e, function (t, e) { return np(t, e, n) }) }, testEpsilon: tp, expectPromiseToFail: function (t, e) { t().then(function () { return e.fail() }, function () { return e() }) }, expectArraysEqual: function (t, e) { var n = "string" == typeof e || "number" == typeof e || "boolean" == typeof e ? [e] : e; return G(t) || G(t[0]) || G(e) || G(e[0]) ? ep(t, n, function (t, e) { return t == e }) : ep(t, e, function (t, e) { return np(t, e, 0) }) }, expectNumbersClose: function (t, e, n) { if (null == n && (n = tp()), !np(t, e, n)) throw new Error("Numbers differ: actual === " + t + ", expected === " + e) }, expectValuesInRange: function (t, e, n) { for (var r = 0; r < t.length; r++)if (t[r] < e || t[r] > n) throw new Error("Value out of range:" + t[r] + " low: " + e + ", high: " + n) }, expectArrayBuffersEqual: function (t, e) { expect(new Float32Array(t)).toEqual(new Float32Array(e)) } }), ip = Object.freeze({ gpgpu_util: ya, webgl_util: Ze, forceHalfFloat: function () { _().set("WEBGL_FORCE_F16_TEXTURES", !0) }, MathBackendWebGL: As, setWebGLContext: oe, GPGPUContext: xa }), ap = (t(sp, rp = Xf), sp.prototype.minimize = function (t, e, n) { void 0 === e && (e = !1); var r = this.computeGradients(t, n), o = r.value, i = r.grads; if (null != n) { var a = n.map(function (t) { return { name: t.name, tensor: i[t.name] } }); this.applyGradients(a) } else this.applyGradients(i); return rn(i), e ? o : (o.dispose(), null) }, Object.defineProperty(sp.prototype, "iterations", { get: function () { return null == this.iterations_ && (this.iterations_ = 0), this.iterations_ }, enumerable: !0, configurable: !0 }), sp.prototype.incrementIterations = function () { this.iterations_ = this.iterations + 1 }, sp.prototype.computeGradients = function (t, e) { return oo(t, e) }, sp.prototype.dispose = function () { null != this.iterations_ && rn(this.iterations_) }, sp.prototype.saveIterations = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { return null == this.iterations_ && (this.iterations_ = 0), [2, { name: "iter", tensor: kn(this.iterations_, "int32") }] }) }) }, sp.prototype.getWeights = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { throw new Error("getWeights() is not implemented for this optimizer yet.") }) }) }, sp.prototype.setWeights = function (t) { return y(this, void 0, void 0, function () { return R(this, function (t) { throw new Error("setWeights() is not implemented for this optimizer class " + this.getClassName()) }) }) }, sp.prototype.extractIterations = function (n) { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return e = this, [4, n[0].tensor.data()]; case 1: return e.iterations_ = t.sent()[0], [2, n.slice(1)] } }) }) }, sp); function sp() { return null !== rp && rp.apply(this, arguments) || this } Object.defineProperty(ap, Symbol.hasInstance, { value: function (t) { return null != t.minimize && null != t.computeGradients && null != t.applyGradients } }); var up, cp = (t(lp, up = ap), lp.prototype.applyGradients = function (n) { var u = this; (Array.isArray(n) ? n.map(function (t) { return t.name }) : Object.keys(n)).forEach(function (t, e) { var o = Kt.registeredVariables[t]; null == u.accumulatedGrads[e] && (u.accumulatedGrads[e] = { originalName: t + "/accum_grad", variable: nn(function () { return Un(o).variable(!1) }) }), null == u.accumulatedUpdates[e] && (u.accumulatedUpdates[e] = { originalName: t + "/accum_var", variable: nn(function () { return Un(o).variable(!1) }) }); var i = Array.isArray(n) ? n[e].tensor : n[t]; if (null != i) { var a = u.accumulatedGrads[e].variable, s = u.accumulatedUpdates[e].variable; nn(function () { var t = a.mul(u.rho).add(i.square().mul(1 - u.rho)), e = s.add(u.epsilon).sqrt().div(a.add(u.epsilon).sqrt()).mul(i), n = s.mul(u.rho).add(e.square().mul(1 - u.rho)); a.assign(t), s.assign(n); var r = e.mul(-u.learningRate).add(o); o.assign(r) }) } }), this.incrementIterations() }, lp.prototype.dispose = function () { null != this.accumulatedUpdates && (rn(this.accumulatedGrads.map(function (t) { return t.variable })), rn(this.accumulatedUpdates.map(function (t) { return t.variable }))) }, lp.prototype.getWeights = function () { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return e = this.accumulatedGrads.concat(this.accumulatedUpdates), [4, this.saveIterations()]; case 1: return [2, [t.sent()].concat(e.map(function (t) { return { name: t.originalName, tensor: t.variable } }))] } }) }) }, lp.prototype.setWeights = function (n) { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return [4, this.extractIterations(n)]; case 1: return n = t.sent(), e = n.length / 2, this.accumulatedGrads = n.slice(0, e).map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), this.accumulatedUpdates = n.slice(e, 2 * e).map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), [2] } }) }) }, lp.prototype.getConfig = function () { return { learningRate: this.learningRate, rho: this.rho, epsilon: this.epsilon } }, lp.fromConfig = function (t, e) { return new t(e.learningRate, e.rho, e.epsilon) }, lp.className = "Adadelta", lp); function lp(t, e, n) { void 0 === n && (n = null); var r = up.call(this) || this; return r.learningRate = t, r.rho = e, r.epsilon = n, r.accumulatedGrads = [], r.accumulatedUpdates = [], null == n && (r.epsilon = Kt.backend.epsilon()), r } Qf(cp); var hp, fp = (t(pp, hp = ap), pp.prototype.applyGradients = function (i) { var a = this; (Array.isArray(i) ? i.map(function (t) { return t.name }) : Object.keys(i)).forEach(function (t, e) { var n = Kt.registeredVariables[t]; null == a.accumulatedGrads[e] && (a.accumulatedGrads[e] = { originalName: t + "/accumulator", variable: nn(function () { return Bn(n.shape, a.initialAccumulatorValue).variable(!1) }) }); var r = Array.isArray(i) ? i[e].tensor : i[t]; if (null != r) { var o = a.accumulatedGrads[e].variable; nn(function () { var t = o.add(r.square()); o.assign(t); var e = r.div(t.add(Kt.backend.epsilon()).sqrt()).mul(-a.learningRate).add(n); n.assign(e) }) } }), this.incrementIterations() }, pp.prototype.dispose = function () { null != this.accumulatedGrads && rn(this.accumulatedGrads.map(function (t) { return t.variable })) }, pp.prototype.getWeights = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { switch (t.label) { case 0: return [4, this.saveIterations()]; case 1: return [2, [t.sent()].concat(this.accumulatedGrads.map(function (t) { return { name: t.originalName, tensor: t.variable } }))] } }) }) }, pp.prototype.setWeights = function (e) { return y(this, void 0, void 0, function () { return R(this, function (t) { switch (t.label) { case 0: return [4, this.extractIterations(e)]; case 1: return e = t.sent(), this.accumulatedGrads = e.map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), [2] } }) }) }, pp.prototype.getConfig = function () { return { learningRate: this.learningRate, initialAccumulatorValue: this.initialAccumulatorValue } }, pp.fromConfig = function (t, e) { return new t(e.learningRate, e.initialAccumulatorValue) }, pp.className = "Adagrad", pp); function pp(t, e) { void 0 === e && (e = .1); var n = hp.call(this) || this; return n.learningRate = t, n.initialAccumulatorValue = e, n.accumulatedGrads = [], n } Qf(fp); var dp, vp = (t(mp, dp = ap), mp.prototype.applyGradients = function (p) { var d = this, t = Array.isArray(p) ? p.map(function (t) { return t.name }) : Object.keys(p); nn(function () { var h = tc(1, d.accBeta1), f = tc(1, d.accBeta2); t.forEach(function (t, e) { var n = Kt.registeredVariables[t]; null == d.accumulatedFirstMoment[e] && (d.accumulatedFirstMoment[e] = { originalName: t + "/m", variable: nn(function () { return Un(n).variable(!1) }) }), null == d.accumulatedSecondMoment[e] && (d.accumulatedSecondMoment[e] = { originalName: t + "/v", variable: nn(function () { return Un(n).variable(!1) }) }); var r = Array.isArray(p) ? p[e].tensor : p[t]; if (null != r) { var o = d.accumulatedFirstMoment[e].variable, i = d.accumulatedSecondMoment[e].variable, a = o.mul(d.beta1).add(r.mul(1 - d.beta1)), s = i.mul(d.beta2).add(r.square().mul(1 - d.beta2)), u = a.div(h), c = s.div(f); o.assign(a), i.assign(s); var l = u.div(c.sqrt().add(d.epsilon)).mul(-d.learningRate).add(n); n.assign(l) } }), d.accBeta1.assign(d.accBeta1.mul(d.beta1)), d.accBeta2.assign(d.accBeta2.mul(d.beta2)) }), this.incrementIterations() }, mp.prototype.dispose = function () { this.accBeta1.dispose(), this.accBeta2.dispose(), null != this.accumulatedFirstMoment && rn(this.accumulatedFirstMoment.map(function (t) { return t.variable })), null != this.accumulatedSecondMoment && rn(this.accumulatedSecondMoment.map(function (t) { return t.variable })) }, mp.prototype.getWeights = function () { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return e = this.accumulatedFirstMoment.concat(this.accumulatedSecondMoment), [4, this.saveIterations()]; case 1: return [2, [t.sent()].concat(e.map(function (t) { return { name: t.originalName, tensor: t.variable } }))] } }) }) }, mp.prototype.setWeights = function (r) { return y(this, void 0, void 0, function () { var e, n = this; return R(this, function (t) { switch (t.label) { case 0: return [4, this.extractIterations(r)]; case 1: return r = t.sent(), nn(function () { n.accBeta1.assign(Ju(n.beta1, n.iterations_ + 1)), n.accBeta2.assign(Ju(n.beta2, n.iterations_ + 1)) }), e = r.length / 2, this.accumulatedFirstMoment = r.slice(0, e).map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), this.accumulatedSecondMoment = r.slice(e, 2 * e).map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), [2] } }) }) }, mp.prototype.getConfig = function () { return { learningRate: this.learningRate, beta1: this.beta1, beta2: this.beta2, epsilon: this.epsilon } }, mp.fromConfig = function (t, e) { return new t(e.learningRate, e.beta1, e.beta2, e.epsilon) }, mp.className = "Adam", mp); function mp(t, e, n, r) { void 0 === r && (r = null); var o = dp.call(this) || this; return o.learningRate = t, o.beta1 = e, o.beta2 = n, o.epsilon = r, o.accumulatedFirstMoment = [], o.accumulatedSecondMoment = [], nn(function () { o.accBeta1 = kn(e).variable(), o.accBeta2 = kn(n).variable() }), null == r && (o.epsilon = Kt.backend.epsilon()), o } Qf(vp); var gp, yp = (t(xp, gp = ap), xp.prototype.applyGradients = function (p) { var d = this, t = Array.isArray(p) ? p.map(function (t) { return t.name }) : Object.keys(p); nn(function () { var h = tc(1, d.accBeta1), f = Wu(-d.learningRate, d.iteration.mul(d.decay).add(1)); t.forEach(function (t, e) { var n = Kt.registeredVariables[t]; null == d.accumulatedFirstMoment[e] && (d.accumulatedFirstMoment[e] = { originalName: t + "/m", variable: Un(n).variable(!1) }), null == d.accumulatedWeightedInfNorm[e] && (d.accumulatedWeightedInfNorm[e] = { originalName: t + "/v", variable: Un(n).variable(!1) }); var r = Array.isArray(p) ? p[e].tensor : p[t]; if (null != r) { var o = d.accumulatedFirstMoment[e].variable, i = d.accumulatedWeightedInfNorm[e].variable, a = o.mul(d.beta1).add(r.mul(1 - d.beta1)), s = i.mul(d.beta2), u = r.abs(), c = s.maximum(u); o.assign(a), i.assign(c); var l = f.div(h).mul(a.div(c.add(d.epsilon))).add(n); n.assign(l) } }), d.iteration.assign(d.iteration.add(1)), d.accBeta1.assign(d.accBeta1.mul(d.beta1)) }), this.incrementIterations() }, xp.prototype.dispose = function () { this.accBeta1.dispose(), this.iteration.dispose(), null != this.accumulatedFirstMoment && rn(this.accumulatedFirstMoment.map(function (t) { return t.variable })), null != this.accumulatedWeightedInfNorm && rn(this.accumulatedWeightedInfNorm.map(function (t) { return t.variable })) }, xp.prototype.getWeights = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { throw new Error("getWeights() is not implemented for Adamax yet.") }) }) }, xp.prototype.setWeights = function (t) { return y(this, void 0, void 0, function () { return R(this, function (t) { throw new Error("setWeights() is not implemented for Adamax yet.") }) }) }, xp.prototype.getConfig = function () { return { learningRate: this.learningRate, beta1: this.beta1, beta2: this.beta2, epsilon: this.epsilon, decay: this.decay } }, xp.fromConfig = function (t, e) { return new t(e.learningRate, e.beta1, e.beta2, e.epsilon, e.decay) }, xp.className = "Adamax", xp); function xp(t, e, n, r, o) { void 0 === r && (r = null), void 0 === o && (o = 0); var i = gp.call(this) || this; return i.learningRate = t, i.beta1 = e, i.beta2 = n, i.epsilon = r, i.decay = o, i.accumulatedFirstMoment = [], i.accumulatedWeightedInfNorm = [], nn(function () { i.iteration = kn(0).variable(), i.accBeta1 = kn(e).variable() }), null == r && (i.epsilon = Kt.backend.epsilon()), i } Qf(yp); var bp, wp = (t(Cp, bp = ap), Cp.prototype.applyGradients = function (o) { var i = this; (Array.isArray(o) ? o.map(function (t) { return t.name }) : Object.keys(o)).forEach(function (t, e) { var n = Array.isArray(o) ? o[e].tensor : o[t]; if (null != n) { var r = Kt.registeredVariables[t]; nn(function () { var t = i.c.mul(n).add(r); r.assign(t) }) } }), this.incrementIterations() }, Cp.prototype.setLearningRate = function (t) { this.learningRate = t, null != this.c && this.c.dispose(), this.c = on(kn(-t)) }, Cp.prototype.dispose = function () { this.c.dispose() }, Cp.prototype.getWeights = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { switch (t.label) { case 0: return [4, this.saveIterations()]; case 1: return [2, [t.sent()]] } }) }) }, Cp.prototype.setWeights = function (e) { return y(this, void 0, void 0, function () { return R(this, function (t) { switch (t.label) { case 0: return [4, this.extractIterations(e)]; case 1: if (0 !== (e = t.sent()).length) throw new Error("SGD optimizer does not have settable weights."); return [2] } }) }) }, Cp.prototype.getConfig = function () { return { learningRate: this.learningRate } }, Cp.fromConfig = function (t, e) { return new t(e.learningRate) }, Cp.className = "SGD", Cp); function Cp(t) { var e = bp.call(this) || this; return e.learningRate = t, e.setLearningRate(t), e } Qf(wp); var Ep, _p = (t(Ip, Ep = wp), Ip.prototype.applyGradients = function (i) { var a = this; (Array.isArray(i) ? i.map(function (t) { return t.name }) : Object.keys(i)).forEach(function (t, e) { var n = Kt.registeredVariables[t]; null == a.accumulations[e] && (a.accumulations[e] = { originalName: t + "/momentum", variable: nn(function () { return Un(n).variable(!1) }) }); var r = a.accumulations[e].variable, o = Array.isArray(i) ? i[e].tensor : i[t]; null != o && nn(function () { var t, e = a.m.mul(r).add(o); t = a.useNesterov ? a.c.mul(o.add(e.mul(a.m))).add(n) : a.c.mul(e).add(n), r.assign(e), n.assign(t) }) }), this.incrementIterations() }, Ip.prototype.dispose = function () { this.m.dispose(), null != this.accumulations && rn(this.accumulations.map(function (t) { return t.variable })) }, Ip.prototype.setMomentum = function (t) { this.momentum = t }, Ip.prototype.getWeights = function () { return y(this, void 0, void 0, function () { return R(this, function (t) { switch (t.label) { case 0: return [4, this.saveIterations()]; case 1: return [2, [t.sent()].concat(this.accumulations.map(function (t) { return { name: t.originalName, tensor: t.variable } }))] } }) }) }, Ip.prototype.setWeights = function (e) { return y(this, void 0, void 0, function () { return R(this, function (t) { switch (t.label) { case 0: return [4, this.extractIterations(e)]; case 1: return e = t.sent(), this.accumulations = e.map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), [2] } }) }) }, Ip.prototype.getConfig = function () { return { learningRate: this.learningRate, momentum: this.momentum, useNesterov: this.useNesterov } }, Ip.fromConfig = function (t, e) { return new t(e.learningRate, e.momentum, e.useNesterov) }, Ip.className = "Momentum", Ip); function Ip(t, e, n) { void 0 === n && (n = !1); var r = Ep.call(this, t) || this; return r.learningRate = t, r.momentum = e, r.useNesterov = n, r.accumulations = [], r.m = kn(r.momentum), r } Qf(_p); var Rp, kp = (t(Sp, Rp = ap), Sp.prototype.applyGradients = function (e) { var h = this; (Array.isArray(e) ? e.map(function (t) { return t.name }) : Object.keys(e)).forEach(function (t, a) { var s = Kt.registeredVariables[t]; null == h.accumulatedMeanSquares[a] && (h.accumulatedMeanSquares[a] = { originalName: t + "/rms", variable: nn(function () { return Un(s).variable(!1) }) }), null == h.accumulatedMoments[a] && (h.accumulatedMoments[a] = { originalName: t + "/momentum", variable: nn(function () { return Un(s).variable(!1) }) }), null == h.accumulatedMeanGrads[a] && h.centered && (h.accumulatedMeanGrads[a] = { originalName: t + "/mg", variable: nn(function () { return Un(s).variable(!1) }) }); var u = Array.isArray(e) ? e[a].tensor : e[t]; if (null != u) { var c = h.accumulatedMeanSquares[a].variable, l = h.accumulatedMoments[a].variable; nn(function () { var t = c.mul(h.decay).add(u.square().mul(1 - h.decay)); if (h.centered) { var e = h.accumulatedMeanGrads[a].variable, n = e.mul(h.decay).add(u.mul(1 - h.decay)), r = l.mul(h.momentum).add(u.mul(h.learningRate).div(t.sub(n.square().add(h.epsilon)).sqrt())); c.assign(t), e.assign(n), l.assign(r); var o = s.sub(r); s.assign(o) } else { var i = c.mul(h.decay).add(u.square().mul(1 - h.decay)); r = l.mul(h.momentum).add(u.mul(h.learningRate).div(i.add(h.epsilon).sqrt())), c.assign(i), l.assign(r), o = s.sub(r), s.assign(o) } }) } }), this.incrementIterations() }, Sp.prototype.dispose = function () { null != this.accumulatedMeanSquares && rn(this.accumulatedMeanSquares.map(function (t) { return t.variable })), null != this.accumulatedMeanGrads && this.centered && rn(this.accumulatedMeanGrads.map(function (t) { return t.variable })), null != this.accumulatedMoments && rn(this.accumulatedMoments.map(function (t) { return t.variable })) }, Sp.prototype.getWeights = function () { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return e = this.accumulatedMeanSquares.concat(this.accumulatedMoments), this.centered && e.push.apply(e, this.accumulatedMeanGrads), [4, this.saveIterations()]; case 1: return [2, [t.sent()].concat(e.map(function (t) { return { name: t.originalName, tensor: t.variable } }))] } }) }) }, Sp.prototype.setWeights = function (n) { return y(this, void 0, void 0, function () { var e; return R(this, function (t) { switch (t.label) { case 0: return [4, this.extractIterations(n)]; case 1: return n = t.sent(), e = this.centered ? n.length / 3 : n.length / 2, this.accumulatedMeanSquares = n.slice(0, e).map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), this.accumulatedMoments = n.slice(e, 2 * e).map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } }), this.centered && (this.accumulatedMeanGrads = n.slice(2 * e, 3 * e).map(function (t) { return { originalName: t.name, variable: t.tensor.variable(!1) } })), [2] } }) }) }, Sp.prototype.getConfig = function () { return { learningRate: this.learningRate, decay: this.decay, momentum: this.momentum, epsilon: this.epsilon, centered: this.centered } }, Sp.fromConfig = function (t, e) { return new t(e.learningRate, e.decay, e.momentum, e.epsilon, e.centered) }, Sp.className = "RMSProp", Sp); function Sp(t, e, n, r, o) { void 0 === e && (e = .9), void 0 === n && (n = 0), void 0 === r && (r = null), void 0 === o && (o = !1); var i = Rp.call(this) || this; if (i.learningRate = t, i.decay = e, i.momentum = n, i.epsilon = r, i.accumulatedMeanSquares = [], i.accumulatedMoments = [], i.accumulatedMeanGrads = [], i.centered = o, null == r && (i.epsilon = Kt.backend.epsilon()), null == t) throw new Error("learningRate for RMSPropOptimizer must be defined."); return i } Qf(kp); var Dp = (Np.sgd = function (t) { return new wp(t) }, Np.momentum = function (t, e, n) { return void 0 === n && (n = !1), new _p(t, e, n) }, Np.rmsprop = function (t, e, n, r, o) { return void 0 === e && (e = .9), void 0 === n && (n = 0), void 0 === r && (r = null), void 0 === o && (o = !1), new kp(t, e, n, r, o) }, Np.adam = function (t, e, n, r) { return void 0 === t && (t = .001), void 0 === e && (e = .9), void 0 === n && (n = .999), void 0 === r && (r = null), new vp(t, e, n, r) }, Np.adadelta = function (t, e, n) { return void 0 === t && (t = .001), void 0 === e && (e = .95), void 0 === n && (n = null), new cp(t, e, n) }, Np.adamax = function (t, e, n, r, o) { return void 0 === t && (t = .002), void 0 === e && (e = .9), void 0 === n && (n = .999), void 0 === r && (r = null), void 0 === o && (o = 0), new yp(t, e, n, r, o) }, Np.adagrad = function (t, e) { return void 0 === e && (e = .1), new fp(t, e) }, Np), Ap = { sgd: Dp.sgd, momentum: Dp.momentum, adadelta: Dp.adadelta, adagrad: Dp.adagrad, rmsprop: Dp.rmsprop, adamax: Dp.adamax, adam: Dp.adam }, Tp = "undefined" != typeof requestAnimationFrame ? requestAnimationFrame : "undefined" != typeof setImmediate ? setImmediate : function (t) { return t() }; function Np() { } bt.prototype.squaredDifference = function (t) { return Ms(this, t) }, gt = bh; var Fp = Object.freeze({ __proto__: null, AdadeltaOptimizer: cp, AdagradOptimizer: fp, AdamOptimizer: vp, AdamaxOptimizer: yp, DataStorage: co, get ENV() { return i }, Environment: o, KernelBackend: lo, MomentumOptimizer: _p, Optimizer: ap, RMSPropOptimizer: kp, get Rank() { return Ct }, get Reduction() { return Bl }, SGDOptimizer: wp, Tensor: bt, TensorBuffer: vt, Variable: Ft, abs: Os, acos: Ps, acosh: Bs, add: Ou, addN: Pu, addStrict: Bu, all: tl, any: el, argMax: nl, argMin: rl, asin: Ls, asinh: Ws, atan: zs, atan2: Lu, atanh: Us, avgPool: Hc, avgPool3d: Kc, backend: function () { return Kt.backend }, backend_util: Fo, basicLSTMCell: bl, batchNorm: Ru, batchNorm2d: ku, batchNorm3d: Su, batchNorm4d: Du, batchNormalization: Iu, batchNormalization2d: Cu, batchNormalization3d: Eu, batchNormalization4d: _u, batchToSpaceND: fr, booleanMaskAsync: mc, broadcastTo: pr, browser: Kf, buffer: cr, cast: dr, ceil: Vs, clipByValue: Gs, clone: vr, complex: Cn, concat: Vn, concat1d: Gn, concat2d: Hn, concat3d: qn, concat4d: jn, conv1d: Cc, conv2d: Ec, conv2dTranspose: Tc, conv3d: _c, conv3dTranspose: Nc, cos: Hs, cosh: qs, cumsum: mr, customGrad: io, deprecationWarn: en, depthToSpace: gr, depthwiseConv2d: kc, diag: Fl, disableDeprecationWarnings: function () { _().set("DEPRECATION_WARNINGS_ENABLED", !1), console.warn("TensorFlow.js deprecation warnings have been disabled.") }, dispose: rn, disposeVariables: function () { Kt.disposeVariables() }, div: Wu, divNoNan: zu, divStrict: Uu, dot: Mc, dropout: Ml, elu: hl, enableDebugMode: function () { _().set("DEBUG", !0) }, enableProdMode: function () { _().set("PROD", !0) }, engine: function () { return Kt }, env: _, equal: nc, equalStrict: rc, erf: js, exp: Ks, expandDims: yr, expm1: Xs, eye: xr, fft: Rl, fill: Bn, findBackend: function (t) { return Kt.findBackend(t) }, findBackendFactory: function (t) { return Kt.findBackendFactory(t) }, floor: Ys, floorDiv: Vu, frame: Ul, fused: xh, gather: gc, gatherND: Nl, gather_util: Hr, getBackend: function () { return Kt.backendName }, getGradient: l, getKernel: g, getKernelsForBackend: a, grad: function (i) { return P(K(i), function () { return "The f passed in grad(f) must be a function" }), function (t, e) { var r = cn(t, "x", "tf.grad", null), o = null != e ? cn(e, "dy", "tf.grad") : null; return Kt.tidy(function () { var t = Kt.gradients(function () { return i(r) }, [r], o), e = t.value, n = t.grads; return null != o && x(e.shape, o.shape, "The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"), ao(n), n[0] }) } }, grads: function (i) { return P(K(i), function () { return "The f passed in grads(f) must be a function" }), function (t, e) { P(Array.isArray(t), function () { return "The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s" }); var r = ln(t, "args", "tf.grads", null), o = null != e ? cn(e, "dy", "tf.grads") : null; return Kt.tidy(function () { var t = Kt.gradients(function () { return i.apply(void 0, r) }, r, o), e = t.value, n = t.grads; return null != o && x(e.shape, o.shape, "The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"), ao(n), n }) } }, greater: oc, greaterEqual: ic, greaterEqualStrict: ac, greaterStrict: sc, hammingWindow: zl, hannWindow: Wl, ifft: kl, imag: _n, image: vh, inTopKAsync: Pl, io: Gf, irfft: Dl, isFinite: su, isInf: au, isNaN: iu, keep: on, leakyRelu: fl, less: uc, lessEqual: cc, lessEqualStrict: lc, lessStrict: hc, linalg: oh, linspace: Ln, localResponseNormalization: yl, log: $s, log1p: Js, logSigmoid: Qs, logSoftmax: uo, logSumExp: ol, logicalAnd: Au, logicalNot: Tu, logicalOr: Nu, logicalXor: Fu, losses: Zl, matMul: Fc, math: qf, max: il, maxPool: Gc, maxPool3d: jc, maximum: Gu, maximumStrict: Hu, mean: al, memory: function () { return Kt.memory() }, min: sl, minimum: qu, minimumStrict: ju, mod: Ku, modStrict: Xu, moments: ul, movingAverage: Cl, mul: Yu, mulStrict: $u, multiRNNCell: wl, multinomial: br, neg: Zs, nextFrame: function () { return new Promise(function (t) { return Tp(function () { return t() }) }) }, norm: xl, notEqual: fc, notEqualStrict: pc, oneHot: wr, ones: On, onesLike: zn, op: wn, outerProduct: Oc, pad: Cr, pad1d: Er, pad2d: _r, pad3d: Ir, pad4d: Rr, pool: qc, pow: Ju, powStrict: Qu, prelu: pl, print: lr, prod: ll, profile: function (t) { return Kt.profile(t) }, rand: kr, randomGamma: Dr, randomNormal: Sr, randomUniform: Ar, range: Wn, ready: function () { return Kt.ready() }, real: En, reciprocal: tu, registerBackend: function (t, e, n) { return void 0 === n && (n = 1), Kt.registerBackend(t, e, n) }, registerGradient: h, registerKernel: s, relu: dl, relu6: vl, removeBackend: function (t) { Kt.removeBackend(t) }, reshape: Tr, reverse: Pc, reverse1d: Bc, reverse2d: Lc, reverse3d: Wc, reverse4d: zc, rfft: Sl, round: eu, rsqrt: nu, scalar: kn, scatterND: Il, scatter_util: Yr, selu: ml, separableConv2d: Ac, serialization: Zf, setBackend: function (t) { return Kt.setBackend(t) }, setPlatform: function (t, e) { _().setPlatform(t, e) }, setdiff1dAsync: hr, sigmoid: ru, sign: ou, signal: Gl, sin: uu, sinh: cu, slice: Xc, slice1d: Yc, slice2d: $c, slice3d: Jc, slice4d: Qc, slice_util: ro, softmax: so, softplus: lu, spaceToBatchND: Nr, sparseToDense: Tl, spectral: Al, split: Kn, sqrt: hu, square: Ns, squaredDifference: Ms, squaredDifferenceStrict: Zu, squeeze: Fr, stack: Mr, step: fu, stft: Vl, stridedSlice: El, sub: tc, subStrict: ec, sum: cl, sumOutType: Bt, tan: pu, tanh: du, tensor: In, tensor1d: Sn, tensor2d: Dn, tensor3d: An, tensor4d: Tn, tensor5d: Nn, tensor6d: Fn, tensor_util: Vt, test_util: op, tidy: nn, tile: Or, time: function (t) { return Kt.time(t) }, topk: _l, train: Ap, transpose: gl, truncatedNormal: Pr, unregisterGradient: function (t) { if (!n.has(t)) throw new Error("The gradient '" + t + "' for backend is not registered"); n.delete(t) }, unregisterKernel: function (t, e) { var n = f(t, e); if (!u.has(n)) throw new Error("The kernel '" + t + "' for backend '" + e + "' is not registered"); u.delete(n) }, unsortedSegmentSum: yc, unstack: Br, util: at, valueAndGrad: function (i) { return P(K(i), function () { return "The f passed in valueAndGrad(f) must be a function" }), function (t, e) { P(t instanceof bt, function () { return "The x passed in valueAndGrad(f)(x) must be a tensor" }), P(null == e || e instanceof bt, function () { return "The dy passed in valueAndGrad(f)(x, dy) must be a tensor" }); var n = Kt.gradients(function () { return i(t) }, [t], e), r = n.grads, o = n.value; return ao(r), { grad: r[0], value: o } } }, valueAndGrads: function (r) { return P(K(r), function () { return "The f passed in valueAndGrads(f) must be a function" }), function (t, e) { P(Array.isArray(t) && t.every(function (t) { return t instanceof bt }), function () { return "The args passed in valueAndGrads(f)(args) must be array of tensors" }), P(null == e || e instanceof bt, function () { return "The dy passed in valueAndGrads(f)(args, dy) must be a tensor" }); var n = Kt.gradients(function () { return r.apply(void 0, t) }, t, e); return null != e && x(n.value.shape, e.shape, "The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"), ao(n.grads), n } }, variable: Mn, variableGrads: oo, version_core: "1.7.0", webgl: ip, where: Mu, whereAsync: wu, zeros: Pn, zerosLike: Un }); function Mp(i, a, t) { if (void 0 === t && (t = !1), i.beginPath(), a.slice(1).forEach(function (t, e) { var n = t.x, r = t.y, o = a[e]; i.moveTo(o.x, o.y), i.lineTo(n, r) }), t) { var e = a[a.length - 1], n = a[0]; if (!e || !n) return; i.moveTo(e.x, e.y), i.lineTo(n.x, n.y) } i.stroke() } var Op = function (t, e) { return (Op = Object.setPrototypeOf || { __proto__: [] } instanceof Array && function (t, e) { t.__proto__ = e } || function (t, e) { for (var n in e) e.hasOwnProperty(n) && (t[n] = e[n]) })(t, e) }; function Pp(t, e) { function n() { this.constructor = t } Op(t, e), t.prototype = null === e ? Object.create(e) : (n.prototype = e.prototype, new n) } var Bp = function () { return (Bp = Object.assign || function (t) { for (var e, n = 1, r = arguments.length; n < r; n++)for (var o in e = arguments[n]) Object.prototype.hasOwnProperty.call(e, o) && (t[o] = e[o]); return t }).apply(this, arguments) }; function Lp(i, a, s, u) { return new (s = s || Promise)(function (t, e) { function n(t) { try { o(u.next(t)) } catch (t) { e(t) } } function r(t) { try { o(u.throw(t)) } catch (t) { e(t) } } function o(e) { e.done ? t(e.value) : new s(function (t) { t(e.value) }).then(n, r) } o((u = u.apply(i, a || [])).next()) }) } function Wp(n, r) { var o, i, a, t, s = { label: 0, sent: function () { if (1 & a[0]) throw a[1]; return a[1] }, trys: [], ops: [] }; return t = { next: e(0), throw: e(1), return: e(2) }, "function" == typeof Symbol && (t[Symbol.iterator] = function () { return this }), t; function e(e) { return function (t) { return function (e) { if (o) throw new TypeError("Generator is already executing."); for (; s;)try { if (o = 1, i && (a = 2 & e[0] ? i.return : e[0] ? i.throw || ((a = i.return) && a.call(i), 0) : i.next) && !(a = a.call(i, e[1])).done) return a; switch (i = 0, a && (e = [2 & e[0], a.value]), e[0]) { case 0: case 1: a = e; break; case 4: return s.label++, { value: e[1], done: !1 }; case 5: s.label++, i = e[1], e = [0]; continue; case 7: e = s.ops.pop(), s.trys.pop(); continue; default: if (!(a = 0 < (a = s.trys).length && a[a.length - 1]) && (6 === e[0] || 2 === e[0])) { s = 0; continue } if (3 === e[0] && (!a || e[1] > a[0] && e[1] < a[3])) { s.label = e[1]; break } if (6 === e[0] && s.label < a[1]) { s.label = a[1], a = e; break } if (a && s.label < a[2]) { s.label = a[2], s.ops.push(e); break } a[2] && s.ops.pop(), s.trys.pop(); continue }e = r.call(n, s) } catch (t) { e = [6, t], i = 0 } finally { o = a = 0 } if (5 & e[0]) throw e[1]; return { value: e[0] ? e[1] : void 0, done: !0 } }([e, t]) } } } function zp() { for (var t = 0, e = 0, n = arguments.length; e < n; e++)t += arguments[e].length; var r = Array(t), o = 0; for (e = 0; e < n; e++)for (var i = arguments[e], a = 0, s = i.length; a < s; a++, o++)r[o] = i[a]; return r } var Up = (Object.defineProperty(Vp.prototype, "width", { get: function () { return this._width }, enumerable: !0, configurable: !0 }), Object.defineProperty(Vp.prototype, "height", { get: function () { return this._height }, enumerable: !0, configurable: !0 }), Vp.prototype.reverse = function () { return new Vp(1 / this.width, 1 / this.height) }, Vp); function Vp(t, e) { if (!td(t) || !td(e)) throw new Error("Dimensions.constructor - expected width and height to be valid numbers, instead have " + JSON.stringify({ width: t, height: e })); this._width = t, this._height = e } function Gp(t, e) { return t instanceof bt && t.shape.length === e } function Hp(t) { return Gp(t, 2) } function qp(t) { return Gp(t, 3) } function jp(t) { return Gp(t, 4) } function Kp(t) { return t % 1 != 0 } function Xp(t) { return t % 2 == 0 } function Yp(t, e) { void 0 === e && (e = 2); var n = Math.pow(10, e); return Math.floor(t * n) / n } function $p(t) { return t && t.width && t.height } function Jp(t, e) { var n = t.width, r = t.height, o = e / Math.max(r, n); return new Up(Math.round(n * o), Math.round(r * o)) } function Qp(t) { return t.reduce(function (t, e) { return t.add(e) }, new rd(0, 0)).div(new rd(t.length, t.length)) } function Zp(t, n, r) { return Array(t).fill(0).map(function (t, e) { return n + e * r }) } function td(t) { return !!t && t !== 1 / 0 && t !== -1 / 0 && !isNaN(t) || 0 === t } function ed(t) { return td(t) && 0 <= t && t <= 1 } var nd = Object.freeze({ __proto__: null, isTensor: Gp, isTensor1D: function (t) { return Gp(t, 1) }, isTensor2D: Hp, isTensor3D: qp, isTensor4D: jp, isFloat: Kp, isEven: Xp, round: Yp, isDimensions: $p, computeReshapedDimensions: Jp, getCenterPoint: Qp, range: Zp, isValidNumber: td, isValidProbablitiy: ed }), rd = (Object.defineProperty(od.prototype, "x", { get: function () { return this._x }, enumerable: !0, configurable: !0 }), Object.defineProperty(od.prototype, "y", { get: function () { return this._y }, enumerable: !0, configurable: !0 }), od.prototype.add = function (t) { return new od(this.x + t.x, this.y + t.y) }, od.prototype.sub = function (t) { return new od(this.x - t.x, this.y - t.y) }, od.prototype.mul = function (t) { return new od(this.x * t.x, this.y * t.y) }, od.prototype.div = function (t) { return new od(this.x / t.x, this.y / t.y) }, od.prototype.abs = function () { return new od(Math.abs(this.x), Math.abs(this.y)) }, od.prototype.magnitude = function () { return Math.sqrt(Math.pow(this.x, 2) + Math.pow(this.y, 2)) }, od.prototype.floor = function () { return new od(Math.floor(this.x), Math.floor(this.y)) }, od); function od(t, e) { this._x = t, this._y = e } var id = (ad.isRect = function (t) { return !!t && [t.x, t.y, t.width, t.height].every(td) }, ad.assertIsValidBox = function (t, e, n) { if (void 0 === n && (n = !1), !ad.isRect(t)) throw new Error(e + " - invalid box: " + JSON.stringify(t) + ", expected object with properties x, y, width, height"); if (!n && (t.width < 0 || t.height < 0)) throw new Error(e + " - width (" + t.width + ") and height (" + t.height + ") must be positive numbers") }, Object.defineProperty(ad.prototype, "x", { get: function () { return this._x }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "y", { get: function () { return this._y }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "width", { get: function () { return this._width }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "height", { get: function () { return this._height }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "left", { get: function () { return this.x }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "top", { get: function () { return this.y }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "right", { get: function () { return this.x + this.width }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "bottom", { get: function () { return this.y + this.height }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "area", { get: function () { return this.width * this.height }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "topLeft", { get: function () { return new rd(this.left, this.top) }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "topRight", { get: function () { return new rd(this.right, this.top) }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "bottomLeft", { get: function () { return new rd(this.left, this.bottom) }, enumerable: !0, configurable: !0 }), Object.defineProperty(ad.prototype, "bottomRight", { get: function () { return new rd(this.right, this.bottom) }, enumerable: !0, configurable: !0 }), ad.prototype.round = function () { var t = [this.x, this.y, this.width, this.height].map(function (t) { return Math.round(t) }); return new ad({ x: t[0], y: t[1], width: t[2], height: t[3] }) }, ad.prototype.floor = function () { var t = [this.x, this.y, this.width, this.height].map(function (t) { return Math.floor(t) }); return new ad({ x: t[0], y: t[1], width: t[2], height: t[3] }) }, ad.prototype.toSquare = function () { var t = this.x, e = this.y, n = this.width, r = this.height, o = Math.abs(n - r); return n < r && (t -= o / 2, n += o), r < n && (e -= o / 2, r += o), new ad({ x: t, y: e, width: n, height: r }) }, ad.prototype.rescale = function (t) { var e = $p(t) ? t.width : t, n = $p(t) ? t.height : t; return new ad({ x: this.x * e, y: this.y * n, width: this.width * e, height: this.height * n }) }, ad.prototype.pad = function (t, e) { var n = [this.x - t / 2, this.y - e / 2, this.width + t, this.height + e]; return new ad({ x: n[0], y: n[1], width: n[2], height: n[3] }) }, ad.prototype.clipAtImageBorders = function (t, e) { var n = this.x, r = this.y, o = this.right, i = this.bottom, a = Math.max(n, 0), s = Math.max(r, 0), u = o - a, c = i - s; return new ad({ x: a, y: s, width: Math.min(u, t - a), height: Math.min(c, e - s) }).floor() }, ad.prototype.shift = function (t, e) { var n = this.width, r = this.height; return new ad({ x: this.x + t, y: this.y + e, width: n, height: r }) }, ad.prototype.padAtBorders = function (t, e) { var n = this.width + 1, r = this.height + 1, o = n, i = r, a = this.left, s = this.top, u = this.right, c = this.bottom; return e < u && (o = -u + e + n, u = e), t < c && (i = -c + t + r, c = t), a < 1 && (i = 2 - a, a = 1), s < 1 && (i = 2 - s, s = 1), { dy: 1, edy: i, dx: 1, edx: o, y: s, ey: c, x: a, ex: u, w: n, h: r } }, ad.prototype.calibrate = function (t) { return new ad({ left: this.left + t.left * this.width, top: this.top + t.top * this.height, right: this.right + t.right * this.width, bottom: this.bottom + t.bottom * this.height }).toSquare().round() }, ad); function ad(t, e) { void 0 === e && (e = !0); var n = t || {}, r = [n.left, n.top, n.right, n.bottom].every(td), o = [n.x, n.y, n.width, n.height].every(td); if (!o && !r) throw new Error("Box.constructor - expected box to be IBoundingBox | IRect, instead have " + JSON.stringify(n)); var i = o ? [n.x, n.y, n.width, n.height] : [n.left, n.top, n.right - n.left, n.bottom - n.top], a = i[0], s = i[1], u = i[2], c = i[3]; ad.assertIsValidBox({ x: a, y: s, width: u, height: c }, "Box.constructor", e), this._x = a, this._y = s, this._width = u, this._height = c } var sd, ud = (Pp(cd, sd = id), cd); function cd(t, e, n, r, o) { return void 0 === o && (o = !1), sd.call(this, { left: t, top: e, right: n, bottom: r }, o) || this } var ld = (Object.defineProperty(hd.prototype, "score", { get: function () { return this._score }, enumerable: !0, configurable: !0 }), Object.defineProperty(hd.prototype, "classScore", { get: function () { return this._classScore }, enumerable: !0, configurable: !0 }), Object.defineProperty(hd.prototype, "className", { get: function () { return this._className }, enumerable: !0, configurable: !0 }), Object.defineProperty(hd.prototype, "box", { get: function () { return this._box }, enumerable: !0, configurable: !0 }), Object.defineProperty(hd.prototype, "imageDims", { get: function () { return this._imageDims }, enumerable: !0, configurable: !0 }), Object.defineProperty(hd.prototype, "imageWidth", { get: function () { return this.imageDims.width }, enumerable: !0, configurable: !0 }), Object.defineProperty(hd.prototype, "imageHeight", { get: function () { return this.imageDims.height }, enumerable: !0, configurable: !0 }), Object.defineProperty(hd.prototype, "relativeBox", { get: function () { return new id(this._box).rescale(this.imageDims.reverse()) }, enumerable: !0, configurable: !0 }), hd.prototype.forSize = function (t, e) { return new hd(this.score, this.classScore, this.className, this.relativeBox, { width: t, height: e }) }, hd); function hd(t, e, n, r, o) { this._imageDims = new Up(o.width, o.height), this._score = t, this._classScore = e, this._className = n, this._box = new id(r).rescale(this._imageDims) } var fd, pd = (Pp(dd, fd = ld), dd.prototype.forSize = function (t, e) { var n = fd.prototype.forSize.call(this, t, e); return new dd(n.score, n.relativeBox, n.imageDims) }, dd); function dd(t, e, n) { return fd.call(this, t, t, "", e, n) || this } function vd(t, e, n) { void 0 === n && (n = !0); var r = Math.max(0, Math.min(t.right, e.right) - Math.max(t.left, e.left)) * Math.max(0, Math.min(t.bottom, e.bottom) - Math.max(t.top, e.top)); return n ? r / (t.area + e.area - r) : r / Math.min(t.area, e.area) } function md(t) { var e = t.map(function (t) { return t.x }), n = t.map(function (t) { return t.y }), r = e.reduce(function (t, e) { return e < t ? e : t }, 1 / 0), o = n.reduce(function (t, e) { return e < t ? e : t }, 1 / 0), i = e.reduce(function (t, e) { return t < e ? e : t }, 0), a = n.reduce(function (t, e) { return t < e ? e : t }, 0); return new ud(r, o, i, a) } function gd(s, t, u, c) { void 0 === c && (c = !0); for (var l = t.map(function (t, e) { return { score: t, boxIndex: e } }).sort(function (t, e) { return t.score - e.score }).map(function (t) { return t.boxIndex }), h = [], e = function () { var t = l.pop(); h.push(t); for (var e = l, n = [], r = 0; r < e.length; r++) { var o = e[r], i = s[t], a = s[o]; n.push(vd(i, a, c)) } l = l.filter(function (t, e) { return n[e] <= u }) }; 0 < l.length;)e(); return h } function yd(s, u) { return nn(function () { var t = u[0], e = u[1], n = u[2], r = Bn(zp(s.shape.slice(0, 3), [1]), t), o = Bn(zp(s.shape.slice(0, 3), [1]), e), i = Bn(zp(s.shape.slice(0, 3), [1]), n), a = Vn([r, o, i], 3); return tc(s, a) }) } function xd(l, h) { return void 0 === h && (h = !1), nn(function () { var t = l.shape.slice(1), e = t[0], n = t[1]; if (e === n) return l; function r(t) { var e = l.shape.slice(); return e[a] = t, Bn(e, 0) } var o = Math.abs(e - n), i = Math.round(o * (h ? .5 : 1)), a = n < e ? 2 : 1, s = r(i), u = o - s.shape[a], c = [h && u ? r(u) : null, l, s].filter(function (t) { return !!t }).map(function (t) { return t.toFloat() }); return Vn(c, a) }) } function bd(t) { return 1 / (1 + Math.exp(-t)) } var wd, Cd = (Pp(Ed, wd = id), Ed); function Ed(t, e, n, r, o) { return void 0 === o && (o = !1), wd.call(this, { x: t, y: e, width: n, height: r }, o) || this } var _d = (Object.defineProperty(Id.prototype, "shift", { get: function () { return new rd(this._shift.x, this._shift.y) }, enumerable: !0, configurable: !0 }), Object.defineProperty(Id.prototype, "imageWidth", { get: function () { return this._imgDims.width }, enumerable: !0, configurable: !0 }), Object.defineProperty(Id.prototype, "imageHeight", { get: function () { return this._imgDims.height }, enumerable: !0, configurable: !0 }), Object.defineProperty(Id.prototype, "positions", { get: function () { return this._positions }, enumerable: !0, configurable: !0 }), Object.defineProperty(Id.prototype, "relativePositions", { get: function () { var e = this; return this._positions.map(function (t) { return t.sub(e._shift).div(new rd(e.imageWidth, e.imageHeight)) }) }, enumerable: !0, configurable: !0 }), Id.prototype.forSize = function (t, e) { return new this.constructor(this.relativePositions, { width: t, height: e }) }, Id.prototype.shiftBy = function (t, e) { return new this.constructor(this.relativePositions, this._imgDims, new rd(t, e)) }, Id.prototype.shiftByPoint = function (t) { return this.shiftBy(t.x, t.y) }, Id.prototype.align = function (t, e) { if (void 0 === e && (e = {}), t) { var n = t instanceof pd ? t.box.floor() : new id(t); return this.shiftBy(n.x, n.y).align(null, e) } var r = Object.assign({}, { useDlibAlignment: !1, minBoxPadding: .2 }, e), o = r.useDlibAlignment, i = r.minBoxPadding; return o ? this.alignDlib() : this.alignMinBbox(i) }, Id.prototype.alignDlib = function () { function t(t) { return o.sub(t).magnitude() } var e = this.getRefPointsForAlignment(), n = e[0], r = e[1], o = e[2], i = (t(n) + t(r)) / 2, a = Math.floor(i / .45), s = Qp(e), u = Math.floor(Math.max(0, s.x - .5 * a)), c = Math.floor(Math.max(0, s.y - .43 * a)); return new Cd(u, c, Math.min(a, this.imageWidth + u), Math.min(a, this.imageHeight + c)) }, Id.prototype.alignMinBbox = function (t) { var e = md(this.positions); return e.pad(e.width * t, e.height * t) }, Id.prototype.getRefPointsForAlignment = function () { throw new Error("getRefPointsForAlignment not implemented by base class") }, Id); function Id(t, e, n) { void 0 === n && (n = new rd(0, 0)); var r = e.width, o = e.height; this._imgDims = new Up(r, o), this._shift = n, this._positions = t.map(function (t) { return t.mul(new rd(r, o)).add(n) }) } var Rd, kd = (Pp(Sd, Rd = _d), Sd.prototype.getRefPointsForAlignment = function () { var t = this.positions; return [t[0], t[1], Qp([t[3], t[4]])] }, Sd); function Sd() { return null !== Rd && Rd.apply(this, arguments) || this } var Dd, Ad = (Pp(Td, Dd = _d), Td.prototype.getJawOutline = function () { return this.positions.slice(0, 17) }, Td.prototype.getLeftEyeBrow = function () { return this.positions.slice(17, 22) }, Td.prototype.getRightEyeBrow = function () { return this.positions.slice(22, 27) }, Td.prototype.getNose = function () { return this.positions.slice(27, 36) }, Td.prototype.getLeftEye = function () { return this.positions.slice(36, 42) }, Td.prototype.getRightEye = function () { return this.positions.slice(42, 48) }, Td.prototype.getMouth = function () { return this.positions.slice(48, 68) }, Td.prototype.getRefPointsForAlignment = function () { return [this.getLeftEye(), this.getRightEye(), this.getMouth()].map(Qp) }, Td); function Td() { return null !== Dd && Dd.apply(this, arguments) || this } var Nd = (Object.defineProperty(Fd.prototype, "label", { get: function () { return this._label }, enumerable: !0, configurable: !0 }), Object.defineProperty(Fd.prototype, "distance", { get: function () { return this._distance }, enumerable: !0, configurable: !0 }), Fd.prototype.toString = function (t) { return void 0 === t && (t = !0), this.label + (t ? " (" + Yp(this.distance) + ")" : "") }, Fd); function Fd(t, e) { this._label = t, this._distance = e } var Md, Od = (Pp(Pd, Md = id), Pd.assertIsValidLabeledBox = function (t, e) { if (id.assertIsValidBox(t, e), !td(t.label)) throw new Error(e + " - expected property label (" + t.label + ") to be a number") }, Object.defineProperty(Pd.prototype, "label", { get: function () { return this._label }, enumerable: !0, configurable: !0 }), Pd); function Pd(t, e) { var n = Md.call(this, t) || this; return n._label = e, n } var Bd = (Object.defineProperty(Ld.prototype, "label", { get: function () { return this._label }, enumerable: !0, configurable: !0 }), Object.defineProperty(Ld.prototype, "descriptors", { get: function () { return this._descriptors }, enumerable: !0, configurable: !0 }), Ld.prototype.toJSON = function () { return { label: this.label, descriptors: this.descriptors.map(function (t) { return Array.from(t) }) } }, Ld.fromJSON = function (t) { var e = t.descriptors.map(function (t) { return new Float32Array(t) }); return new Ld(t.label, e) }, Ld); function Ld(t, e) { if ("string" != typeof t) throw new Error("LabeledFaceDescriptors - constructor expected label to be a string"); if (!Array.isArray(e) || e.some(function (t) { return !(t instanceof Float32Array) })) throw new Error("LabeledFaceDescriptors - constructor expected descriptors to be an array of Float32Array"); this._label = t, this._descriptors = e } var Wd, zd, Ud = (Pp(Vd, Wd = Od), Vd.assertIsValidPredictedBox = function (t, e) { if (Od.assertIsValidLabeledBox(t, e), !ed(t.score) || !ed(t.classScore)) throw new Error(e + " - expected properties score (" + t.score + ") and (" + t.classScore + ") to be a number between [0, 1]") }, Object.defineProperty(Vd.prototype, "score", { get: function () { return this._score }, enumerable: !0, configurable: !0 }), Object.defineProperty(Vd.prototype, "classScore", { get: function () { return this._classScore }, enumerable: !0, configurable: !0 }), Vd); function Vd(t, e, n, r) { var o = Wd.call(this, t, e) || this; return o._score = n, o._classScore = r, o } function Gd(t) { return t.detection instanceof pd } function Hd(t, e) { var n = { detection: e }; return Object.assign({}, t, n) } function qd() { var t = window.fetch || function () { throw new Error("fetch - missing fetch implementation for browser environment") }; return { Canvas: HTMLCanvasElement, CanvasRenderingContext2D: CanvasRenderingContext2D, Image: HTMLImageElement, ImageData: ImageData, Video: HTMLVideoElement, createCanvasElement: function () { return document.createElement("canvas") }, createImageElement: function () { return document.createElement("img") }, fetch: t, readFile: function () { throw new Error("readFile - filesystem not available for browser environment") } } } function jd(e) { var n = ""; if (!e) try { e = require("fs") } catch (t) { n = t.toString() } return { readFile: e ? function (t) { return new Promise(function (n, r) { e.readFile(t, function (t, e) { return t ? r(t) : n(e) }) }) } : function () { throw new Error("readFile - failed to require fs in nodejs environment with error: " + n) } } } function Kd() { var t = global.Canvas || global.HTMLCanvasElement, e = global.Image || global.HTMLImageElement, n = global.fetch || function () { throw new Error("fetch - missing fetch implementation for nodejs environment") }, r = jd(); return Bp({ Canvas: t || function () { }, CanvasRenderingContext2D: global.CanvasRenderingContext2D || function () { }, Image: e || function () { }, ImageData: global.ImageData || function () { }, Video: global.HTMLVideoElement || function () { }, createCanvasElement: function () { if (t) return new t; throw new Error("createCanvasElement - missing Canvas implementation for nodejs environment") }, createImageElement: function () { if (e) return new e; throw new Error("createImageElement - missing Image implementation for nodejs environment") }, fetch: n }, r) } function Xd() { return "object" == typeof window && "undefined" != typeof document && "undefined" != typeof HTMLImageElement && "undefined" != typeof HTMLCanvasElement && "undefined" != typeof HTMLVideoElement && "undefined" != typeof ImageData && "undefined" != typeof CanvasRenderingContext2D } function Yd() { return "object" == typeof global && "function" == typeof require && "undefined" != typeof module && "undefined" != typeof process && !!process.version } function $d(t) { zd = t } function Jd() { Xd() && $d(qd()), Yd() && $d(Kd()) } var Qd, Zd, tv = { getEnv: function () { if (!zd) throw new Error("getEnv - environment is not defined, check isNodejs() and isBrowser()"); return zd }, setEnv: $d, initialize: Jd, createBrowserEnv: qd, createFileSystem: jd, createNodejsEnv: Kd, monkeyPatch: function (t) { if (zd || Jd(), !zd) throw new Error("monkeyPatch - environment is not defined, check isNodejs() and isBrowser()"); var e = t.Canvas, n = void 0 === e ? zd.Canvas : e, r = t.Image, o = void 0 === r ? zd.Image : r; zd.Canvas = n, zd.Image = o, zd.createCanvasElement = t.createCanvasElement || function () { return new n }, zd.createImageElement = t.createImageElement || function () { return new o }, zd.ImageData = t.ImageData || zd.ImageData, zd.Video = t.Video || zd.Video, zd.fetch = t.fetch || zd.fetch, zd.readFile = t.readFile || zd.readFile }, isBrowser: Xd, isNodejs: Yd }; function ev(t) { return tv.isNodejs() || "string" != typeof t ? t : document.getElementById(t) } function nv(t) { var e = tv.getEnv(), n = e.Canvas; if (t instanceof e.CanvasRenderingContext2D) return t; var r = ev(t); if (!(r instanceof n)) throw new Error("resolveContext2d - expected canvas to be of instance of Canvas"); var o = r.getContext("2d"); if (!o) throw new Error("resolveContext2d - canvas 2d context is null"); return o } Jd(), (Zd = Qd = Qd || {}).TOP_LEFT = "TOP_LEFT", Zd.TOP_RIGHT = "TOP_RIGHT", Zd.BOTTOM_LEFT = "BOTTOM_LEFT", Zd.BOTTOM_RIGHT = "BOTTOM_RIGHT"; var rv = function (t) { void 0 === t && (t = {}); var e = t.anchorPosition, n = t.backgroundColor, r = t.fontColor, o = t.fontSize, i = t.fontStyle, a = t.padding; this.anchorPosition = e || Qd.TOP_LEFT, this.backgroundColor = n || "rgba(0, 0, 0, 0.5)", this.fontColor = r || "rgba(255, 255, 255, 1)", this.fontSize = o || 14, this.fontStyle = i || "Georgia", this.padding = a || 4 }, ov = (iv.prototype.measureWidth = function (e) { var t = this.options.padding; return this.text.map(function (t) { return e.measureText(t).width }).reduce(function (t, e) { return t < e ? e : t }, 0) + 2 * t }, iv.prototype.measureHeight = function () { var t = this.options, e = t.fontSize, n = t.padding; return this.text.length * e + 2 * n }, iv.prototype.getUpperLeft = function (t, e) { var n = this.options.anchorPosition, r = n === Qd.BOTTOM_RIGHT || n === Qd.TOP_RIGHT, o = n === Qd.BOTTOM_LEFT || n === Qd.BOTTOM_RIGHT, i = this.measureWidth(t), a = this.measureHeight(), s = r ? this.anchor.x - i : this.anchor.x, u = o ? this.anchor.y - a : this.anchor.y; if (e) { var c = e.width, l = e.height; return { x: Math.max(Math.min(s, c - i), 0), y: Math.max(Math.min(u, l - a), 0) } } return { x: s, y: u } }, iv.prototype.draw = function (t) { var e = ev(t), o = nv(e), n = this.options, r = n.backgroundColor, i = n.fontColor, a = n.fontSize, s = n.fontStyle, u = n.padding; o.font = a + "px " + s; var c = this.measureWidth(o), l = this.measureHeight(); o.fillStyle = r; var h = this.getUpperLeft(o, e); o.fillRect(h.x, h.y, c, l), o.fillStyle = i, this.text.forEach(function (t, e) { var n = u + h.x, r = u + h.y + (e + 1) * a; o.fillText(t, n, r) }) }, iv); function iv(t, e, n) { void 0 === n && (n = {}), this.text = "string" == typeof t ? [t] : t instanceof iv ? t.text : t, this.anchor = e, this.options = new rv(n) } var av = function (t) { void 0 === t && (t = {}); var e = t.boxColor, n = t.lineWidth, r = t.label, o = t.drawLabelOptions; this.boxColor = e || "rgba(0, 0, 255, 1)", this.lineWidth = n || 2, this.label = r; var i = { anchorPosition: Qd.BOTTOM_LEFT, backgroundColor: this.boxColor }; this.drawLabelOptions = new rv(Object.assign({}, i, o)) }, sv = (uv.prototype.draw = function (t) { var e = nv(t), n = this.options, r = n.boxColor, o = n.lineWidth, i = this.box, a = i.x, s = i.y, u = i.width, c = i.height; e.strokeStyle = r, e.lineWidth = o, e.strokeRect(a, s, u, c); var l = this.options.label; l && new ov([l], { x: a - o / 2, y: s }, this.options.drawLabelOptions).draw(t) }, uv); function uv(t, e) { void 0 === e && (e = {}), this.box = new id(t), this.options = new av(e) } function cv(t) { var e = tv.getEnv(), n = e.Image, r = e.Video; return t instanceof n && t.complete || t instanceof r && 3 <= t.readyState } function lv(t) { return new Promise(function (e, n) { if (t instanceof tv.getEnv().Canvas || cv(t)) return e(); function r(t) { t.currentTarget && (t.currentTarget.removeEventListener("load", r), t.currentTarget.removeEventListener("error", o), e(t)) } function o(t) { t.currentTarget && (t.currentTarget.removeEventListener("load", r), t.currentTarget.removeEventListener("error", o), n(t)) } t.addEventListener("load", r), t.addEventListener("error", o) }) } function hv(t) { return new Promise(function (e, n) { if (!(t instanceof Blob)) return n("bufferToImage - expected buf to be of type: Blob"); var r = new FileReader; r.onload = function () { if ("string" != typeof r.result) return n("bufferToImage - expected reader.result to be a string, in onload"); var t = tv.getEnv().createImageElement(); t.onload = function () { return e(t) }, t.onerror = n, t.src = r.result }, r.onerror = n, r.readAsDataURL(t) }) } function fv(t) { var e = tv.getEnv(), n = e.Image, r = e.Video; return t instanceof n ? new Up(t.naturalWidth, t.naturalHeight) : t instanceof r ? new Up(t.videoWidth, t.videoHeight) : new Up(t.width, t.height) } function pv(t) { var e = t.width, n = t.height, r = (0, tv.getEnv().createCanvasElement)(); return r.width = e, r.height = n, r } function dv(t, e) { var n = tv.getEnv().ImageData; if (!(t instanceof n || cv(t))) throw new Error("createCanvasFromMedia - media has not finished loading yet"); var r = e || fv(t), o = r.width, i = r.height, a = pv({ width: o, height: i }); return t instanceof n ? nv(a).putImageData(t, 0, 0) : nv(a).drawImage(t, 0, 0, o, i), a } function vv(s, u) { return Lp(this, void 0, void 0, function () { var e, n, r, o, i, a; return Wp(this, function (t) { switch (t.label) { case 0: return e = u || tv.getEnv().createCanvasElement(), n = s.shape.slice(jp(s) ? 1 : 0), r = n[0], o = n[1], i = n[2], a = nn(function () { return s.as3D(r, o, i).toInt() }), [4, Kf.toPixels(a, e)]; case 1: return t.sent(), a.dispose(), [2, e] } }) }) } function mv(t) { var e = tv.getEnv(), n = e.Image, r = e.Canvas, o = e.Video; return t instanceof n || t instanceof r || t instanceof o } function gv(t, e, n) { void 0 === n && (n = !1); var r = tv.getEnv(), o = r.Image, i = r.Canvas; if (!(t instanceof o || t instanceof i)) throw new Error("imageToSquare - expected arg0 to be HTMLImageElement | HTMLCanvasElement"); var a = fv(t), s = e / Math.max(a.height, a.width), u = s * a.width, c = s * a.height, l = pv({ width: e, height: e }), h = t instanceof i ? t : dv(t), f = Math.abs(u - c) / 2, p = n && u < c ? f : 0, d = n && c < u ? f : 0; return nv(l).drawImage(h, p, d, u, c), l } var yv = (Object.defineProperty(xv.prototype, "imageTensors", { get: function () { return this._imageTensors }, enumerable: !0, configurable: !0 }), Object.defineProperty(xv.prototype, "canvases", { get: function () { return this._canvases }, enumerable: !0, configurable: !0 }), Object.defineProperty(xv.prototype, "isBatchInput", { get: function () { return 1 < this.batchSize || this._treatAsBatchInput }, enumerable: !0, configurable: !0 }), Object.defineProperty(xv.prototype, "batchSize", { get: function () { return this._batchSize }, enumerable: !0, configurable: !0 }), Object.defineProperty(xv.prototype, "inputDimensions", { get: function () { return this._inputDimensions }, enumerable: !0, configurable: !0 }), Object.defineProperty(xv.prototype, "inputSize", { get: function () { return this._inputSize }, enumerable: !0, configurable: !0 }), Object.defineProperty(xv.prototype, "reshapedInputDimensions", { get: function () { var n = this; return Zp(this.batchSize, 0, 1).map(function (t, e) { return n.getReshapedInputDimensions(e) }) }, enumerable: !0, configurable: !0 }), xv.prototype.getInput = function (t) { return this.canvases[t] || this.imageTensors[t] }, xv.prototype.getInputDimensions = function (t) { return this._inputDimensions[t] }, xv.prototype.getInputHeight = function (t) { return this._inputDimensions[t][0] }, xv.prototype.getInputWidth = function (t) { return this._inputDimensions[t][1] }, xv.prototype.getReshapedInputDimensions = function (t) { if ("number" != typeof this.inputSize) throw new Error("getReshapedInputDimensions - inputSize not set, toBatchTensor has not been called yet"); return Jp({ width: this.getInputWidth(t), height: this.getInputHeight(t) }, this.inputSize) }, xv.prototype.toBatchTensor = function (r, o) { var i = this; return void 0 === o && (o = !0), this._inputSize = r, nn(function () { var t = Zp(i.batchSize, 0, 1).map(function (t) { var e = i.getInput(t); if (e instanceof bt) { var n = jp(e) ? e : e.expandDims(); return (n = xd(n, o)).shape[1] === r && n.shape[2] === r || (n = vh.resizeBilinear(n, [r, r])), n.as3D(r, r, 3) } if (e instanceof tv.getEnv().Canvas) return Kf.fromPixels(gv(e, r, o)); throw new Error("toBatchTensor - at batchIdx " + t + ", expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have " + e) }); return Mr(t.map(function (t) { return t.toFloat() })).as4D(i.batchSize, r, r, 3) }) }, xv); function xv(t, e) { var o = this; if (void 0 === e && (e = !1), this._imageTensors = [], this._canvases = [], this._treatAsBatchInput = !1, this._inputDimensions = [], !Array.isArray(t)) throw new Error("NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have " + t); this._treatAsBatchInput = e, this._batchSize = t.length, t.forEach(function (t, e) { if (qp(t)) return o._imageTensors[e] = t, void (o._inputDimensions[e] = t.shape); if (jp(t)) { var n = t.shape[0]; if (1 !== n) throw new Error("NetInput - tf.Tensor4D with batchSize " + n + " passed, but not supported in input array"); return o._imageTensors[e] = t, void (o._inputDimensions[e] = t.shape.slice(1)) } var r = t instanceof tv.getEnv().Canvas ? t : dv(t); o._canvases[e] = r, o._inputDimensions[e] = [r.height, r.width, 3] }) } function bv(n) { return Lp(this, void 0, void 0, function () { var r, o, e; return Wp(this, function (t) { switch (t.label) { case 0: if (n instanceof yv) return [2, n]; if (!(r = Array.isArray(n) ? n : [n]).length) throw new Error("toNetInput - empty array passed as input"); return o = function (t) { return Array.isArray(n) ? " at input index " + t + ":" : "" }, (e = r.map(ev)).forEach(function (t, e) { if (!mv(t) && !qp(t) && !jp(t)) { if ("string" == typeof r[e]) throw new Error("toNetInput -" + o(e) + " string passed, but could not resolve HTMLElement for element id " + r[e]); throw new Error("toNetInput -" + o(e) + " expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id") } if (jp(t)) { var n = t.shape[0]; if (1 !== n) throw new Error("toNetInput -" + o(e) + " tf.Tensor4D with batchSize " + n + " passed, but not supported in input array") } }), [4, Promise.all(e.map(function (t) { return mv(t) && lv(t) }))]; case 1: return t.sent(), [2, new yv(e, Array.isArray(n))] } }) }) } function wv(s, u) { return Lp(this, void 0, void 0, function () { var e, n, r, o, i, a; return Wp(this, function (t) { switch (t.label) { case 0: return e = tv.getEnv().Canvas, (n = s) instanceof e ? [3, 5] : [4, bv(s)]; case 1: if (1 < (r = t.sent()).batchSize) throw new Error("extractFaces - batchSize > 1 not supported"); return (o = r.getInput(0)) instanceof e ? (i = o, [3, 4]) : [3, 2]; case 2: return [4, vv(o)]; case 3: i = t.sent(), t.label = 4; case 4: n = i, t.label = 5; case 5: return a = nv(n), [2, u.map(function (t) { return t instanceof pd ? t.forSize(n.width, n.height).box.floor() : t }).map(function (t) { return t.clipAtImageBorders(n.width, n.height) }).map(function (t) { var e = t.x, n = t.y, r = t.width, o = t.height, i = pv({ width: r, height: o }); return nv(i).putImageData(a.getImageData(e, n, r, o), 0, 0), i })] } }) }) } function Cv(u, e) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { if (!qp(u) && !jp(u)) throw new Error("extractFaceTensors - expected image tensor to be 3D or 4D"); if (jp(u) && 1 < u.shape[0]) throw new Error("extractFaceTensors - batchSize > 1 not supported"); return [2, nn(function () { var t = u.shape.slice(jp(u) ? 1 : 0), i = t[0], a = t[1], s = t[2]; return e.map(function (t) { return t instanceof pd ? t.forSize(a, i).box : t }).map(function (t) { return t.clipAtImageBorders(a, i) }).map(function (t) { var e = t.x, n = t.y, r = t.width, o = t.height; return Jc(u.as3D(i, a, s), [n, e, 0], [o, r, s]) }) })] }) }) } function Ev(n, r) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return [4, (0, tv.getEnv().fetch)(n, r)]; case 1: if (!((e = t.sent()).status < 400)) throw new Error("failed to fetch: (" + e.status + ") " + e.statusText + ", from url: " + e.url); return [2, e] } }) }) } function _v(e) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return [4, Ev(e)]; case 1: return [2, t.sent().json()] } }) }) } function Iv(t, e) { var n = e + "-weights_manifest.json"; if (!t) return { modelBaseUri: "", manifestUri: n }; if ("/" === t) return { modelBaseUri: "/", manifestUri: "/" + n }; var r = t.startsWith("http://") ? "http://" : t.startsWith("https://") ? "https://" : "", o = (t = t.replace(r, "")).split("/").filter(function (t) { return t }), i = t.endsWith(".json") ? o[o.length - 1] : n, a = r + (t.endsWith(".json") ? o.slice(0, o.length - 1) : o).join("/"); return { modelBaseUri: a = t.startsWith("/") ? "/" + a : a, manifestUri: "/" === a ? "/" + i : a + "/" + i } } function Rv(i, a) { return Lp(this, void 0, void 0, function () { var e, n, r, o; return Wp(this, function (t) { switch (t.label) { case 0: return e = Iv(i, a), n = e.manifestUri, r = e.modelBaseUri, [4, _v(n)]; case 1: return o = t.sent(), [2, Gf.loadWeights(o, r)] } }) }) } var kv = (Object.defineProperty(Sv.prototype, "params", { get: function () { return this._params }, enumerable: !0, configurable: !0 }), Object.defineProperty(Sv.prototype, "paramMappings", { get: function () { return this._paramMappings }, enumerable: !0, configurable: !0 }), Object.defineProperty(Sv.prototype, "isLoaded", { get: function () { return !!this.params }, enumerable: !0, configurable: !0 }), Sv.prototype.getParamFromPath = function (t) { var e = this.traversePropertyPath(t); return e.obj[e.objProp] }, Sv.prototype.reassignParamFromPath = function (t, e) { var n = this.traversePropertyPath(t), r = n.obj, o = n.objProp; r[o].dispose(), r[o] = e }, Sv.prototype.getParamList = function () { var n = this; return this._paramMappings.map(function (t) { var e = t.paramPath; return { path: e, tensor: n.getParamFromPath(e) } }) }, Sv.prototype.getTrainableParams = function () { return this.getParamList().filter(function (t) { return t.tensor instanceof Ft }) }, Sv.prototype.getFrozenParams = function () { return this.getParamList().filter(function (t) { return !(t.tensor instanceof Ft) }) }, Sv.prototype.variable = function () { var r = this; this.getFrozenParams().forEach(function (t) { var e = t.path, n = t.tensor; r.reassignParamFromPath(e, n.variable()) }) }, Sv.prototype.freeze = function () { var o = this; this.getTrainableParams().forEach(function (t) { var e = t.path, n = t.tensor, r = In(n.dataSync()); n.dispose(), o.reassignParamFromPath(e, r) }) }, Sv.prototype.dispose = function (e) { void 0 === e && (e = !0), this.getParamList().forEach(function (t) { if (e && t.tensor.isDisposed) throw new Error("param tensor has already been disposed for path " + t.path); t.tensor.dispose() }), this._params = void 0 }, Sv.prototype.serializeParams = function () { return new Float32Array(this.getParamList().map(function (t) { var e = t.tensor; return Array.from(e.dataSync()) }).reduce(function (t, e) { return t.concat(e) })) }, Sv.prototype.load = function (e) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return e instanceof Float32Array ? (this.extractWeights(e), [2]) : [4, this.loadFromUri(e)]; case 1: return t.sent(), [2] } }) }) }, Sv.prototype.loadFromUri = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: if (n && "string" != typeof n) throw new Error(this._name + ".loadFromUri - expected model uri"); return [4, Rv(n, this.getDefaultModelName())]; case 1: return e = t.sent(), this.loadFromWeightMap(e), [2] } }) }) }, Sv.prototype.loadFromDisk = function (h) { return Lp(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l; return Wp(this, function (t) { switch (t.label) { case 0: if (h && "string" != typeof h) throw new Error(this._name + ".loadFromDisk - expected model file path"); return e = tv.getEnv().readFile, n = Iv(h, this.getDefaultModelName()), r = n.manifestUri, o = n.modelBaseUri, i = function (t) { return Promise.all(t.map(function (t) { return e(t).then(function (t) { return t.buffer }) })) }, a = Gf.weightsLoaderFactory(i), c = (u = JSON).parse, [4, e(r)]; case 1: return s = c.apply(u, [t.sent().toString()]), [4, a(s, o)]; case 2: return l = t.sent(), this.loadFromWeightMap(l), [2] } }) }) }, Sv.prototype.loadFromWeightMap = function (t) { var e = this.extractParamsFromWeigthMap(t), n = e.paramMappings, r = e.params; this._paramMappings = n, this._params = r }, Sv.prototype.extractWeights = function (t) { var e = this.extractParams(t), n = e.paramMappings, r = e.params; this._paramMappings = n, this._params = r }, Sv.prototype.traversePropertyPath = function (n) { if (!this.params) throw new Error("traversePropertyPath - model has no loaded params"); var t = n.split("/").reduce(function (t, e) { if (!t.nextObj.hasOwnProperty(e)) throw new Error("traversePropertyPath - object does not have property " + e + ", for path " + n); return { obj: t.nextObj, objProp: e, nextObj: t.nextObj[e] } }, { nextObj: this.params }), e = t.obj, r = t.objProp; if (!(e && r && e[r] instanceof bt)) throw new Error("traversePropertyPath - parameter is not a tensor, for path " + n); return { obj: e, objProp: r } }, Sv); function Sv(t) { this._name = t, this._params = void 0, this._paramMappings = [] } function Dv(e, n, r) { return nn(function () { var t = Ac(e, n.depthwise_filter, n.pointwise_filter, r, "same"); return t = Ou(t, n.bias) }) } function Av(r, o, i) { return void 0 === i && (i = !1), nn(function () { var t = dl(i ? Ou(Ec(r, o.conv0.filters, [2, 2], "same"), o.conv0.bias) : Dv(r, o.conv0, [2, 2])), e = Dv(t, o.conv1, [1, 1]), n = Dv(dl(Ou(t, e)), o.conv2, [1, 1]); return dl(Ou(t, Ou(e, n))) }) } function Tv(o, i, a, s) { return void 0 === a && (a = !1), void 0 === s && (s = !0), nn(function () { var t = dl(a ? Ou(Ec(o, i.conv0.filters, s ? [2, 2] : [1, 1], "same"), i.conv0.bias) : Dv(o, i.conv0, s ? [2, 2] : [1, 1])), e = Dv(t, i.conv1, [1, 1]), n = Dv(dl(Ou(t, e)), i.conv2, [1, 1]), r = Dv(dl(Ou(t, Ou(e, n))), i.conv3, [1, 1]); return dl(Ou(t, Ou(e, Ou(n, r)))) }) } function Nv(e, n, r, o) { return void 0 === r && (r = "same"), void 0 === o && (o = !1), nn(function () { var t = Ou(Ec(e, n.filters, [1, 1], r), n.bias); return o ? dl(t) : t }) } function Fv(t, n) { Object.keys(t).forEach(function (e) { n.some(function (t) { return t.originalPath === e }) || t[e].dispose() }) } function Mv(a, s) { return function (t, e, n, r) { var o = Tn(a(t * e * n * n), [n, n, t, e]), i = Sn(a(e)); return s.push({ paramPath: r + "/filters" }, { paramPath: r + "/bias" }), { filters: o, bias: i } } } function Ov(i, a) { return function (t, e, n) { var r = Dn(i(t * e), [t, e]), o = Sn(i(e)); return a.push({ paramPath: n + "/weights" }, { paramPath: n + "/bias" }), { weights: r, bias: o } } } var Pv = function (t, e, n) { this.depthwise_filter = t, this.pointwise_filter = e, this.bias = n }; function Bv(a, s) { return function (t, e, n) { var r = Tn(a(9 * t), [3, 3, t, 1]), o = Tn(a(t * e), [1, 1, t, e]), i = Sn(a(e)); return s.push({ paramPath: n + "/depthwise_filter" }, { paramPath: n + "/pointwise_filter" }, { paramPath: n + "/bias" }), new Pv(r, o, i) } } function Lv(o) { return function (t) { var e = o(t + "/depthwise_filter", 4), n = o(t + "/pointwise_filter", 4), r = o(t + "/bias", 1); return new Pv(e, n, r) } } function Wv(o, i) { return function (t, e, n) { var r = o[t]; if (!Gp(r, e)) throw new Error("expected weightMap[" + t + "] to be a Tensor" + e + "D, instead have " + r); return i.push({ originalPath: t, paramPath: n || t }), r } } function zv(t) { var n = t; return { extractWeights: function (t) { var e = n.slice(0, t); return n = n.slice(t), e }, getRemainingWeights: function () { return n } } } function Uv(t, e) { var o = Mv(t, e), i = Bv(t, e); function a(t, e, n, r) { return void 0 === r && (r = !1), { conv0: r ? o(t, e, 3, n + "/conv0") : i(t, e, n + "/conv0"), conv1: i(e, e, n + "/conv1"), conv2: i(e, e, n + "/conv2") } } return { extractDenseBlock3Params: a, extractDenseBlock4Params: function (t, e, n, r) { void 0 === r && (r = !1); var o = a(t, e, n, r); return { conv0: o.conv0, conv1: o.conv1, conv2: o.conv2, conv3: i(e, e, n + "/conv3") } } } } function Vv(e) { return function (t) { return { filters: e(t + "/filters", 4), bias: e(t + "/bias", 1) } } } function Gv(t, e) { var n = Wv(t, e), r = Vv(n), o = Lv(n); return { extractDenseBlock3Params: function (t, e) { return void 0 === e && (e = !1), { conv0: e ? r(t + "/conv0") : o(t + "/conv0"), conv1: o(t + "/conv1"), conv2: o(t + "/conv2") } }, extractDenseBlock4Params: function (t, e) { return void 0 === e && (e = !1), { conv0: e ? r(t + "/conv0") : o(t + "/conv0"), conv1: o(t + "/conv1"), conv2: o(t + "/conv2"), conv3: o(t + "/conv3") } } } } var Hv, qv = (Pp(jv, Hv = kv), jv.prototype.forwardInput = function (e) { var n = this.params; if (!n) throw new Error("FaceFeatureExtractor - load model before inference"); return nn(function () { var t = Tv(yd(e.toBatchTensor(112, !0), [122.782, 117.001, 104.298]).div(kn(255)), n.dense0, !0); return t = Tv(t = Tv(t = Tv(t, n.dense1), n.dense2), n.dense3), t = Hc(t, [7, 7], [2, 2], "valid") }) }, jv.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, jv.prototype.getDefaultModelName = function () { return "face_feature_extractor_model" }, jv.prototype.extractParamsFromWeigthMap = function (t) { return function (t) { var e = [], n = Gv(t, e).extractDenseBlock4Params, r = { dense0: n("dense0", !0), dense1: n("dense1"), dense2: n("dense2"), dense3: n("dense3") }; return Fv(t, e), { params: r, paramMappings: e } }(t) }, jv.prototype.extractParams = function (t) { return function (t) { var e = [], n = zv(t), r = n.extractWeights, o = n.getRemainingWeights, i = Uv(r, e).extractDenseBlock4Params, a = i(3, 32, "dense0", !0), s = i(32, 64, "dense1"), u = i(64, 128, "dense2"), c = i(128, 256, "dense3"); if (0 !== o().length) throw new Error("weights remaing after extract: " + o().length); return { paramMappings: e, params: { dense0: a, dense1: s, dense2: u, dense3: c } } }(t) }, jv); function jv() { return Hv.call(this, "FaceFeatureExtractor") || this } function Kv(t, e) { return nn(function () { return Ou(Fc(t, e.weights), e.bias) }) } function Xv(e) { var n = {}, r = {}; return Object.keys(e).forEach(function (t) { (t.startsWith("fc") ? r : n)[t] = e[t] }), { featureExtractorMap: n, classifierMap: r } } var Yv, $v = (Pp(Jv, Yv = kv), Object.defineProperty(Jv.prototype, "faceFeatureExtractor", { get: function () { return this._faceFeatureExtractor }, enumerable: !0, configurable: !0 }), Jv.prototype.runNet = function (e) { var n = this, r = this.params; if (!r) throw new Error(this._name + " - load model before inference"); return nn(function () { var t = e instanceof yv ? n.faceFeatureExtractor.forwardInput(e) : e; return Kv(t.as2D(t.shape[0], -1), r.fc) }) }, Jv.prototype.dispose = function (t) { void 0 === t && (t = !0), this.faceFeatureExtractor.dispose(t), Yv.prototype.dispose.call(this, t) }, Jv.prototype.loadClassifierParams = function (t) { var e = this.extractClassifierParams(t), n = e.params, r = e.paramMappings; this._params = n, this._paramMappings = r }, Jv.prototype.extractClassifierParams = function (t) { return function (t, e, n) { var r = [], o = zv(t), i = o.extractWeights, a = o.getRemainingWeights, s = Ov(i, r)(e, n, "fc"); if (0 !== a().length) throw new Error("weights remaing after extract: " + a().length); return { paramMappings: r, params: { fc: s } } }(t, this.getClassifierChannelsIn(), this.getClassifierChannelsOut()) }, Jv.prototype.extractParamsFromWeigthMap = function (t) { var e = Xv(t), n = e.featureExtractorMap, r = e.classifierMap; return this.faceFeatureExtractor.loadFromWeightMap(n), function (t) { var e, n = [], r = Wv(t, n), o = { fc: (e = "fc", { weights: r(e + "/weights", 2), bias: r(e + "/bias", 1) }) }; return Fv(t, n), { params: o, paramMappings: n } }(r) }, Jv.prototype.extractParams = function (t) { var e = this.getClassifierChannelsIn(), n = this.getClassifierChannelsOut(), r = n * e + n, o = t.slice(0, t.length - r), i = t.slice(t.length - r); return this.faceFeatureExtractor.extractWeights(o), this.extractClassifierParams(i) }, Jv); function Jv(t, e) { var n = Yv.call(this, t) || this; return n._faceFeatureExtractor = e, n } var Qv = ["neutral", "happy", "sad", "angry", "fearful", "disgusted", "surprised"], Zv = (tm.prototype.asSortedArray = function () { var e = this; return Qv.map(function (t) { return { expression: t, probability: e[t] } }).sort(function (t, e) { return e.probability - t.probability }) }, tm); function tm(n) { var r = this; if (7 !== n.length) throw new Error("FaceExpressions.constructor - expected probabilities.length to be 7, have: " + n.length); Qv.forEach(function (t, e) { r[t] = n[e] }) } var em, nm = (Pp(rm, em = $v), rm.prototype.forwardInput = function (t) { var e = this; return nn(function () { return so(e.runNet(t)) }) }, rm.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, rm.prototype.predictExpressions = function (a) { return Lp(this, void 0, void 0, function () { var e, n, r, o, i = this; return Wp(this, function (t) { switch (t.label) { case 0: return [4, bv(a)]; case 1: return e = t.sent(), [4, this.forwardInput(e)]; case 2: return n = t.sent(), [4, Promise.all(Br(n).map(function (n) { return Lp(i, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return [4, n.data()]; case 1: return e = t.sent(), n.dispose(), [2, e] } }) }) }))]; case 3: return r = t.sent(), n.dispose(), o = r.map(function (t) { return new Zv(t) }), [2, e.isBatchInput ? o : o[0]] } }) }) }, rm.prototype.getDefaultModelName = function () { return "face_expression_model" }, rm.prototype.getClassifierChannelsIn = function () { return 256 }, rm.prototype.getClassifierChannelsOut = function () { return 7 }, rm); function rm(t) { return void 0 === t && (t = new qv), em.call(this, "FaceExpressionNet", t) || this } function om(t) { return t.expressions instanceof Zv } function im(t, e) { var n = { expressions: e }; return Object.assign({}, t, n) } function am(t) { return Gd(t) && t.landmarks instanceof _d && t.unshiftedLandmarks instanceof _d && t.alignedRect instanceof pd } function sm(t, e) { var n = t.detection.box, r = e.shiftBy(n.x, n.y), o = r.align(), i = t.detection.imageDims, a = { landmarks: r, unshiftedLandmarks: e, alignedRect: new pd(t.detection.score, o.rescale(i.reverse()), i) }; return Object.assign({}, t, a) } var um = function (t) { void 0 === t && (t = {}); var e = t.drawLines, n = void 0 === e || e, r = t.drawPoints, o = void 0 === r || r, i = t.lineWidth, a = t.lineColor, s = t.pointSize, u = t.pointColor; this.drawLines = n, this.drawPoints = o, this.lineWidth = i || 1, this.pointSize = s || 2, this.lineColor = a || "rgba(0, 255, 255, 1)", this.pointColor = u || "rgba(255, 0, 255, 1)" }, cm = (lm.prototype.draw = function (t) { var e = nv(t), n = this.options, r = n.drawLines, o = n.drawPoints, i = n.lineWidth, a = n.lineColor, s = n.pointSize, u = n.pointColor; r && this.faceLandmarks instanceof Ad && (e.strokeStyle = a, e.lineWidth = i, Mp(e, this.faceLandmarks.getJawOutline()), Mp(e, this.faceLandmarks.getLeftEyeBrow()), Mp(e, this.faceLandmarks.getRightEyeBrow()), Mp(e, this.faceLandmarks.getNose()), Mp(e, this.faceLandmarks.getLeftEye(), !0), Mp(e, this.faceLandmarks.getRightEye(), !0), Mp(e, this.faceLandmarks.getMouth(), !0)), o && (e.strokeStyle = u, e.fillStyle = u, this.faceLandmarks.positions.forEach(function (t) { e.beginPath(), e.arc(t.x, t.y, s, 0, 2 * Math.PI), e.fill() })) }, lm); function lm(t, e) { void 0 === e && (e = {}), this.faceLandmarks = t, this.options = new um(e) } var hm = Object.freeze({ __proto__: null, drawContour: Mp, drawDetections: function (o, t) { (Array.isArray(t) ? t : [t]).forEach(function (t) { var e = t instanceof pd ? t.score : Gd(t) ? t.detection.score : void 0, n = t instanceof pd ? t.box : Gd(t) ? t.detection.box : new id(t), r = e ? "" + Yp(e) : void 0; new sv(n, { label: r }).draw(o) }) }, drawFaceExpressions: function (o, t, i, a) { void 0 === i && (i = .1), (Array.isArray(t) ? t : [t]).forEach(function (t) { var e = t instanceof Zv ? t : om(t) ? t.expressions : void 0; if (!e) throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof"); var n = e.asSortedArray().filter(function (t) { return t.probability > i }), r = Gd(t) ? t.detection.box.bottomLeft : a || new rd(0, 0); new ov(n.map(function (t) { return t.expression + " (" + Yp(t.probability) + ")" }), r).draw(o) }) }, DrawBoxOptions: av, DrawBox: sv, DrawFaceLandmarksOptions: um, DrawFaceLandmarks: cm, drawFaceLandmarks: function (n, t) { (Array.isArray(t) ? t : [t]).forEach(function (t) { var e = t instanceof _d ? t : am(t) ? t.landmarks : void 0; if (!e) throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof"); new cm(e).draw(n) }) }, get AnchorPosition() { return Qd }, DrawTextFieldOptions: rv, DrawTextField: ov }); function fm(t, e) { var n = [], r = zv(t), o = r.extractWeights, i = r.getRemainingWeights, a = function (t, e) { var r = Mv(t, e), o = Bv(t, e); return { extractConvParams: r, extractSeparableConvParams: o, extractReductionBlockParams: function (t, e, n) { return { separable_conv0: o(t, e, n + "/separable_conv0"), separable_conv1: o(e, e, n + "/separable_conv1"), expansion_conv: r(t, e, 1, n + "/expansion_conv") } }, extractMainBlockParams: function (t, e) { return { separable_conv0: o(t, t, e + "/separable_conv0"), separable_conv1: o(t, t, e + "/separable_conv1"), separable_conv2: o(t, t, e + "/separable_conv2") } } } }(o, n), s = a.extractConvParams, u = a.extractSeparableConvParams, c = a.extractReductionBlockParams, l = a.extractMainBlockParams, h = { conv_in: s(3, 32, 3, "entry_flow/conv_in"), reduction_block_0: c(32, 64, "entry_flow/reduction_block_0"), reduction_block_1: c(64, 128, "entry_flow/reduction_block_1") }, f = {}; Zp(e, 0, 1).forEach(function (t) { f["main_block_" + t] = l(128, "middle_flow/main_block_" + t) }); var p = { reduction_block: c(128, 256, "exit_flow/reduction_block"), separable_conv: u(256, 512, "exit_flow/separable_conv") }; if (0 !== i().length) throw new Error("weights remaing after extract: " + i().length); return { paramMappings: n, params: { entry_flow: h, middle_flow: f, exit_flow: p } } } function pm(t, e) { var n = [], r = function (t, e) { var n = Wv(t, e), r = Vv(n), o = Lv(n); return { extractConvParams: r, extractSeparableConvParams: o, extractReductionBlockParams: function (t) { return { separable_conv0: o(t + "/separable_conv0"), separable_conv1: o(t + "/separable_conv1"), expansion_conv: r(t + "/expansion_conv") } }, extractMainBlockParams: function (t) { return { separable_conv0: o(t + "/separable_conv0"), separable_conv1: o(t + "/separable_conv1"), separable_conv2: o(t + "/separable_conv2") } } } }(t, n), o = r.extractConvParams, i = r.extractSeparableConvParams, a = r.extractReductionBlockParams, s = r.extractMainBlockParams, u = { conv_in: o("entry_flow/conv_in"), reduction_block_0: a("entry_flow/reduction_block_0"), reduction_block_1: a("entry_flow/reduction_block_1") }, c = {}; Zp(e, 0, 1).forEach(function (t) { c["main_block_" + t] = s("middle_flow/main_block_" + t) }); var l = { reduction_block: a("exit_flow/reduction_block"), separable_conv: i("exit_flow/separable_conv") }; return Fv(t, n), { params: { entry_flow: u, middle_flow: c, exit_flow: l }, paramMappings: n } } function dm(t, e, n) { return Ou(Ec(t, e.filters, n, "same"), e.bias) } function vm(t, e, n) { void 0 === n && (n = !0); var r = n ? dl(t) : t; return r = Dv(r, e.separable_conv0, [1, 1]), r = Dv(dl(r), e.separable_conv1, [1, 1]), r = Gc(r, [3, 3], [2, 2], "same"), r = Ou(r, dm(t, e.expansion_conv, [2, 2])) } var mm, gm, ym = (Pp(xm, mm = kv), xm.prototype.forwardInput = function (n) { var r = this, o = this.params; if (!o) throw new Error("TinyXception - load model before inference"); return nn(function () { var t = yd(n.toBatchTensor(112, !0), [122.782, 117.001, 104.298]).div(kn(256)), e = dl(dm(t, o.entry_flow.conv_in, [2, 2])); return e = vm(e = vm(e, o.entry_flow.reduction_block_0, !1), o.entry_flow.reduction_block_1), Zp(r._numMainBlocks, 0, 1).forEach(function (t) { e = function (t, e) { var n = Dv(dl(t), e.separable_conv0, [1, 1]); return n = Dv(dl(n), e.separable_conv1, [1, 1]), n = Dv(dl(n), e.separable_conv2, [1, 1]), n = Ou(n, t) }(e, o.middle_flow["main_block_" + t]) }), e = vm(e, o.exit_flow.reduction_block), e = dl(Dv(e, o.exit_flow.separable_conv, [1, 1])) }) }, xm.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, xm.prototype.getDefaultModelName = function () { return "tiny_xception_model" }, xm.prototype.extractParamsFromWeigthMap = function (t) { return pm(t, this._numMainBlocks) }, xm.prototype.extractParams = function (t) { return fm(t, this._numMainBlocks) }, xm); function xm(t) { var e = mm.call(this, "TinyXception") || this; return e._numMainBlocks = t, e } (gm = c.Gender || (c.Gender = {})).FEMALE = "female", gm.MALE = "male"; var bm, wm = (Pp(Cm, bm = kv), Object.defineProperty(Cm.prototype, "faceFeatureExtractor", { get: function () { return this._faceFeatureExtractor }, enumerable: !0, configurable: !0 }), Cm.prototype.runNet = function (n) { var r = this, o = this.params; if (!o) throw new Error(this._name + " - load model before inference"); return nn(function () { var t = n instanceof yv ? r.faceFeatureExtractor.forwardInput(n) : n, e = Hc(t, [7, 7], [2, 2], "valid").as2D(t.shape[0], -1); return { age: Kv(e, o.fc.age).as1D(), gender: Kv(e, o.fc.gender) } }) }, Cm.prototype.forwardInput = function (r) { var o = this; return nn(function () { var t = o.runNet(r), e = t.age, n = t.gender; return { age: e, gender: so(n) } }) }, Cm.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, Cm.prototype.predictAgeAndGender = function (s) { return Lp(this, void 0, void 0, function () { var e, n, r, o, i, a, u = this; return Wp(this, function (t) { switch (t.label) { case 0: return [4, bv(s)]; case 1: return e = t.sent(), [4, this.forwardInput(e)]; case 2: return n = t.sent(), r = Br(n.age), o = Br(n.gender), i = r.map(function (t, e) { return { ageTensor: t, genderTensor: o[e] } }), [4, Promise.all(i.map(function (t) { var a = t.ageTensor, s = t.genderTensor; return Lp(u, void 0, void 0, function () { var e, n, r, o, i; return Wp(this, function (t) { switch (t.label) { case 0: return [4, a.data()]; case 1: return e = t.sent()[0], [4, s.data()]; case 2: return n = t.sent()[0], o = (r = .5 < n) ? c.Gender.MALE : c.Gender.FEMALE, i = r ? n : 1 - n, a.dispose(), s.dispose(), [2, { age: e, gender: o, genderProbability: i }] } }) }) }))]; case 3: return a = t.sent(), n.age.dispose(), n.gender.dispose(), [2, e.isBatchInput ? a : a[0]] } }) }) }, Cm.prototype.getDefaultModelName = function () { return "age_gender_model" }, Cm.prototype.dispose = function (t) { void 0 === t && (t = !0), this.faceFeatureExtractor.dispose(t), bm.prototype.dispose.call(this, t) }, Cm.prototype.loadClassifierParams = function (t) { var e = this.extractClassifierParams(t), n = e.params, r = e.paramMappings; this._params = n, this._paramMappings = r }, Cm.prototype.extractClassifierParams = function (t) { return function (t) { var e = [], n = zv(t), r = n.extractWeights, o = n.getRemainingWeights, i = Ov(r, e), a = i(512, 1, "fc/age"), s = i(512, 2, "fc/gender"); if (0 !== o().length) throw new Error("weights remaing after extract: " + o().length); return { paramMappings: e, params: { fc: { age: a, gender: s } } } }(t) }, Cm.prototype.extractParamsFromWeigthMap = function (t) { var e = Xv(t), n = e.featureExtractorMap, r = e.classifierMap; return this.faceFeatureExtractor.loadFromWeightMap(n), function (t) { var e = [], n = Wv(t, e); function r(t) { return { weights: n(t + "/weights", 2), bias: n(t + "/bias", 1) } } var o = { fc: { age: r("fc/age"), gender: r("fc/gender") } }; return Fv(t, e), { params: o, paramMappings: e } }(r) }, Cm.prototype.extractParams = function (t) { var e = t.slice(0, t.length - 1539), n = t.slice(t.length - 1539); return this.faceFeatureExtractor.extractWeights(e), this.extractClassifierParams(n) }, Cm); function Cm(t) { void 0 === t && (t = new ym(2)); var e = bm.call(this, "AgeGenderNet") || this; return e._faceFeatureExtractor = t, e } var Em, _m = (Pp(Im, Em = $v), Im.prototype.postProcess = function (t, o, e) { var i = e.map(function (t) { var e = t.width, n = t.height, r = o / Math.max(n, e); return { width: e * r, height: n * r } }), a = i.length; return nn(function () { function n(t, e) { return Mr([Bn([68], t), Bn([68], e)], 1).as2D(1, 136).as1D() } function r(t, e) { var n = i[t], r = n.width, o = n.height; return e(r, o) ? Math.abs(r - o) / 2 : 0 } return t.mul(Bn([a, 136], o)).sub(Mr(Array.from(Array(a), function (t, e) { return n(function (t) { return r(t, function (t, e) { return t < e }) }(e), function (t) { return r(t, function (t, e) { return e < t }) }(e)) }))).div(Mr(Array.from(Array(a), function (t, e) { return n(i[e].width, i[e].height) }))) }) }, Im.prototype.forwardInput = function (e) { var n = this; return nn(function () { var t = n.runNet(e); return n.postProcess(t, e.inputSize, e.inputDimensions.map(function (t) { return { height: t[0], width: t[1] } })) }) }, Im.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, Im.prototype.detectLandmarks = function (o) { return Lp(this, void 0, void 0, function () { var u, e, n, r = this; return Wp(this, function (t) { switch (t.label) { case 0: return [4, bv(o)]; case 1: return u = t.sent(), e = nn(function () { return Br(r.forwardInput(u)) }), [4, Promise.all(e.map(function (a, s) { return Lp(r, void 0, void 0, function () { var e, n, r, o, i; return Wp(this, function (t) { switch (t.label) { case 0: return r = (n = Array).from, [4, a.data()]; case 1: return e = r.apply(n, [t.sent()]), o = e.filter(function (t, e) { return Xp(e) }), i = e.filter(function (t, e) { return !Xp(e) }), [2, new Ad(Array(68).fill(0).map(function (t, e) { return new rd(o[e], i[e]) }), { height: u.getInputHeight(s), width: u.getInputWidth(s) })] } }) }) }))]; case 2: return n = t.sent(), e.forEach(function (t) { return t.dispose() }), [2, u.isBatchInput ? n : n[0]] } }) }) }, Im.prototype.getClassifierChannelsOut = function () { return 136 }, Im); function Im() { return null !== Em && Em.apply(this, arguments) || this } var Rm, km = (Pp(Sm, Rm = _m), Sm.prototype.getDefaultModelName = function () { return "face_landmark_68_model" }, Sm.prototype.getClassifierChannelsIn = function () { return 256 }, Sm); function Sm(t) { return void 0 === t && (t = new qv), Rm.call(this, "FaceLandmark68Net", t) || this } var Dm, Am = (Pp(Tm, Dm = kv), Tm.prototype.forwardInput = function (e) { var n = this.params; if (!n) throw new Error("TinyFaceFeatureExtractor - load model before inference"); return nn(function () { var t = Av(yd(e.toBatchTensor(112, !0), [122.782, 117.001, 104.298]).div(kn(255)), n.dense0, !0); return t = Av(t = Av(t, n.dense1), n.dense2), t = Hc(t, [14, 14], [2, 2], "valid") }) }, Tm.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, Tm.prototype.getDefaultModelName = function () { return "face_feature_extractor_tiny_model" }, Tm.prototype.extractParamsFromWeigthMap = function (t) { return function (t) { var e = [], n = Gv(t, e).extractDenseBlock3Params, r = { dense0: n("dense0", !0), dense1: n("dense1"), dense2: n("dense2") }; return Fv(t, e), { params: r, paramMappings: e } }(t) }, Tm.prototype.extractParams = function (t) { return function (t) { var e = [], n = zv(t), r = n.extractWeights, o = n.getRemainingWeights, i = Uv(r, e).extractDenseBlock3Params, a = i(3, 32, "dense0", !0), s = i(32, 64, "dense1"), u = i(64, 128, "dense2"); if (0 !== o().length) throw new Error("weights remaing after extract: " + o().length); return { paramMappings: e, params: { dense0: a, dense1: s, dense2: u } } }(t) }, Tm); function Tm() { return Dm.call(this, "TinyFaceFeatureExtractor") || this } var Nm, Fm = (Pp(Mm, Nm = _m), Mm.prototype.getDefaultModelName = function () { return "face_landmark_68_tiny_model" }, Mm.prototype.getClassifierChannelsIn = function () { return 128 }, Mm); function Mm(t) { return void 0 === t && (t = new Am), Nm.call(this, "FaceLandmark68TinyNet", t) || this } var Om, Pm = (Pp(Bm, Om = km), Bm); function Bm() { return null !== Om && Om.apply(this, arguments) || this } function Lm(t, e, n, r, o) { void 0 === o && (o = "same"); var i = e.conv, a = i.filters, s = i.bias, u = Ec(t, a, n, o); return u = function (t, e) { return Ou(Yu(t, e.weights), e.biases) }(u = Ou(u, s), e.scale), r ? dl(u) : u } function Wm(t, e) { return Lm(t, e, [1, 1], !1) } function zm(t, e) { return Lm(t, e, [2, 2], !0, "valid") } function Um(a, s) { function o(t, e, n, r) { var o = function (t, e, n) { var r = a(t), o = r.length / (e * n * n); if (Kp(o)) throw new Error("depth has to be an integer: " + o + ", weights.length: " + r.length + ", numFilters: " + e + ", filterSize: " + n); return nn(function () { return gl(Tn(r, [e, o, n, n]), [2, 3, 1, 0]) }) }(t, e, n), i = Sn(a(e)); return s.push({ paramPath: r + "/filters" }, { paramPath: r + "/bias" }), { filters: o, bias: i } } function i(t, e, n, r) { return { conv: o(t, e, n, r + "/conv"), scale: function (t, e) { var n = Sn(a(t)), r = Sn(a(t)); return s.push({ paramPath: e + "/weights" }, { paramPath: e + "/biases" }), { weights: n, biases: r } }(e, r + "/scale") } } return { extractConvLayerParams: i, extractResidualLayerParams: function (t, e, n, r, o) { return void 0 === o && (o = !1), { conv1: i((o ? .5 : 1) * t, e, n, r + "/conv1"), conv2: i(t, e, n, r + "/conv2") } } } } function Vm(t, e) { var n = Wv(t, e); function r(t) { return { conv: { filters: n(t + "/conv/filters", 4), bias: n(t + "/conv/bias", 1) }, scale: function (t) { return { weights: n(t + "/scale/weights", 1), biases: n(t + "/scale/biases", 1) } }(t) } } return { extractConvLayerParams: r, extractResidualLayerParams: function (t) { return { conv1: r(t + "/conv1"), conv2: r(t + "/conv2") } } } } function Gm(t, e) { var n = function (t, e) { return Lm(t, e, [1, 1], !0) }(t, e.conv1); return n = Wm(n, e.conv2), n = Ou(n, t), n = dl(n) } function Hm(t, e) { var n = zm(t, e.conv1); n = Wm(n, e.conv2); var r = Hc(t, 2, 2, "valid"), o = Pn(r.shape), i = r.shape[3] !== n.shape[3]; if (r.shape[1] !== n.shape[1] || r.shape[2] !== n.shape[2]) { var a = zp(n.shape); a[1] = 1; var s = Pn(a), u = zp((n = Vn([n, s], 1)).shape); u[2] = 1; var c = Pn(u); n = Vn([n, c], 2) } return r = i ? Vn([r, o], 3) : r, n = Ou(r, n), n = dl(n) } var qm, jm = (Pp(Km, qm = kv), Km.prototype.forwardInput = function (n) { var r = this.params; if (!r) throw new Error("FaceRecognitionNet - load model before inference"); return nn(function () { var t = zm(yd(n.toBatchTensor(150, !0).toFloat(), [122.782, 117.001, 104.298]).div(kn(256)), r.conv32_down), e = (t = Hm(t = Gm(t = Gm(t = Hm(t = Gm(t = Gm(t = Hm(t = Gm(t = Gm(t = Gm(t = Hm(t = Gm(t = Gm(t = Gm(t = Gc(t, 3, 2, "valid"), r.conv32_1), r.conv32_2), r.conv32_3), r.conv64_down), r.conv64_1), r.conv64_2), r.conv64_3), r.conv128_down), r.conv128_1), r.conv128_2), r.conv256_down), r.conv256_1), r.conv256_2), r.conv256_down_out)).mean([1, 2]); return Fc(e, r.fc) }) }, Km.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, Km.prototype.computeFaceDescriptor = function (i) { return Lp(this, void 0, void 0, function () { var e, n, r, o = this; return Wp(this, function (t) { switch (t.label) { case 0: return [4, bv(i)]; case 1: return e = t.sent(), n = nn(function () { return Br(o.forwardInput(e)) }), [4, Promise.all(n.map(function (t) { return t.data() }))]; case 2: return r = t.sent(), n.forEach(function (t) { return t.dispose() }), [2, e.isBatchInput ? r : r[0]] } }) }) }, Km.prototype.getDefaultModelName = function () { return "face_recognition_model" }, Km.prototype.extractParamsFromWeigthMap = function (t) { return function (t) { var e = [], n = Vm(t, e), r = n.extractConvLayerParams, o = n.extractResidualLayerParams, i = r("conv32_down"), a = o("conv32_1"), s = o("conv32_2"), u = o("conv32_3"), c = o("conv64_down"), l = o("conv64_1"), h = o("conv64_2"), f = o("conv64_3"), p = o("conv128_down"), d = o("conv128_1"), v = o("conv128_2"), m = o("conv256_down"), g = o("conv256_1"), y = o("conv256_2"), x = o("conv256_down_out"), b = t.fc; if (e.push({ originalPath: "fc", paramPath: "fc" }), !Hp(b)) throw new Error("expected weightMap[fc] to be a Tensor2D, instead have " + b); var w = { conv32_down: i, conv32_1: a, conv32_2: s, conv32_3: u, conv64_down: c, conv64_1: l, conv64_2: h, conv64_3: f, conv128_down: p, conv128_1: d, conv128_2: v, conv256_down: m, conv256_1: g, conv256_2: y, conv256_down_out: x, fc: b }; return Fv(t, e), { params: w, paramMappings: e } }(t) }, Km.prototype.extractParams = function (t) { return function (t) { var e = zv(t), n = e.extractWeights, r = e.getRemainingWeights, o = [], i = Um(n, o), a = i.extractConvLayerParams, s = i.extractResidualLayerParams, u = a(4704, 32, 7, "conv32_down"), c = s(9216, 32, 3, "conv32_1"), l = s(9216, 32, 3, "conv32_2"), h = s(9216, 32, 3, "conv32_3"), f = s(36864, 64, 3, "conv64_down", !0), p = s(36864, 64, 3, "conv64_1"), d = s(36864, 64, 3, "conv64_2"), v = s(36864, 64, 3, "conv64_3"), m = s(147456, 128, 3, "conv128_down", !0), g = s(147456, 128, 3, "conv128_1"), y = s(147456, 128, 3, "conv128_2"), x = s(589824, 256, 3, "conv256_down", !0), b = s(589824, 256, 3, "conv256_1"), w = s(589824, 256, 3, "conv256_2"), C = s(589824, 256, 3, "conv256_down_out"), E = nn(function () { return gl(Dn(n(32768), [128, 256]), [1, 0]) }); if (o.push({ paramPath: "fc" }), 0 !== r().length) throw new Error("weights remaing after extract: " + r().length); return { params: { conv32_down: u, conv32_1: c, conv32_2: l, conv32_3: h, conv64_down: f, conv64_1: p, conv64_2: d, conv64_3: v, conv128_down: m, conv128_1: g, conv128_2: y, conv256_down: x, conv256_1: b, conv256_2: w, conv256_down_out: C, fc: E }, paramMappings: o } }(t) }, Km); function Km() { return qm.call(this, "FaceRecognitionNet") || this } function Xm(t, e) { var n = { descriptor: e }; return Object.assign({}, t, n) } function Ym(t, e) { var n = { age: e }; return Object.assign({}, t, n) } function $m(t, e, n) { var r = { gender: e, genderProbability: n }; return Object.assign({}, t, r) } var Jm = (Object.defineProperty(Qm.prototype, "minFaceSize", { get: function () { return this._minFaceSize }, enumerable: !0, configurable: !0 }), Object.defineProperty(Qm.prototype, "scaleFactor", { get: function () { return this._scaleFactor }, enumerable: !0, configurable: !0 }), Object.defineProperty(Qm.prototype, "maxNumScales", { get: function () { return this._maxNumScales }, enumerable: !0, configurable: !0 }), Object.defineProperty(Qm.prototype, "scoreThresholds", { get: function () { return this._scoreThresholds }, enumerable: !0, configurable: !0 }), Object.defineProperty(Qm.prototype, "scaleSteps", { get: function () { return this._scaleSteps }, enumerable: !0, configurable: !0 }), Qm); function Qm(t) { var e = void 0 === t ? {} : t, n = e.minFaceSize, r = e.scaleFactor, o = e.maxNumScales, i = e.scoreThresholds, a = e.scaleSteps; if (this._name = "MtcnnOptions", this._minFaceSize = n || 20, this._scaleFactor = r || .709, this._maxNumScales = o || 10, this._scoreThresholds = i || [.6, .7, .7], this._scaleSteps = a, "number" != typeof this._minFaceSize || this._minFaceSize < 0) throw new Error(this._name + " - expected minFaceSize to be a number > 0"); if ("number" != typeof this._scaleFactor || this._scaleFactor <= 0 || 1 <= this._scaleFactor) throw new Error(this._name + " - expected scaleFactor to be a number between 0 and 1"); if ("number" != typeof this._maxNumScales || this._maxNumScales < 0) throw new Error(this._name + " - expected maxNumScales to be a number > 0"); if (!Array.isArray(this._scoreThresholds) || 3 !== this._scoreThresholds.length || this._scoreThresholds.some(function (t) { return "number" != typeof t })) throw new Error(this._name + " - expected scoreThresholds to be an array of numbers of length 3"); if (this._scaleSteps && (!Array.isArray(this._scaleSteps) || this._scaleSteps.some(function (t) { return "number" != typeof t }))) throw new Error(this._name + " - expected scaleSteps to be an array of numbers") } function Zm(s, u) { function i(t, e, n, r, o) { var i = Tn(s(t * e * n * n), [n, n, t, e]), a = Sn(s(e)); return u.push({ paramPath: r + "/filters" }, { paramPath: r + "/" + (o ? "batch_norm_offset" : "bias") }), { filters: i, bias: a } } function r(t, e, n, r) { var o = i(t, e, n, r, !0); return { filters: o.filters, batch_norm_offset: o.bias } } function t(t, e, n) { return { depthwise_conv: function (t, e) { var n = Tn(s(9 * t), [3, 3, t, 1]), r = Sn(s(t)), o = Sn(s(t)), i = Sn(s(t)), a = Sn(s(t)); return u.push({ paramPath: e + "/filters" }, { paramPath: e + "/batch_norm_scale" }, { paramPath: e + "/batch_norm_offset" }, { paramPath: e + "/batch_norm_mean" }, { paramPath: e + "/batch_norm_variance" }), { filters: n, batch_norm_scale: r, batch_norm_offset: o, batch_norm_mean: i, batch_norm_variance: a } }(t, n + "/depthwise_conv"), pointwise_conv: r(t, e, 1, n + "/pointwise_conv") } } return { extractMobilenetV1Params: function () { return { conv_0: r(3, 32, 3, "mobilenetv1/conv_0"), conv_1: t(32, 64, "mobilenetv1/conv_1"), conv_2: t(64, 128, "mobilenetv1/conv_2"), conv_3: t(128, 128, "mobilenetv1/conv_3"), conv_4: t(128, 256, "mobilenetv1/conv_4"), conv_5: t(256, 256, "mobilenetv1/conv_5"), conv_6: t(256, 512, "mobilenetv1/conv_6"), conv_7: t(512, 512, "mobilenetv1/conv_7"), conv_8: t(512, 512, "mobilenetv1/conv_8"), conv_9: t(512, 512, "mobilenetv1/conv_9"), conv_10: t(512, 512, "mobilenetv1/conv_10"), conv_11: t(512, 512, "mobilenetv1/conv_11"), conv_12: t(512, 1024, "mobilenetv1/conv_12"), conv_13: t(1024, 1024, "mobilenetv1/conv_13") } }, extractPredictionLayerParams: function () { return { conv_0: r(1024, 256, 1, "prediction_layer/conv_0"), conv_1: r(256, 512, 3, "prediction_layer/conv_1"), conv_2: r(512, 128, 1, "prediction_layer/conv_2"), conv_3: r(128, 256, 3, "prediction_layer/conv_3"), conv_4: r(256, 128, 1, "prediction_layer/conv_4"), conv_5: r(128, 256, 3, "prediction_layer/conv_5"), conv_6: r(256, 64, 1, "prediction_layer/conv_6"), conv_7: r(64, 128, 3, "prediction_layer/conv_7"), box_predictor_0: { box_encoding_predictor: i(512, 12, 1, "prediction_layer/box_predictor_0/box_encoding_predictor"), class_predictor: i(512, 9, 1, "prediction_layer/box_predictor_0/class_predictor") }, box_predictor_1: { box_encoding_predictor: i(1024, 24, 1, "prediction_layer/box_predictor_1/box_encoding_predictor"), class_predictor: i(1024, 18, 1, "prediction_layer/box_predictor_1/class_predictor") }, box_predictor_2: { box_encoding_predictor: i(512, 24, 1, "prediction_layer/box_predictor_2/box_encoding_predictor"), class_predictor: i(512, 18, 1, "prediction_layer/box_predictor_2/class_predictor") }, box_predictor_3: { box_encoding_predictor: i(256, 24, 1, "prediction_layer/box_predictor_3/box_encoding_predictor"), class_predictor: i(256, 18, 1, "prediction_layer/box_predictor_3/class_predictor") }, box_predictor_4: { box_encoding_predictor: i(256, 24, 1, "prediction_layer/box_predictor_4/box_encoding_predictor"), class_predictor: i(256, 18, 1, "prediction_layer/box_predictor_4/class_predictor") }, box_predictor_5: { box_encoding_predictor: i(128, 24, 1, "prediction_layer/box_predictor_5/box_encoding_predictor"), class_predictor: i(128, 18, 1, "prediction_layer/box_predictor_5/class_predictor") } } } } } function tg(t) { var e = [], n = function (t, e) { var i = Wv(t, e); function a(t, e, n) { return { filters: i(t + "/Conv2d_" + e + "_pointwise/weights", 4, n + "/filters"), batch_norm_offset: i(t + "/Conv2d_" + e + "_pointwise/convolution_bn_offset", 1, n + "/batch_norm_offset") } } function n(t) { var e = "mobilenetv1/conv_" + t, n = "MobilenetV1/Conv2d_" + t + "_depthwise", r = e + "/depthwise_conv", o = e + "/pointwise_conv"; return { depthwise_conv: { filters: i(n + "/depthwise_weights", 4, r + "/filters"), batch_norm_scale: i(n + "/BatchNorm/gamma", 1, r + "/batch_norm_scale"), batch_norm_offset: i(n + "/BatchNorm/beta", 1, r + "/batch_norm_offset"), batch_norm_mean: i(n + "/BatchNorm/moving_mean", 1, r + "/batch_norm_mean"), batch_norm_variance: i(n + "/BatchNorm/moving_variance", 1, r + "/batch_norm_variance") }, pointwise_conv: a("MobilenetV1", t, o) } } function r(t, e) { return { filters: i(t + "/weights", 4, e + "/filters"), bias: i(t + "/biases", 1, e + "/bias") } } function o(t) { return { box_encoding_predictor: r("Prediction/BoxPredictor_" + t + "/BoxEncodingPredictor", "prediction_layer/box_predictor_" + t + "/box_encoding_predictor"), class_predictor: r("Prediction/BoxPredictor_" + t + "/ClassPredictor", "prediction_layer/box_predictor_" + t + "/class_predictor") } } return { extractMobilenetV1Params: function () { return { conv_0: a("MobilenetV1", 0, "mobilenetv1/conv_0"), conv_1: n(1), conv_2: n(2), conv_3: n(3), conv_4: n(4), conv_5: n(5), conv_6: n(6), conv_7: n(7), conv_8: n(8), conv_9: n(9), conv_10: n(10), conv_11: n(11), conv_12: n(12), conv_13: n(13) } }, extractPredictionLayerParams: function () { return { conv_0: a("Prediction", 0, "prediction_layer/conv_0"), conv_1: a("Prediction", 1, "prediction_layer/conv_1"), conv_2: a("Prediction", 2, "prediction_layer/conv_2"), conv_3: a("Prediction", 3, "prediction_layer/conv_3"), conv_4: a("Prediction", 4, "prediction_layer/conv_4"), conv_5: a("Prediction", 5, "prediction_layer/conv_5"), conv_6: a("Prediction", 6, "prediction_layer/conv_6"), conv_7: a("Prediction", 7, "prediction_layer/conv_7"), box_predictor_0: o(0), box_predictor_1: o(1), box_predictor_2: o(2), box_predictor_3: o(3), box_predictor_4: o(4), box_predictor_5: o(5) } } } }(t, e), r = n.extractMobilenetV1Params, o = n.extractPredictionLayerParams, i = t["Output/extra_dim"]; if (e.push({ originalPath: "Output/extra_dim", paramPath: "output_layer/extra_dim" }), !qp(i)) throw new Error("expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have " + i); var a = { mobilenetv1: r(), prediction_layer: o(), output_layer: { extra_dim: i } }; return Fv(t, e), { params: a, paramMappings: e } } function eg(e, n, r) { return nn(function () { var t = Ec(e, n.filters, r, "same"); return t = Ou(t, n.batch_norm_offset), Gs(t, 0, 6) }) } var ng = .0010000000474974513; function rg(t, e) { return nn(function () { var o = null, i = eg(t, e.conv_0, [2, 2]); if ([e.conv_1, e.conv_2, e.conv_3, e.conv_4, e.conv_5, e.conv_6, e.conv_7, e.conv_8, e.conv_9, e.conv_10, e.conv_11, e.conv_12, e.conv_13].forEach(function (t, e) { var n = e + 1, r = function (e) { return [2, 4, 6, 12].some(function (t) { return t === e }) ? [2, 2] : [1, 1] }(n); i = eg(i = function (e, n, r) { return nn(function () { var t = kc(e, n.filters, r, "same"); return t = Ru(t, n.batch_norm_mean, n.batch_norm_variance, n.batch_norm_offset, n.batch_norm_scale, ng), Gs(t, 0, 6) }) }(i, t.depthwise_conv, r), t.pointwise_conv, [1, 1]), 11 === n && (o = i) }), null === o) throw new Error("mobileNetV1 - output of conv layer 11 is null"); return { out: i, conv11: o } }) } function og(t, e, n) { var r = t.arraySync(), o = Math.min(r[e][0], r[e][2]), i = Math.min(r[e][1], r[e][3]), a = Math.max(r[e][0], r[e][2]), s = Math.max(r[e][1], r[e][3]), u = Math.min(r[n][0], r[n][2]), c = Math.min(r[n][1], r[n][3]), l = Math.max(r[n][0], r[n][2]), h = Math.max(r[n][1], r[n][3]), f = (a - o) * (s - i), p = (l - u) * (h - c); if (f <= 0 || p <= 0) return 0; var d = Math.max(o, u), v = Math.max(i, c), m = Math.min(a, l), g = Math.min(s, h), y = Math.max(m - d, 0) * Math.max(g - v, 0); return y / (f + p - y) } function ig(t, e) { var n = function (t) { var e = Br(gl(t, [1, 0])), n = [tc(e[2], e[0]), tc(e[3], e[1])]; return { sizes: n, centers: [Ou(e[0], Wu(n[0], kn(2))), Ou(e[1], Wu(n[1], kn(2)))] } }(t), r = n.sizes, o = n.centers, i = Br(gl(e, [1, 0])), a = Wu(Yu(Ks(Wu(i[2], kn(5))), r[0]), kn(2)), s = Ou(Yu(Wu(i[0], kn(10)), r[0]), o[0]), u = Wu(Yu(Ks(Wu(i[3], kn(5))), r[1]), kn(2)), c = Ou(Yu(Wu(i[1], kn(10)), r[1]), o[1]); return gl(Mr([tc(s, a), tc(c, u), Ou(s, a), Ou(c, u)]), [1, 0]) } function ag(e, n) { return nn(function () { var t = e.shape[0]; return { boxPredictionEncoding: Tr(Nv(e, n.box_encoding_predictor), [t, -1, 1, 4]), classPrediction: Tr(Nv(e, n.class_predictor), [t, -1, 3]) } }) } var sg = (Object.defineProperty(ug.prototype, "minConfidence", { get: function () { return this._minConfidence }, enumerable: !0, configurable: !0 }), Object.defineProperty(ug.prototype, "maxResults", { get: function () { return this._maxResults }, enumerable: !0, configurable: !0 }), ug); function ug(t) { var e = void 0 === t ? {} : t, n = e.minConfidence, r = e.maxResults; if (this._name = "SsdMobilenetv1Options", this._minConfidence = n || .5, this._maxResults = r || 100, "number" != typeof this._minConfidence || this._minConfidence <= 0 || 1 <= this._minConfidence) throw new Error(this._name + " - expected minConfidence to be a number between 0 and 1"); if ("number" != typeof this._maxResults) throw new Error(this._name + " - expected maxResults to be a number") } var cg, lg = (Pp(hg, cg = kv), hg.prototype.forwardInput = function (r) { var o = this.params; if (!o) throw new Error("SsdMobilenetv1 - load model before inference"); return nn(function () { var t = r.toBatchTensor(512, !1).toFloat(), e = rg(tc(Yu(t, kn(.007843137718737125)), kn(1)), o.mobilenetv1), n = function (l, h, f) { return nn(function () { var t = eg(eg(l, f.conv_0, [1, 1]), f.conv_1, [2, 2]), e = eg(eg(t, f.conv_2, [1, 1]), f.conv_3, [2, 2]), n = eg(eg(e, f.conv_4, [1, 1]), f.conv_5, [2, 2]), r = eg(eg(n, f.conv_6, [1, 1]), f.conv_7, [2, 2]), o = ag(h, f.box_predictor_0), i = ag(l, f.box_predictor_1), a = ag(t, f.box_predictor_2), s = ag(e, f.box_predictor_3), u = ag(n, f.box_predictor_4), c = ag(r, f.box_predictor_5); return { boxPredictions: Vn([o.boxPredictionEncoding, i.boxPredictionEncoding, a.boxPredictionEncoding, s.boxPredictionEncoding, u.boxPredictionEncoding, c.boxPredictionEncoding], 1), classPredictions: Vn([o.classPrediction, i.classPrediction, a.classPrediction, s.classPrediction, u.classPrediction, c.classPrediction], 1) } }) }(e.out, e.conv11, o.prediction_layer); return function (o, i, a) { return nn(function () { var t = o.shape[0], e = ig(Tr(Or(a.extra_dim, [t, 1, 1]), [-1, 4]), Tr(o, [-1, 4])); e = Tr(e, [t, e.shape[0] / t, 4]); var n = ru(Xc(i, [0, 0, 1], [-1, -1, -1])), r = Xc(n, [0, 0, 0], [-1, -1, 1]); return r = Tr(r, [t, r.shape[1]]), { boxes: Br(e), scores: Br(r) } }) }(n.boxPredictions, n.classPredictions, o.output_layer) }) }, hg.prototype.forward = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent()])] } }) }) }, hg.prototype.locateFaces = function (w, C) { return void 0 === C && (C = {}), Lp(this, void 0, void 0, function () { var e, n, r, s, o, i, a, u, c, l, h, f, p, d, v, m, g, y, x, b; return Wp(this, function (t) { switch (t.label) { case 0: return e = new sg(C), n = e.maxResults, r = e.minConfidence, [4, bv(w)]; case 1: for (s = t.sent(), o = this.forwardInput(s), i = o.boxes, a = o.scores, u = i[0], c = a[0], l = 1; l < i.length; l++)i[l].dispose(), a[l].dispose(); return p = (f = Array).from, [4, c.data()]; case 2: return h = p.apply(f, [t.sent()]), d = function (o, t, e, i, a) { var n = o.shape[0], s = Math.min(e, n), r = t.map(function (t, e) { return { score: t, boxIndex: e } }).filter(function (t) { return t.score > a }).sort(function (t, e) { return e.score - t.score }), u = []; return r.forEach(function (t) { if (!(u.length >= s)) { for (var e = t.score, n = u.length - 1; 0 <= n; --n) { var r = og(o, t.boxIndex, u[n]); if (0 !== r && (t.score *= r <= i ? 1 : 0, t.score <= a)) break } e === t.score && u.push(t.boxIndex) } }), u }(u, h, n, .5, r), v = s.getReshapedInputDimensions(0), m = s.inputSize, g = m / v.width, y = m / v.height, x = u.arraySync(), b = d.map(function (t) { var e = [Math.max(0, x[t][0]), Math.min(1, x[t][2])].map(function (t) { return t * y }), n = e[0], r = e[1], o = [Math.max(0, x[t][1]), Math.min(1, x[t][3])].map(function (t) { return t * g }), i = o[0], a = o[1]; return new pd(h[t], new Cd(i, n, a - i, r - n), { height: s.getInputHeight(0), width: s.getInputWidth(0) }) }), u.dispose(), c.dispose(), [2, b] } }) }) }, hg.prototype.getDefaultModelName = function () { return "ssd_mobilenetv1_model" }, hg.prototype.extractParamsFromWeigthMap = function (t) { return tg(t) }, hg.prototype.extractParams = function (t) { return function (t) { var e = [], n = zv(t), r = n.extractWeights, o = n.getRemainingWeights, i = Zm(r, e), a = i.extractMobilenetV1Params, s = i.extractPredictionLayerParams, u = a(), c = s(), l = { extra_dim: An(r(20472), [1, 5118, 4]) }; if (e.push({ paramPath: "output_layer/extra_dim" }), 0 !== o().length) throw new Error("weights remaing after extract: " + o().length); return { params: { mobilenetv1: u, prediction_layer: c, output_layer: l }, paramMappings: e } }(t) }, hg); function hg() { return cg.call(this, "SsdMobilenetv1") || this } function fg(t) { var e = new lg; return e.extractWeights(t), e } var pg, dg = (Pp(vg, pg = lg), vg); function vg() { return null !== pg && pg.apply(this, arguments) || this } var mg, gg = [new rd(.738768, .874946), new rd(2.42204, 2.65704), new rd(4.30971, 7.04493), new rd(10.246, 4.59428), new rd(12.6868, 11.8741)], yg = [new rd(1.603231, 2.094468), new rd(6.041143, 7.080126), new rd(2.882459, 3.518061), new rd(4.266906, 5.178857), new rd(9.041765, 10.66308)], xg = [117.001, 114.697, 97.404], bg = function (t) { return "number" == typeof t }; function wg(t) { if (!t) throw new Error("invalid config: " + t); if ("boolean" != typeof t.withSeparableConvs) throw new Error("config.withSeparableConvs has to be a boolean, have: " + t.withSeparableConvs); if (!bg(t.iouThreshold) || t.iouThreshold < 0 || 1 < t.iouThreshold) throw new Error("config.iouThreshold has to be a number between [0, 1], have: " + t.iouThreshold); if (!Array.isArray(t.classes) || !t.classes.length || !t.classes.every(function (t) { return "string" == typeof t })) throw new Error("config.classes has to be an array class names: string[], have: " + JSON.stringify(t.classes)); if (!Array.isArray(t.anchors) || !t.anchors.length || !t.anchors.map(function (t) { return t || {} }).every(function (t) { return bg(t.x) && bg(t.y) })) throw new Error("config.anchors has to be an array of { x: number, y: number }, have: " + JSON.stringify(t.anchors)); if (t.meanRgb && (!Array.isArray(t.meanRgb) || 3 !== t.meanRgb.length || !t.meanRgb.every(bg))) throw new Error("config.meanRgb has to be an array of shape [number, number, number], have: " + JSON.stringify(t.meanRgb)) } function Cg(e) { return nn(function () { var t = Yu(e, kn(.10000000149011612)); return Ou(dl(tc(e, t)), t) }) } function Eg(e, n) { return nn(function () { var t = Cr(e, [[0, 0], [1, 1], [1, 1], [0, 0]]); return t = Ec(t, n.conv.filters, [1, 1], "valid"), t = tc(t, n.bn.sub), t = Yu(t, n.bn.truediv), Cg(t = Ou(t, n.conv.bias)) }) } function _g(e, n) { return nn(function () { var t = Cr(e, [[0, 0], [1, 1], [1, 1], [0, 0]]); return t = Ac(t, n.depthwise_filter, n.pointwise_filter, [1, 1], "valid"), Cg(t = Ou(t, n.bias)) }) } function Ig(o, i) { var r = Mv(o, i); var t = Bv(o, i); return { extractConvParams: r, extractConvWithBatchNormParams: function (t, e, n) { return { conv: r(t, e, 3, n + "/conv"), bn: function (t, e) { var n = Sn(o(t)), r = Sn(o(t)); return i.push({ paramPath: e + "/sub" }, { paramPath: e + "/truediv" }), { sub: n, truediv: r } }(e, n + "/bn") } }, extractSeparableConvParams: t } } function Rg(t, e) { var n = Wv(t, e); function r(t) { return { filters: n(t + "/filters", 4), bias: n(t + "/bias", 1) } } return { extractConvParams: r, extractConvWithBatchNormParams: function (t) { return { conv: r(t + "/conv"), bn: function (t) { return { sub: n(t + "/sub", 1), truediv: n(t + "/truediv", 1) } }(t + "/bn") } }, extractSeparableConvParams: Lv(n) } } (mg = c.TinyYolov2SizeType || (c.TinyYolov2SizeType = {}))[mg.XS = 224] = "XS", mg[mg.SM = 320] = "SM", mg[mg.MD = 416] = "MD", mg[mg.LG = 608] = "LG"; var kg = (Object.defineProperty(Sg.prototype, "inputSize", { get: function () { return this._inputSize }, enumerable: !0, configurable: !0 }), Object.defineProperty(Sg.prototype, "scoreThreshold", { get: function () { return this._scoreThreshold }, enumerable: !0, configurable: !0 }), Sg); function Sg(t) { var e = void 0 === t ? {} : t, n = e.inputSize, r = e.scoreThreshold; if (this._name = "TinyYolov2Options", this._inputSize = n || 416, this._scoreThreshold = r || .5, "number" != typeof this._inputSize || this._inputSize % 32 != 0) throw new Error(this._name + " - expected inputSize to be a number divisible by 32"); if ("number" != typeof this._scoreThreshold || this._scoreThreshold <= 0 || 1 <= this._scoreThreshold) throw new Error(this._name + " - expected scoreThreshold to be a number between 0 and 1") } var Dg, Ag = (Pp(Tg, Dg = kv), Object.defineProperty(Tg.prototype, "config", { get: function () { return this._config }, enumerable: !0, configurable: !0 }), Object.defineProperty(Tg.prototype, "withClassScores", { get: function () { return this.config.withClassScores || 1 < this.config.classes.length }, enumerable: !0, configurable: !0 }), Object.defineProperty(Tg.prototype, "boxEncodingSize", { get: function () { return 5 + (this.withClassScores ? this.config.classes.length : 0) }, enumerable: !0, configurable: !0 }), Tg.prototype.runTinyYolov2 = function (t, e) { var n = Eg(t, e.conv0); return n = Eg(n = Gc(n, [2, 2], [2, 2], "same"), e.conv1), n = Eg(n = Gc(n, [2, 2], [2, 2], "same"), e.conv2), n = Eg(n = Gc(n, [2, 2], [2, 2], "same"), e.conv3), n = Eg(n = Gc(n, [2, 2], [2, 2], "same"), e.conv4), n = Eg(n = Gc(n, [2, 2], [2, 2], "same"), e.conv5), Nv(n = Eg(n = Eg(n = Gc(n, [2, 2], [1, 1], "same"), e.conv6), e.conv7), e.conv8, "valid", !1) }, Tg.prototype.runMobilenet = function (t, e) { var n = this.config.isFirstLayerConv2d ? Cg(Nv(t, e.conv0, "valid", !1)) : _g(t, e.conv0); return n = _g(n = Gc(n, [2, 2], [2, 2], "same"), e.conv1), n = _g(n = Gc(n, [2, 2], [2, 2], "same"), e.conv2), n = _g(n = Gc(n, [2, 2], [2, 2], "same"), e.conv3), n = _g(n = Gc(n, [2, 2], [2, 2], "same"), e.conv4), n = _g(n = Gc(n, [2, 2], [2, 2], "same"), e.conv5), n = Gc(n, [2, 2], [1, 1], "same"), n = e.conv6 ? _g(n, e.conv6) : n, Nv(n = e.conv7 ? _g(n, e.conv7) : n, e.conv8, "valid", !1) }, Tg.prototype.forwardInput = function (e, n) { var r = this, o = this.params; if (!o) throw new Error("TinyYolov2 - load model before inference"); return nn(function () { var t = e.toBatchTensor(n, !1).toFloat(); return t = (t = r.config.meanRgb ? yd(t, r.config.meanRgb) : t).div(kn(256)), r.config.withSeparableConvs ? r.runMobilenet(t, o) : r.runTinyYolov2(t, o) }) }, Tg.prototype.forward = function (n, r) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [4, e.apply(this, [t.sent(), r])]; case 2: return [2, t.sent()] } }) }) }, Tg.prototype.detect = function (d, v) { return void 0 === v && (v = {}), Lp(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p = this; return Wp(this, function (t) { switch (t.label) { case 0: return e = new kg(v), n = e.inputSize, r = e.scoreThreshold, [4, bv(d)]; case 1: return o = t.sent(), [4, this.forwardInput(o, n)]; case 2: return i = t.sent(), a = nn(function () { return Br(i)[0].expandDims() }), s = { width: o.getInputWidth(0), height: o.getInputHeight(0) }, [4, this.extractBoxes(a, o.getReshapedInputDimensions(0), r)]; case 3: return u = t.sent(), i.dispose(), a.dispose(), c = u.map(function (t) { return t.box }), l = u.map(function (t) { return t.score }), h = u.map(function (t) { return t.classScore }), f = u.map(function (t) { return p.config.classes[t.label] }), [2, gd(c.map(function (t) { return t.rescale(n) }), l, this.config.iouThreshold, !0).map(function (t) { return new ld(l[t], h[t], f[t], c[t], s) })] } }) }) }, Tg.prototype.getDefaultModelName = function () { return "" }, Tg.prototype.extractParamsFromWeigthMap = function (t) { return function (t, e) { var n, r = [], o = Rg(t, r), i = o.extractConvParams, a = o.extractConvWithBatchNormParams, s = o.extractSeparableConvParams; if (e.withSeparableConvs) { var u = e.filterSizes && e.filterSizes.length || 9; n = { conv0: e.isFirstLayerConv2d ? i("conv0") : s("conv0"), conv1: s("conv1"), conv2: s("conv2"), conv3: s("conv3"), conv4: s("conv4"), conv5: s("conv5"), conv6: 7 < u ? s("conv6") : void 0, conv7: 8 < u ? s("conv7") : void 0, conv8: i("conv8") } } else n = { conv0: a("conv0"), conv1: a("conv1"), conv2: a("conv2"), conv3: a("conv3"), conv4: a("conv4"), conv5: a("conv5"), conv6: a("conv6"), conv7: a("conv7"), conv8: i("conv8") }; return Fv(t, r), { params: n, paramMappings: r } }(t, this.config) }, Tg.prototype.extractParams = function (t) { var e = this.config.filterSizes || Tg.DEFAULT_FILTER_SIZES, n = e ? e.length : void 0; if (7 !== n && 8 !== n && 9 !== n) throw new Error("TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found " + n + " filterSizes in config"); return function (t, e, n, r) { var o, i = zv(t), a = i.extractWeights, s = i.getRemainingWeights, u = [], c = Ig(a, u), l = c.extractConvParams, h = c.extractConvWithBatchNormParams, f = c.extractSeparableConvParams; if (e.withSeparableConvs) { var p = r[0], d = r[1], v = r[2], m = r[3], g = r[4], y = r[5], x = r[6], b = r[7], w = r[8]; o = { conv0: e.isFirstLayerConv2d ? l(p, d, 3, "conv0") : f(p, d, "conv0"), conv1: f(d, v, "conv1"), conv2: f(v, m, "conv2"), conv3: f(m, g, "conv3"), conv4: f(g, y, "conv4"), conv5: f(y, x, "conv5"), conv6: b ? f(x, b, "conv6") : void 0, conv7: w ? f(b, w, "conv7") : void 0, conv8: l(w || b || x, 5 * n, 1, "conv8") } } else p = r[0], d = r[1], v = r[2], m = r[3], g = r[4], y = r[5], x = r[6], b = r[7], w = r[8], o = { conv0: h(p, d, "conv0"), conv1: h(d, v, "conv1"), conv2: h(v, m, "conv2"), conv3: h(m, g, "conv3"), conv4: h(g, y, "conv4"), conv5: h(y, x, "conv5"), conv6: h(x, b, "conv6"), conv7: h(b, w, "conv7"), conv8: l(w, 5 * n, 1, "conv8") }; if (0 !== s().length) throw new Error("weights remaing after extract: " + s().length); return { params: o, paramMappings: u } }(t, this.config, this.boxEncodingSize, e) }, Tg.prototype.extractBoxes = function (T, N, F) { return Lp(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p, d, v, m, g, y, x, b, w, C, E, _, I, R, k, S, D, A = this; return Wp(this, function (t) { switch (t.label) { case 0: return e = N.width, n = N.height, r = Math.max(e, n), o = r / e, i = r / n, a = T.shape[1], s = this.config.anchors.length, u = nn(function () { var t = T.reshape([a, a, s, A.boxEncodingSize]); return [t.slice([0, 0, 0, 0], [a, a, s, 4]), t.slice([0, 0, 0, 4], [a, a, s, 1]), A.withClassScores ? so(t.slice([0, 0, 0, 5], [a, a, s, A.config.classes.length]), 3) : kn(0)] }), c = u[0], l = u[1], h = u[2], f = [], [4, l.array()]; case 1: return p = t.sent(), [4, c.array()]; case 2: d = t.sent(), v = 0, t.label = 3; case 3: if (!(v < a)) return [3, 12]; m = 0, t.label = 4; case 4: if (!(m < a)) return [3, 11]; g = 0, t.label = 5; case 5: return g < s ? (y = bd(p[v][m][g][0]), !F || F < y ? (x = (m + bd(d[v][m][g][0])) / a * o, b = (v + bd(d[v][m][g][1])) / a * i, w = Math.exp(d[v][m][g][2]) * this.config.anchors[g].x / a * o, C = Math.exp(d[v][m][g][3]) * this.config.anchors[g].y / a * i, E = x - w / 2, _ = b - C / 2, I = { row: v, col: m, anchor: g }, this.withClassScores ? [4, this.extractPredictedClass(h, I)] : [3, 7]) : [3, 9]) : [3, 10]; case 6: return D = t.sent(), [3, 8]; case 7: D = { classScore: 1, label: 0 }, t.label = 8; case 8: k = (R = D).classScore, S = R.label, f.push(Bp({ box: new ud(E, _, E + w, _ + C), score: y, classScore: y * k, label: S }, I)), t.label = 9; case 9: return g++, [3, 5]; case 10: return m++, [3, 4]; case 11: return v++, [3, 3]; case 12: return c.dispose(), l.dispose(), h.dispose(), [2, f] } }) }) }, Tg.prototype.extractPredictedClass = function (e, a) { return Lp(this, void 0, void 0, function () { var n, r, o, i; return Wp(this, function (t) { switch (t.label) { case 0: return n = a.row, r = a.col, o = a.anchor, [4, e.array()]; case 1: return i = t.sent(), [2, Array(this.config.classes.length).fill(0).map(function (t, e) { return i[n][r][o][e] }).map(function (t, e) { return { classScore: t, label: e } }).reduce(function (t, e) { return t.classScore > e.classScore ? t : e })] } }) }) }, Tg.DEFAULT_FILTER_SIZES = [3, 16, 32, 64, 128, 256, 512, 1024, 1024], Tg); function Tg(t) { var e = Dg.call(this, "TinyYolov2") || this; return wg(t), e._config = t, e } var Ng, Fg = (Pp(Mg, Ng = Ag), Object.defineProperty(Mg.prototype, "withSeparableConvs", { get: function () { return this.config.withSeparableConvs }, enumerable: !0, configurable: !0 }), Object.defineProperty(Mg.prototype, "anchors", { get: function () { return this.config.anchors }, enumerable: !0, configurable: !0 }), Mg.prototype.locateFaces = function (e, n) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.detect(e, n)]; case 1: return [2, t.sent().map(function (t) { return new pd(t.score, t.relativeBox, { width: t.imageWidth, height: t.imageHeight }) })] } }) }) }, Mg.prototype.getDefaultModelName = function () { return this.withSeparableConvs ? "tiny_yolov2_separable_conv_model" : "tiny_yolov2_model" }, Mg.prototype.extractParamsFromWeigthMap = function (t) { return Ng.prototype.extractParamsFromWeigthMap.call(this, t) }, Mg); function Mg(t) { void 0 === t && (t = !0); var e = Object.assign({}, { withSeparableConvs: t, iouThreshold: .4, classes: ["face"] }, t ? { anchors: yg, meanRgb: xg } : { anchors: gg, withClassScores: !0 }); return Ng.call(this, e) || this } var Og, Pg = (Pp(Bg, Og = kg), Bg); function Bg() { var t = null !== Og && Og.apply(this, arguments) || this; return t._name = "TinyFaceDetectorOptions", t } var Lg = (Wg.prototype.then = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = n, [4, this.run()]; case 1: return [2, e.apply(void 0, [t.sent()])] } }) }) }, Wg.prototype.run = function () { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { throw new Error("ComposableTask - run is not implemented") }) }) }, Wg); function Wg() { } function zg(a, s, u, c, l) { return void 0 === l && (l = function (t) { return t.alignedRect }), Lp(this, void 0, void 0, function () { var e, n, r, o, i; return Wp(this, function (t) { switch (t.label) { case 0: return e = a.map(function (t) { return am(t) ? l(t) : t.detection }), (r = c) ? [3, 5] : s instanceof bt ? [4, Cv(s, e)] : [3, 2]; case 1: return o = t.sent(), [3, 4]; case 2: return [4, wv(s, e)]; case 3: o = t.sent(), t.label = 4; case 4: r = o, t.label = 5; case 5: return [4, u(n = r)]; case 6: return i = t.sent(), n.forEach(function (t) { return t instanceof bt && t.dispose() }), [2, i] } }) }) } function Ug(e, r, o, i, a) { return Lp(this, void 0, void 0, function () { var n = this; return Wp(this, function (t) { return [2, zg([e], r, function (e) { return Lp(n, void 0, void 0, function () { return Wp(this, function (t) { return [2, o(e[0])] }) }) }, i, a)] }) }) } var Vg = 2, Gg = 12; function Hg(t) { var e = zv(t), n = e.extractWeights, r = e.getRemainingWeights, o = [], i = function (r, o) { var u = Mv(r, o), c = Ov(r, o); function l(t, e) { var n = Sn(r(t)); return o.push({ paramPath: e }), n } function h(t, e, n) { return void 0 === n && (n = !1), { conv1: u(t[0], t[1], 3, e + "/conv1"), prelu1_alpha: l(t[1], e + "/prelu1_alpha"), conv2: u(t[1], t[2], 3, e + "/conv2"), prelu2_alpha: l(t[2], e + "/prelu2_alpha"), conv3: u(t[2], t[3], n ? 2 : 3, e + "/conv3"), prelu3_alpha: l(t[3], e + "/prelu3_alpha") } } return { extractPNetParams: function () { var t = h([3, 10, 16, 32], "pnet"), e = u(32, 2, 1, "pnet/conv4_1"), n = u(32, 4, 1, "pnet/conv4_2"); return Bp(Bp({}, t), { conv4_1: e, conv4_2: n }) }, extractRNetParams: function () { var t = h([3, 28, 48, 64], "rnet", !0), e = c(576, 128, "rnet/fc1"), n = l(128, "rnet/prelu4_alpha"), r = c(128, 2, "rnet/fc2_1"), o = c(128, 4, "rnet/fc2_2"); return Bp(Bp({}, t), { fc1: e, prelu4_alpha: n, fc2_1: r, fc2_2: o }) }, extractONetParams: function () { var t = h([3, 32, 64, 64], "onet"), e = u(64, 128, 2, "onet/conv4"), n = l(128, "onet/prelu4_alpha"), r = c(1152, 256, "onet/fc1"), o = l(256, "onet/prelu5_alpha"), i = c(256, 2, "onet/fc2_1"), a = c(256, 4, "onet/fc2_2"), s = c(256, 10, "onet/fc2_3"); return Bp(Bp({}, t), { conv4: e, prelu4_alpha: n, fc1: r, prelu5_alpha: o, fc2_1: i, fc2_2: a, fc2_3: s }) } } }(n, o), a = i.extractPNetParams, s = i.extractRNetParams, u = i.extractONetParams, c = a(), l = s(), h = u(); if (0 !== r().length) throw new Error("weights remaing after extract: " + r().length); return { params: { pnet: c, rnet: l, onet: h }, paramMappings: o } } function qg(t) { var e = [], n = function (t, e) { var n = Wv(t, e); function u(t) { return { filters: n(t + "/weights", 4, t + "/filters"), bias: n(t + "/bias", 1) } } function c(t) { return { weights: n(t + "/weights", 2), bias: n(t + "/bias", 1) } } function l(t) { return n(t, 1) } function h(t) { return { conv1: u(t + "/conv1"), prelu1_alpha: l(t + "/prelu1_alpha"), conv2: u(t + "/conv2"), prelu2_alpha: l(t + "/prelu2_alpha"), conv3: u(t + "/conv3"), prelu3_alpha: l(t + "/prelu3_alpha") } } return { extractPNetParams: function () { var t = h("pnet"), e = u("pnet/conv4_1"), n = u("pnet/conv4_2"); return Bp(Bp({}, t), { conv4_1: e, conv4_2: n }) }, extractRNetParams: function () { var t = h("rnet"), e = c("rnet/fc1"), n = l("rnet/prelu4_alpha"), r = c("rnet/fc2_1"), o = c("rnet/fc2_2"); return Bp(Bp({}, t), { fc1: e, prelu4_alpha: n, fc2_1: r, fc2_2: o }) }, extractONetParams: function () { var t = h("onet"), e = u("onet/conv4"), n = l("onet/prelu4_alpha"), r = c("onet/fc1"), o = l("onet/prelu5_alpha"), i = c("onet/fc2_1"), a = c("onet/fc2_2"), s = c("onet/fc2_3"); return Bp(Bp({}, t), { conv4: e, prelu4_alpha: n, fc1: r, prelu5_alpha: o, fc2_1: i, fc2_2: a, fc2_3: s }) } } }(t, e), r = n.extractPNetParams, o = n.extractRNetParams, i = n.extractONetParams, a = r(), s = o(), u = i(); return Fv(t, e), { params: { pnet: a, rnet: s, onet: u }, paramMappings: e } } function jg(t, e) { var n = e[0], r = e[1]; return { height: Math.floor(n * t), width: Math.floor(r * t) } } var Kg, Xg = (Pp(Yg, Kg = id), Yg); function Yg(t, e, n, r) { return Kg.call(this, { left: t, top: e, right: n, bottom: r }, !0) || this } function $g(t) { return nn(function () { return Yu(tc(t, kn(127.5)), kn(.0078125)) }) } function Jg(t, e) { return nn(function () { return Ou(dl(t), Yu(e, Zs(dl(Zs(t))))) }) } function Qg(e, n, r) { return void 0 === r && (r = !1), nn(function () { var t = Nv(e, n.conv1, "valid"); return t = Jg(t, n.prelu1_alpha), t = Jg(t = Nv(t = Gc(t, r ? [2, 2] : [3, 3], [2, 2], "same"), n.conv2, "valid"), n.prelu2_alpha), t = Jg(t = Nv(t = r ? t : Gc(t, [3, 3], [2, 2], "valid"), n.conv3, "valid"), n.prelu3_alpha) }) } function Zg(s, t, u, c, l) { l.stage1 = []; var e = t.map(function (a) { return nn(function () { var t = { scale: a }, e = function (o, i) { return nn(function () { var t = jg(i, o.shape.slice(1)), e = t.height, n = t.width, r = $g(vh.resizeBilinear(o, [e, n])); return gl(r, [0, 2, 1, 3]) }) }(s, a), n = Date.now(), r = function (r, o) { return nn(function () { var t = Qg(r, o, !0), e = Nv(t, o.conv4_1, "valid"), n = yr(il(e, 3), 3); return { prob: so(tc(e, n), 3), regions: Nv(t, o.conv4_2, "valid") } }) }(e, c), o = r.prob, i = r.regions; return t.pnet = Date.now() - n, { scoresTensor: Br(Br(o, 3)[1])[0], regionsTensor: Br(i)[0], scale: a, statsForScale: t } }) }).map(function (t) { var e = t.scoresTensor, n = t.regionsTensor, r = t.scale, o = t.statsForScale, i = function (t, o, i, e) { for (var n = [], a = t.arraySync(), r = 0; r < t.shape[0]; r++)for (var s = 0; s < t.shape[1]; s++)a[r][s] >= e && n.push(new rd(s, r)); return n.map(function (t) { var e = new ud(Math.round((t.y * Vg + 1) / i), Math.round((t.x * Vg + 1) / i), Math.round((t.y * Vg + Gg) / i), Math.round((t.x * Vg + Gg) / i)), n = a[t.y][t.x], r = o.arraySync(); return { cell: e, score: n, region: new Xg(r[t.y][t.x][0], r[t.y][t.x][1], r[t.y][t.x][2], r[t.y][t.x][3]) } }) }(e, n, r, u); if (e.dispose(), n.dispose(), !i.length) return l.stage1.push(o), []; var a = Date.now(), s = gd(i.map(function (t) { return t.cell }), i.map(function (t) { return t.score }), .5); return o.nms = Date.now() - a, o.numBoxes = s.length, l.stage1.push(o), s.map(function (t) { return i[t] }) }).reduce(function (t, e) { return t.concat(e) }, []), n = [], r = []; if (0 < e.length) { var o = Date.now(), i = gd(e.map(function (t) { return t.cell }), e.map(function (t) { return t.score }), .7); l.stage1_nms = Date.now() - o, r = i.map(function (t) { return e[t].score }), n = i.map(function (t) { return e[t] }).map(function (t) { var e = t.cell, n = t.region; return new ud(e.left + n.left * e.width, e.top + n.top * e.height, e.right + n.right * e.width, e.bottom + n.bottom * e.height).toSquare().round() }) } return { boxes: n, scores: r } } function ty(h, r, t) { var a = t.width, s = t.height; return Lp(this, void 0, void 0, function () { var l, e, i, n = this; return Wp(this, function (t) { switch (t.label) { case 0: return l = nv(h), [4, Promise.all(r.map(function (c) { return Lp(n, void 0, void 0, function () { var e, n, r, o, i, a, s, u; return Wp(this, function (t) { return e = c.padAtBorders(h.height, h.width), n = e.y, r = e.ey, o = e.x, i = e.ex, a = o - 1, s = n - 1, u = l.getImageData(a, s, i - a, r - s), [2, tv.isNodejs() ? dv(u) : createImageBitmap(u)] }) }) }))]; case 1: return e = t.sent(), i = [], e.forEach(function (t) { var e = nv(pv({ width: a, height: s })); e.drawImage(t, 0, 0, a, s); for (var n = e.getImageData(0, 0, a, s).data, r = [], o = 0; o < n.length; o += 4)r.push(n[o + 2]), r.push(n[o + 1]), r.push(n[o]); i.push(r) }), [2, i.map(function (t) { return nn(function () { return $g(gl(Tn(t, [1, a, s, 3]), [0, 2, 1, 3]).toFloat()) }) })] } }) }) } function ey(v, m, g, y, x) { return Lp(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p, d; return Wp(this, function (t) { switch (t.label) { case 0: return e = Date.now(), [4, ty(v, m, { width: 24, height: 24 })]; case 1: return n = t.sent(), x.stage2_extractImagePatches = Date.now() - e, e = Date.now(), r = n.map(function (t) { var e = function (a, s) { return nn(function () { var t = Qg(a, s), e = Jg(Kv(Tr(t, [t.shape[0], s.fc1.weights.shape[0]]), s.fc1), s.prelu4_alpha), n = Kv(e, s.fc2_1), r = yr(il(n, 1), 1), o = so(tc(n, r), 1), i = Kv(e, s.fc2_2); return { scores: Br(o, 1)[1], regions: i } }) }(t, y); return t.dispose(), e }), x.stage2_rnet = Date.now() - e, o = 1 < r.length ? Vn(r.map(function (t) { return t.scores })) : r[0].scores, s = (a = Array).from, [4, o.data()]; case 2: return i = s.apply(a, [t.sent()]), o.dispose(), u = i.map(function (t, e) { return { score: t, idx: e } }).filter(function (t) { return t.score > g }).map(function (t) { return t.idx }), c = u.map(function (t) { return m[t] }), l = u.map(function (t) { return i[t] }), h = [], f = [], 0 < c.length && (e = Date.now(), p = gd(c, l, .7), x.stage2_nms = Date.now() - e, d = p.map(function (t) { var e = r[u[t]].regions.arraySync(); return new Xg(e[0][0], e[0][1], e[0][2], e[0][3]) }), f = p.map(function (t) { return l[t] }), h = p.map(function (t, e) { return c[t].calibrate(d[e]) })), r.forEach(function (t) { t.regions.dispose(), t.scores.dispose() }), [2, { boxes: h, scores: f }] } }) }) } function ny(m, g, y, x, b) { return Lp(this, void 0, void 0, function () { var e, n, i, r, o, a, s, u, c, l, h, f, p, d, v; return Wp(this, function (t) { switch (t.label) { case 0: return e = Date.now(), [4, ty(m, g, { width: 48, height: 48 })]; case 1: return n = t.sent(), b.stage3_extractImagePatches = Date.now() - e, e = Date.now(), i = n.map(function (t) { var e = function (s, u) { return nn(function () { var t = Qg(s, u); t = Jg(t = Nv(t = Gc(t, [2, 2], [2, 2], "same"), u.conv4, "valid"), u.prelu4_alpha); var e = Jg(Kv(Tr(t, [t.shape[0], u.fc1.weights.shape[0]]), u.fc1), u.prelu5_alpha), n = Kv(e, u.fc2_1), r = yr(il(n, 1), 1), o = so(tc(n, r), 1), i = Kv(e, u.fc2_2), a = Kv(e, u.fc2_3); return { scores: Br(o, 1)[1], regions: i, points: a } }) }(t, x); return t.dispose(), e }), b.stage3_onet = Date.now() - e, r = 1 < i.length ? Vn(i.map(function (t) { return t.scores })) : i[0].scores, s = (a = Array).from, [4, r.data()]; case 2: return o = s.apply(a, [t.sent()]), r.dispose(), u = o.map(function (t, e) { return { score: t, idx: e } }).filter(function (t) { return t.score > y }).map(function (t) { return t.idx }), c = u.map(function (t) { var e = i[t].regions.arraySync(); return new Xg(e[0][0], e[0][1], e[0][2], e[0][3]) }), l = u.map(function (t, e) { return g[t].calibrate(c[e]) }), h = u.map(function (t) { return o[t] }), f = [], p = [], d = [], 0 < l.length && (e = Date.now(), v = gd(l, h, .7, !1), b.stage3_nms = Date.now() - e, f = v.map(function (t) { return l[t] }), p = v.map(function (t) { return h[t] }), d = v.map(function (r, o) { return Array(5).fill(0).map(function (t, e) { var n = i[r].points.arraySync(); return new rd(n[0][e] * (f[o].width + 1) + f[o].left, n[0][e + 5] * (f[o].height + 1) + f[o].top) }) })), i.forEach(function (t) { t.regions.dispose(), t.scores.dispose(), t.points.dispose() }), [2, { boxes: f, scores: p, points: d }] } }) }) } var ry, oy = (Pp(iy, ry = kv), iy.prototype.load = function (e) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { return console.warn("mtcnn is deprecated and will be removed soon"), [2, ry.prototype.load.call(this, e)] }) }) }, iy.prototype.loadFromDisk = function (e) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { return console.warn("mtcnn is deprecated and will be removed soon"), [2, ry.prototype.loadFromDisk.call(this, e)] }) }) }, iy.prototype.forwardInput = function (C, E) { return void 0 === E && (E = {}), Lp(this, void 0, void 0, function () { var e, n, r, o, i, a, s, u, c, l, h, f, p, d, v, m, g, y, x, b, w; return Wp(this, function (t) { switch (t.label) { case 0: if (!(e = this.params)) throw new Error("Mtcnn - load model before inference"); if (!(n = C.canvases[0])) throw new Error("Mtcnn - inputCanvas is not defined, note that passing tensors into Mtcnn.forwardInput is not supported yet."); return r = {}, o = Date.now(), i = nn(function () { return function (t) { return nn(function () { return Mr(Br(t, 3).reverse(), 3) }) }(yr(Kf.fromPixels(n)).toFloat()) }), a = function (t) { return i.dispose(), r.total = Date.now() - o, t }, s = i.shape.slice(1), u = s[0], c = s[1], l = new Jm(E), h = l.minFaceSize, f = l.scaleFactor, p = l.maxNumScales, d = l.scoreThresholds, v = l.scaleSteps, m = (v || function (t, e, n) { for (var r = n[0], o = n[1], i = Gg / t, a = [], s = Math.min(r, o) * i, u = 0; 12 <= s;)a.push(i * Math.pow(e, u)), s *= e, u += 1; return a }(h, f, [u, c])).filter(function (t) { var e = jg(t, [u, c]); return Math.min(e.width, e.height) > Gg }).slice(0, p), r.scales = m, r.pyramid = m.map(function (t) { return jg(t, [u, c]) }), g = Date.now(), [4, Zg(i, m, d[0], e.pnet, r)]; case 1: return y = t.sent(), r.total_stage1 = Date.now() - g, y.boxes.length ? (r.stage2_numInputBoxes = y.boxes.length, g = Date.now(), [4, ey(n, y.boxes, d[1], e.rnet, r)]) : [2, a({ results: [], stats: r })]; case 2: return x = t.sent(), r.total_stage2 = Date.now() - g, x.boxes.length ? (r.stage3_numInputBoxes = x.boxes.length, g = Date.now(), [4, ny(n, x.boxes, d[2], e.onet, r)]) : [2, a({ results: [], stats: r })]; case 3: return b = t.sent(), r.total_stage3 = Date.now() - g, w = b.boxes.map(function (e, t) { return sm(Hd({}, new pd(b.scores[t], new Cd(e.left / c, e.top / u, e.width / c, e.height / u), { height: u, width: c })), new kd(b.points[t].map(function (t) { return t.sub(new rd(e.left, e.top)).div(new rd(e.width, e.height)) }), { width: e.width, height: e.height })) }), [2, a({ results: w, stats: r })] } }) }) }, iy.prototype.forward = function (n, r) { return void 0 === r && (r = {}), Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [4, e.apply(this, [t.sent(), r])]; case 2: return [2, t.sent().results] } }) }) }, iy.prototype.forwardWithStats = function (n, r) { return void 0 === r && (r = {}), Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = this.forwardInput, [4, bv(n)]; case 1: return [2, e.apply(this, [t.sent(), r])] } }) }) }, iy.prototype.getDefaultModelName = function () { return "mtcnn_model" }, iy.prototype.extractParamsFromWeigthMap = function (t) { return qg(t) }, iy.prototype.extractParams = function (t) { return Hg(t) }, iy); function iy() { return ry.call(this, "Mtcnn") || this } var ay, sy = [new rd(1.603231, 2.094468), new rd(6.041143, 7.080126), new rd(2.882459, 3.518061), new rd(4.266906, 5.178857), new rd(9.041765, 10.66308)], uy = [117.001, 114.697, 97.404], cy = (Pp(ly, ay = Ag), Object.defineProperty(ly.prototype, "anchors", { get: function () { return this.config.anchors }, enumerable: !0, configurable: !0 }), ly.prototype.locateFaces = function (e, n) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.detect(e, n)]; case 1: return [2, t.sent().map(function (t) { return new pd(t.score, t.relativeBox, { width: t.imageWidth, height: t.imageHeight }) })] } }) }) }, ly.prototype.getDefaultModelName = function () { return "tiny_face_detector_model" }, ly.prototype.extractParamsFromWeigthMap = function (t) { return ay.prototype.extractParamsFromWeigthMap.call(this, t) }, ly); function ly() { var t = { withSeparableConvs: !0, iouThreshold: .4, classes: ["face"], anchors: sy, meanRgb: uy, isFirstLayerConv2d: !0, filterSizes: [3, 16, 32, 64, 128, 256, 512] }; return ay.call(this, t) || this } function hy(t, e) { return vy.ssdMobilenetv1.locateFaces(t, e) } function fy(t) { return vy.faceLandmark68Net.detectLandmarks(t) } function py(t) { return vy.ssdMobilenetv1.load(t) } var dy, vy = { ssdMobilenetv1: new lg, tinyFaceDetector: new cy, tinyYolov2: new Fg, mtcnn: new oy, faceLandmark68Net: new km, faceLandmark68TinyNet: new Fm, faceRecognitionNet: new jm, faceExpressionNet: new nm, ageGenderNet: new wm }, my = py, gy = hy, yy = fy, xy = (Pp(by, dy = Lg), by); function by(t, e, n) { var r = dy.call(this) || this; return r.parentTask = t, r.input = e, r.extractedFaces = n, r } var wy, Cy = (Pp(Ey, wy = xy), Ey.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n, r = this; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return [4, zg(e = t.sent(), this.input, function (e) { return Lp(r, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return [4, Promise.all(e.map(function (t) { return vy.faceExpressionNet.predictExpressions(t) }))]; case 1: return [2, t.sent()] } }) }) }, this.extractedFaces)]; case 2: return n = t.sent(), [2, e.map(function (t, e) { return im(t, n[e]) })] } }) }) }, Ey.prototype.withAgeAndGender = function () { return new By(this, this.input) }, Ey); function Ey() { return null !== wy && wy.apply(this, arguments) || this } var _y, Iy = (Pp(Ry, _y = xy), Ry.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return (e = t.sent()) ? [4, Ug(e, this.input, function (t) { return vy.faceExpressionNet.predictExpressions(t) }, this.extractedFaces)] : [2]; case 2: return n = t.sent(), [2, im(e, n)] } }) }) }, Ry.prototype.withAgeAndGender = function () { return new zy(this, this.input) }, Ry); function Ry() { return null !== _y && _y.apply(this, arguments) || this } var ky, Sy = (Pp(Dy, ky = Cy), Dy.prototype.withAgeAndGender = function () { return new Gy(this, this.input) }, Dy.prototype.withFaceDescriptors = function () { return new Qy(this, this.input) }, Dy); function Dy() { return null !== ky && ky.apply(this, arguments) || this } var Ay, Ty = (Pp(Ny, Ay = Iy), Ny.prototype.withAgeAndGender = function () { return new jy(this, this.input) }, Ny.prototype.withFaceDescriptor = function () { return new ex(this, this.input) }, Ny); function Ny() { return null !== Ay && Ay.apply(this, arguments) || this } var Fy, My = (Pp(Oy, Fy = Lg), Oy); function Oy(t, e, n) { var r = Fy.call(this) || this; return r.parentTask = t, r.input = e, r.extractedFaces = n, r } var Py, By = (Pp(Ly, Py = My), Ly.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, o, n = this; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return [4, zg(e = t.sent(), this.input, function (e) { return Lp(n, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return [4, Promise.all(e.map(function (t) { return vy.ageGenderNet.predictAgeAndGender(t) }))]; case 1: return [2, t.sent()] } }) }) }, this.extractedFaces)]; case 2: return o = t.sent(), [2, e.map(function (t, e) { var n = o[e], r = n.age; return Ym($m(t, n.gender, n.genderProbability), r) })] } }) }) }, Ly.prototype.withFaceExpressions = function () { return new Cy(this, this.input) }, Ly); function Ly() { return null !== Py && Py.apply(this, arguments) || this } var Wy, zy = (Pp(Uy, Wy = My), Uy.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n, r, o, i; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return (e = t.sent()) ? [4, Ug(e, this.input, function (t) { return vy.ageGenderNet.predictAgeAndGender(t) }, this.extractedFaces)] : [2]; case 2: return n = t.sent(), r = n.age, o = n.gender, i = n.genderProbability, [2, Ym($m(e, o, i), r)] } }) }) }, Uy.prototype.withFaceExpressions = function () { return new Iy(this, this.input) }, Uy); function Uy() { return null !== Wy && Wy.apply(this, arguments) || this } var Vy, Gy = (Pp(Hy, Vy = By), Hy.prototype.withFaceExpressions = function () { return new Sy(this, this.input) }, Hy.prototype.withFaceDescriptors = function () { return new Qy(this, this.input) }, Hy); function Hy() { return null !== Vy && Vy.apply(this, arguments) || this } var qy, jy = (Pp(Ky, qy = zy), Ky.prototype.withFaceExpressions = function () { return new Ty(this, this.input) }, Ky.prototype.withFaceDescriptor = function () { return new ex(this, this.input) }, Ky); function Ky() { return null !== qy && qy.apply(this, arguments) || this } var Xy, Yy = (Pp($y, Xy = Lg), $y); function $y(t, e) { var n = Xy.call(this) || this; return n.parentTask = t, n.input = e, n } var Jy, Qy = (Pp(Zy, Jy = Yy), Zy.prototype.run = function () { return Lp(this, void 0, void 0, function () { var n; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return [4, zg(n = t.sent(), this.input, function (t) { return Promise.all(t.map(function (t) { return vy.faceRecognitionNet.computeFaceDescriptor(t) })) }, null, function (t) { return t.landmarks.align(null, { useDlibAlignment: !0 }) })]; case 2: return [2, t.sent().map(function (t, e) { return Xm(n[e], t) })] } }) }) }, Zy.prototype.withFaceExpressions = function () { return new Sy(this, this.input) }, Zy.prototype.withAgeAndGender = function () { return new Gy(this, this.input) }, Zy); function Zy() { return null !== Jy && Jy.apply(this, arguments) || this } var tx, ex = (Pp(nx, tx = Yy), nx.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return (e = t.sent()) ? [4, Ug(e, this.input, function (t) { return vy.faceRecognitionNet.computeFaceDescriptor(t) }, null, function (t) { return t.landmarks.align(null, { useDlibAlignment: !0 }) })] : [2]; case 2: return n = t.sent(), [2, Xm(e, n)] } }) }) }, nx.prototype.withFaceExpressions = function () { return new Ty(this, this.input) }, nx.prototype.withAgeAndGender = function () { return new jy(this, this.input) }, nx); function nx() { return null !== tx && tx.apply(this, arguments) || this } var rx, ox = (Pp(ix, rx = Lg), Object.defineProperty(ix.prototype, "landmarkNet", { get: function () { return this.useTinyLandmarkNet ? vy.faceLandmark68TinyNet : vy.faceLandmark68Net }, enumerable: !0, configurable: !0 }), ix); function ix(t, e, n) { var r = rx.call(this) || this; return r.parentTask = t, r.input = e, r.useTinyLandmarkNet = n, r } var ax, sx = (Pp(ux, ax = ox), ux.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n, r, o, i, a = this; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return e = t.sent(), n = e.map(function (t) { return t.detection }), this.input instanceof bt ? [4, Cv(this.input, n)] : [3, 3]; case 2: return o = t.sent(), [3, 5]; case 3: return [4, wv(this.input, n)]; case 4: o = t.sent(), t.label = 5; case 5: return r = o, [4, Promise.all(r.map(function (t) { return a.landmarkNet.detectLandmarks(t) }))]; case 6: return i = t.sent(), r.forEach(function (t) { return t instanceof bt && t.dispose() }), [2, e.map(function (t, e) { return sm(t, i[e]) })] } }) }) }, ux.prototype.withFaceExpressions = function () { return new Sy(this, this.input) }, ux.prototype.withAgeAndGender = function () { return new Gy(this, this.input) }, ux.prototype.withFaceDescriptors = function () { return new Qy(this, this.input) }, ux); function ux() { return null !== ax && ax.apply(this, arguments) || this } var cx, lx = (Pp(hx, cx = ox), hx.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n, r, o, i; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.parentTask]; case 1: return (e = t.sent()) ? (n = e.detection, this.input instanceof bt ? [4, Cv(this.input, [n])] : [3, 3]) : [2]; case 2: return o = t.sent(), [3, 5]; case 3: return [4, wv(this.input, [n])]; case 4: o = t.sent(), t.label = 5; case 5: return r = o, [4, this.landmarkNet.detectLandmarks(r[0])]; case 6: return i = t.sent(), r.forEach(function (t) { return t instanceof bt && t.dispose() }), [2, sm(e, i)] } }) }) }, hx.prototype.withFaceExpressions = function () { return new Ty(this, this.input) }, hx.prototype.withAgeAndGender = function () { return new jy(this, this.input) }, hx.prototype.withFaceDescriptor = function () { return new ex(this, this.input) }, hx); function hx() { return null !== cx && cx.apply(this, arguments) || this } var fx, px = (Pp(dx, fx = Lg), dx); function dx(t, e) { void 0 === e && (e = new sg); var n = fx.call(this) || this; return n.input = t, n.options = e, n } var vx, mx = (Pp(gx, vx = px), gx.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n, r, o; return Wp(this, function (t) { switch (t.label) { case 0: return n = (e = this).input, (r = e.options) instanceof Jm ? [4, vy.mtcnn.forward(n, r)] : [3, 2]; case 1: return [2, t.sent().map(function (t) { return t.detection })]; case 2: if (!(o = r instanceof Pg ? function (t) { return vy.tinyFaceDetector.locateFaces(t, r) } : r instanceof sg ? function (t) { return vy.ssdMobilenetv1.locateFaces(t, r) } : r instanceof kg ? function (t) { return vy.tinyYolov2.locateFaces(t, r) } : null)) throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | MtcnnOptions | TinyYolov2Options"); return [2, o(n)] } }) }) }, gx.prototype.runAndExtendWithFaceDetections = function () { var t = this; return new Promise(function (n) { return Lp(t, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.run()]; case 1: return e = t.sent(), [2, n(e.map(function (t) { return Hd({}, t) }))] } }) }) }) }, gx.prototype.withFaceLandmarks = function (t) { return void 0 === t && (t = !1), new sx(this.runAndExtendWithFaceDetections(), this.input, t) }, gx.prototype.withFaceExpressions = function () { return new Cy(this.runAndExtendWithFaceDetections(), this.input) }, gx.prototype.withAgeAndGender = function () { return new By(this.runAndExtendWithFaceDetections(), this.input) }, gx); function gx() { return null !== vx && vx.apply(this, arguments) || this } var yx, xx = (Pp(bx, yx = px), bx.prototype.run = function () { return Lp(this, void 0, void 0, function () { var e, n; return Wp(this, function (t) { switch (t.label) { case 0: return [4, new mx(this.input, this.options)]; case 1: return e = t.sent(), n = e[0], e.forEach(function (t) { t.score > n.score && (n = t) }), [2, n] } }) }) }, bx.prototype.runAndExtendWithFaceDetection = function () { var t = this; return new Promise(function (n) { return Lp(t, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return [4, this.run()]; case 1: return e = t.sent(), [2, n(e ? Hd({}, e) : void 0)] } }) }) }) }, bx.prototype.withFaceLandmarks = function (t) { return void 0 === t && (t = !1), new lx(this.runAndExtendWithFaceDetection(), this.input, t) }, bx.prototype.withFaceExpressions = function () { return new Iy(this.runAndExtendWithFaceDetection(), this.input) }, bx.prototype.withAgeAndGender = function () { return new zy(this.runAndExtendWithFaceDetection(), this.input) }, bx); function bx() { return null !== yx && yx.apply(this, arguments) || this } function wx(t, e) { return void 0 === e && (e = new sg), new mx(t, e) } function Cx(e, n) { return Lp(this, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return console.warn("allFacesSsdMobilenetv1 is deprecated and will be removed soon, use the high level api instead"), [4, wx(e, new sg(n ? { minConfidence: n } : {})).withFaceLandmarks().withFaceDescriptors()]; case 1: return [2, t.sent()] } }) }) } var Ex = Cx; function _x(t, e) { if (t.length !== e.length) throw new Error("euclideanDistance: arr1.length !== arr2.length"); var n = Array.from(t), r = Array.from(e); return Math.sqrt(n.map(function (t, e) { return t - r[e] }).reduce(function (t, e) { return t + Math.pow(e, 2) }, 0)) } var Ix = (Object.defineProperty(Rx.prototype, "labeledDescriptors", { get: function () { return this._labeledDescriptors }, enumerable: !0, configurable: !0 }), Object.defineProperty(Rx.prototype, "distanceThreshold", { get: function () { return this._distanceThreshold }, enumerable: !0, configurable: !0 }), Rx.prototype.computeMeanDistance = function (e, t) { return t.map(function (t) { return _x(t, e) }).reduce(function (t, e) { return t + e }, 0) / (t.length || 1) }, Rx.prototype.matchDescriptor = function (r) { var o = this; return this.labeledDescriptors.map(function (t) { var e = t.descriptors, n = t.label; return new Nd(n, o.computeMeanDistance(r, e)) }).reduce(function (t, e) { return t.distance < e.distance ? t : e }) }, Rx.prototype.findBestMatch = function (t) { var e = this.matchDescriptor(t); return e.distance < this.distanceThreshold ? e : new Nd("unknown", e.distance) }, Rx.prototype.toJSON = function () { return { distanceThreshold: this.distanceThreshold, labeledDescriptors: this.labeledDescriptors.map(function (t) { return t.toJSON() }) } }, Rx.fromJSON = function (t) { return new Rx(t.labeledDescriptors.map(function (t) { return Bd.fromJSON(t) }), t.distanceThreshold) }, Rx); function Rx(t, e) { void 0 === e && (e = .6), this._distanceThreshold = e; var n = Array.isArray(t) ? t : [t]; if (!n.length) throw new Error("FaceRecognizer.constructor - expected atleast one input"); function r() { return "person " + o++ } var o = 1; this._labeledDescriptors = n.map(function (t) { if (t instanceof Bd) return t; if (t instanceof Float32Array) return new Bd(r(), [t]); if (t.descriptor && t.descriptor instanceof Float32Array) return new Bd(r(), [t.descriptor]); throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>") }) } c.AgeGenderNet = wm, c.BoundingBox = ud, c.Box = id, c.ComposableTask = Lg, c.ComputeAllFaceDescriptorsTask = Qy, c.ComputeFaceDescriptorsTaskBase = Yy, c.ComputeSingleFaceDescriptorTask = ex, c.DetectAllFaceLandmarksTask = sx, c.DetectAllFacesTask = mx, c.DetectFaceLandmarksTaskBase = ox, c.DetectFacesTaskBase = px, c.DetectSingleFaceLandmarksTask = lx, c.DetectSingleFaceTask = xx, c.Dimensions = Up, c.FACE_EXPRESSION_LABELS = Qv, c.FaceDetection = pd, c.FaceDetectionNet = dg, c.FaceExpressionNet = nm, c.FaceExpressions = Zv, c.FaceLandmark68Net = km, c.FaceLandmark68TinyNet = Fm, c.FaceLandmarkNet = Pm, c.FaceLandmarks = _d, c.FaceLandmarks5 = kd, c.FaceLandmarks68 = Ad, c.FaceMatch = Nd, c.FaceMatcher = Ix, c.FaceRecognitionNet = jm, c.LabeledBox = Od, c.LabeledFaceDescriptors = Bd, c.Mtcnn = oy, c.MtcnnOptions = Jm, c.NetInput = yv, c.NeuralNetwork = kv, c.ObjectDetection = ld, c.Point = rd, c.PredictedBox = Ud, c.Rect = Cd, c.SsdMobilenetv1 = lg, c.SsdMobilenetv1Options = sg, c.TinyFaceDetector = cy, c.TinyFaceDetectorOptions = Pg, c.TinyYolov2 = Fg, c.TinyYolov2Options = kg, c.allFaces = Ex, c.allFacesMtcnn = function (e, n) { return void 0 === n && (n = {}), Lp(this, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return console.warn("allFacesMtcnn is deprecated and will be removed soon, use the high level api instead"), [4, wx(e, new Jm(n)).withFaceLandmarks().withFaceDescriptors()]; case 1: return [2, t.sent()] } }) }) }, c.allFacesSsdMobilenetv1 = Cx, c.allFacesTinyYolov2 = function (e, n) { return void 0 === n && (n = {}), Lp(this, void 0, void 0, function () { return Wp(this, function (t) { switch (t.label) { case 0: return console.warn("allFacesTinyYolov2 is deprecated and will be removed soon, use the high level api instead"), [4, wx(e, new kg(n)).withFaceLandmarks().withFaceDescriptors()]; case 1: return [2, t.sent()] } }) }) }, c.awaitMediaLoaded = lv, c.bufferToImage = hv, c.computeFaceDescriptor = function (t) { return vy.faceRecognitionNet.computeFaceDescriptor(t) }, c.createCanvas = pv, c.createCanvasFromMedia = dv, c.createFaceDetectionNet = function (t) { return fg(t) }, c.createFaceRecognitionNet = function (t) { var e = new jm; return e.extractWeights(t), e }, c.createMtcnn = function (t) { var e = new oy; return e.extractWeights(t), e }, c.createSsdMobilenetv1 = fg, c.createTinyFaceDetector = function (t) { var e = new cy; return e.extractWeights(t), e }, c.createTinyYolov2 = function (t, e) { void 0 === e && (e = !0); var n = new Fg(e); return n.extractWeights(t), n }, c.detectAllFaces = wx, c.detectFaceLandmarks = fy, c.detectFaceLandmarksTiny = function (t) { return vy.faceLandmark68TinyNet.detectLandmarks(t) }, c.detectLandmarks = yy, c.detectSingleFace = function (t, e) { return void 0 === e && (e = new sg), new xx(t, e) }, c.draw = hm, c.env = tv, c.euclideanDistance = _x, c.extendWithAge = Ym, c.extendWithFaceDescriptor = Xm, c.extendWithFaceDetection = Hd, c.extendWithFaceExpressions = im, c.extendWithFaceLandmarks = sm, c.extendWithGender = $m, c.extractFaceTensors = Cv, c.extractFaces = wv, c.fetchImage = function (r) { return Lp(this, void 0, void 0, function () { var e, n; return Wp(this, function (t) { switch (t.label) { case 0: return [4, Ev(r)]; case 1: return [4, (e = t.sent()).blob()]; case 2: if (!(n = t.sent()).type.startsWith("image/")) throw new Error("fetchImage - expected blob type to be of type image/*, instead have: " + n.type + ", for url: " + e.url); return [2, hv(n)] } }) }) }, c.fetchJson = _v, c.fetchNetWeights = function (n) { return Lp(this, void 0, void 0, function () { var e; return Wp(this, function (t) { switch (t.label) { case 0: return e = Float32Array.bind, [4, Ev(n)]; case 1: return [4, t.sent().arrayBuffer()]; case 2: return [2, new (e.apply(Float32Array, [void 0, t.sent()]))] } }) }) }, c.fetchOrThrow = Ev, c.getContext2dOrThrow = nv, c.getMediaDimensions = fv, c.imageTensorToCanvas = vv, c.imageToSquare = gv, c.inverseSigmoid = function (t) { return Math.log(t / (1 - t)) }, c.iou = vd, c.isMediaElement = mv, c.isMediaLoaded = cv, c.isWithAge = function (t) { return "number" == typeof t.age }, c.isWithFaceDetection = Gd, c.isWithFaceExpressions = om, c.isWithFaceLandmarks = am, c.isWithGender = function (t) { return (t.gender === c.Gender.MALE || t.gender === c.Gender.FEMALE) && ed(t.genderProbability) }, c.loadAgeGenderModel = function (t) { return vy.ageGenderNet.load(t) }, c.loadFaceDetectionModel = my, c.loadFaceExpressionModel = function (t) { return vy.faceExpressionNet.load(t) }, c.loadFaceLandmarkModel = function (t) { return vy.faceLandmark68Net.load(t) }, c.loadFaceLandmarkTinyModel = function (t) { return vy.faceLandmark68TinyNet.load(t) }, c.loadFaceRecognitionModel = function (t) { return vy.faceRecognitionNet.load(t) }, c.loadMtcnnModel = function (t) { return vy.mtcnn.load(t) }, c.loadSsdMobilenetv1Model = py, c.loadTinyFaceDetectorModel = function (t) { return vy.tinyFaceDetector.load(t) }, c.loadTinyYolov2Model = function (t) { return vy.tinyYolov2.load(t) }, c.loadWeightMap = Rv, c.locateFaces = gy, c.matchDimensions = function (t, e, n) { void 0 === n && (n = !1); var r = n ? fv(e) : e, o = r.width, i = r.height; return { width: t.width = o, height: t.height = i } }, c.minBbox = md, c.mtcnn = function (t, e) { return vy.mtcnn.forward(t, e) }, c.nets = vy, c.nonMaxSuppression = gd, c.normalize = yd, c.padToSquare = xd, c.predictAgeAndGender = function (t) { return vy.ageGenderNet.predictAgeAndGender(t) }, c.recognizeFaceExpressions = function (t) { return vy.faceExpressionNet.predictExpressions(t) }, c.resizeResults = function e(t, n) { var r = new Up(n.width, n.height), o = r.width, i = r.height; if (o <= 0 || i <= 0) throw new Error("resizeResults - invalid dimensions: " + JSON.stringify({ width: o, height: i })); if (Array.isArray(t)) return t.map(function (t) { return e(t, { width: o, height: i }) }); if (am(t)) { var a = t.detection.forSize(o, i), s = t.unshiftedLandmarks.forSize(a.box.width, a.box.height); return sm(Hd(t, a), s) } return Gd(t) ? Hd(t, t.detection.forSize(o, i)) : t instanceof _d || t instanceof pd ? t.forSize(o, i) : t }, c.resolveInput = ev, c.shuffleArray = function (t) { for (var e = t.slice(), n = e.length - 1; 0 < n; n--) { var r = Math.floor(Math.random() * (n + 1)), o = e[n]; e[n] = e[r], e[r] = o } return e }, c.sigmoid = bd, c.ssdMobilenetv1 = hy, c.tf = Fp, c.tinyFaceDetector = function (t, e) { return vy.tinyFaceDetector.locateFaces(t, e) }, c.tinyYolov2 = function (t, e) { return vy.tinyYolov2.locateFaces(t, e) }, c.toNetInput = bv, c.utils = nd, c.validateConfig = wg, Object.defineProperty(c, "__esModule", { value: !0 }) });
  