"use strict";
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var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
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return new (P || (P = Promise))(function (resolve, reject) {
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function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
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function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
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function step(result) { result.done ? resolve(result.value) : new P(function (resolve) { resolve(result.value); }).then(fulfilled, rejected); }
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step((generator = generator.apply(thisArg, _arguments || [])).next());
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});
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};
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var __generator = (this && this.__generator) || function (thisArg, body) {
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var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;
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return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
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function verb(n) { return function (v) { return step([n, v]); }; }
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function step(op) {
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if (f) throw new TypeError("Generator is already executing.");
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while (_) try {
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if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
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if (y = 0, t) op = [op[0] & 2, t.value];
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switch (op[0]) {
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case 0: case 1: t = op; break;
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case 4: _.label++; return { value: op[1], done: false };
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case 5: _.label++; y = op[1]; op = [0]; continue;
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case 7: op = _.ops.pop(); _.trys.pop(); continue;
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default:
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if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
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if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
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if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
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if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
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if (t[2]) _.ops.pop();
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_.trys.pop(); continue;
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}
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op = body.call(thisArg, _);
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} catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
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if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
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}
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};
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var _this = this;
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Object.defineProperty(exports, "__esModule", { value: true });
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/**
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* @license
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* Copyright 2018 Google LLC. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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var tf = require("../index");
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var jasmine_util_1 = require("../jasmine_util");
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var test_util_1 = require("../test_util");
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jasmine_util_1.describeWithFlags('complex64', jasmine_util_1.ALL_ENVS, function () {
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it('tf.complex', function () { return __awaiter(_this, void 0, void 0, function () {
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var real, imag, complex, _a;
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return __generator(this, function (_b) {
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switch (_b.label) {
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case 0:
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real = tf.tensor1d([3, 30]);
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imag = tf.tensor1d([4, 40]);
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complex = tf.complex(real, imag);
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expect(complex.dtype).toBe('complex64');
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expect(complex.shape).toEqual(real.shape);
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_a = test_util_1.expectArraysClose;
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return [4 /*yield*/, complex.data()];
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case 1:
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_a.apply(void 0, [_b.sent(), [3, 4, 30, 40]]);
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return [2 /*return*/];
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}
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});
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}); });
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it('tf.real', function () { return __awaiter(_this, void 0, void 0, function () {
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var complex, real, _a;
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return __generator(this, function (_b) {
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switch (_b.label) {
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case 0:
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complex = tf.complex([3, 30], [4, 40]);
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real = tf.real(complex);
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expect(real.dtype).toBe('float32');
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expect(real.shape).toEqual([2]);
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_a = test_util_1.expectArraysClose;
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return [4 /*yield*/, real.data()];
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case 1:
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_a.apply(void 0, [_b.sent(), [3, 30]]);
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return [2 /*return*/];
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}
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});
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}); });
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it('tf.imag', function () { return __awaiter(_this, void 0, void 0, function () {
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var complex, imag, _a;
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return __generator(this, function (_b) {
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switch (_b.label) {
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case 0:
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complex = tf.complex([3, 30], [4, 40]);
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imag = tf.imag(complex);
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expect(imag.dtype).toBe('float32');
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expect(imag.shape).toEqual([2]);
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_a = test_util_1.expectArraysClose;
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return [4 /*yield*/, imag.data()];
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case 1:
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_a.apply(void 0, [_b.sent(), [4, 40]]);
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return [2 /*return*/];
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}
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});
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}); });
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it('throws when shapes dont match', function () {
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var real = tf.tensor1d([3, 30]);
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var imag = tf.tensor1d([4, 40, 50]);
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var re = /real and imag shapes, 2 and 3, must match in call to tf.complex\(\)/;
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expect(function () { return tf.complex(real, imag); }).toThrowError(re);
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});
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});
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var BYTES_PER_COMPLEX_ELEMENT = 4 * 2;
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jasmine_util_1.describeWithFlags('complex64 memory', jasmine_util_1.BROWSER_ENVS, function () {
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it('usage', function () { return __awaiter(_this, void 0, void 0, function () {
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var numTensors, numBuffers, startTensors, real1, imag1, complex1, real2, imag2, complex2, result, _a, real, _b, imag, _c;
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return __generator(this, function (_d) {
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switch (_d.label) {
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case 0:
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numTensors = tf.memory().numTensors;
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numBuffers = tf.memory().numDataBuffers;
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startTensors = numTensors;
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real1 = tf.tensor1d([1]);
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imag1 = tf.tensor1d([2]);
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complex1 = tf.complex(real1, imag1);
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// 5 new Tensors: real1, imag1, complex1, and two internal clones.
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expect(tf.memory().numTensors).toBe(numTensors + 5);
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// Only 3 new data buckets are actually created.
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expect(tf.memory().numDataBuffers).toBe(numBuffers + 3);
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numTensors = tf.memory().numTensors;
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numBuffers = tf.memory().numDataBuffers;
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real2 = tf.tensor1d([3]);
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imag2 = tf.tensor1d([4]);
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complex2 = tf.complex(real2, imag2);
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// 5 new Tensors: real1, imag1, complex1, and two internal clones.
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expect(tf.memory().numTensors).toBe(numTensors + 5);
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// Only 3 new data buckets are actually created.
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expect(tf.memory().numDataBuffers).toBe(numBuffers + 3);
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numTensors = tf.memory().numTensors;
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numBuffers = tf.memory().numDataBuffers;
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result = complex1.add(complex2);
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// A complex tensor is created, which is composed of 2 underlying tensors.
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expect(tf.memory().numTensors).toBe(numTensors + 3);
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numTensors = tf.memory().numTensors;
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expect(result.dtype).toBe('complex64');
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expect(result.shape).toEqual([1]);
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_a = test_util_1.expectArraysClose;
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return [4 /*yield*/, result.data()];
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case 1:
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_a.apply(void 0, [_d.sent(), [4, 6]]);
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real = tf.real(result);
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expect(tf.memory().numTensors).toBe(numTensors + 1);
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numTensors = tf.memory().numTensors;
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_b = test_util_1.expectArraysClose;
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return [4 /*yield*/, real.data()];
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case 2:
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_b.apply(void 0, [_d.sent(), [4]]);
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imag = tf.imag(result);
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expect(tf.memory().numTensors).toBe(numTensors + 1);
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numTensors = tf.memory().numTensors;
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_c = test_util_1.expectArraysClose;
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return [4 /*yield*/, imag.data()];
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case 3:
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_c.apply(void 0, [_d.sent(), [6]]);
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// After disposing, there should be no tensors.
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real1.dispose();
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imag1.dispose();
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real2.dispose();
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imag2.dispose();
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complex1.dispose();
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complex2.dispose();
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result.dispose();
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real.dispose();
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imag.dispose();
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expect(tf.memory().numTensors).toBe(startTensors);
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return [2 /*return*/];
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}
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});
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}); });
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it('tf.complex disposing underlying tensors', function () { return __awaiter(_this, void 0, void 0, function () {
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var numTensors, real, imag, complex, _a;
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return __generator(this, function (_b) {
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switch (_b.label) {
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case 0:
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numTensors = tf.memory().numTensors;
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real = tf.tensor1d([3, 30]);
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imag = tf.tensor1d([4, 40]);
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expect(tf.memory().numTensors).toEqual(numTensors + 2);
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complex = tf.complex(real, imag);
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// real and imag are cloned.
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expect(tf.memory().numTensors).toEqual(numTensors + 5);
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real.dispose();
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imag.dispose();
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// A copy of real and imag still exist, the one owned by the complex tensor.
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expect(tf.memory().numTensors).toEqual(numTensors + 3);
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expect(complex.dtype).toBe('complex64');
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expect(complex.shape).toEqual(real.shape);
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_a = test_util_1.expectArraysClose;
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return [4 /*yield*/, complex.data()];
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case 1:
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_a.apply(void 0, [_b.sent(), [3, 4, 30, 40]]);
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complex.dispose();
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expect(tf.memory().numTensors).toEqual(numTensors);
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return [2 /*return*/];
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}
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});
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}); });
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it('reshape', function () { return __awaiter(_this, void 0, void 0, function () {
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var memoryBefore, a, b, _a, _b;
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return __generator(this, function (_c) {
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switch (_c.label) {
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case 0:
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memoryBefore = tf.memory();
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a = tf.complex([[1, 3, 5], [7, 9, 11]], [[2, 4, 6], [8, 10, 12]]);
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// 3 new tensors, the complex64 tensor and the 2 underlying float32 tensors.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors + 3);
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// Bytes should be counted once.
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expect(tf.memory().numBytes)
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.toBe(memoryBefore.numBytes + 6 * BYTES_PER_COMPLEX_ELEMENT);
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b = a.reshape([6]);
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// 1 new tensor from the reshape.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors + 4);
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// No new bytes from a reshape.
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expect(tf.memory().numBytes)
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.toBe(memoryBefore.numBytes + 6 * BYTES_PER_COMPLEX_ELEMENT);
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expect(b.dtype).toBe('complex64');
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expect(b.shape).toEqual([6]);
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_a = test_util_1.expectArraysClose;
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return [4 /*yield*/, a.data()];
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case 1:
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_b = [_c.sent()];
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return [4 /*yield*/, b.data()];
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case 2:
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_a.apply(void 0, _b.concat([_c.sent()]));
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b.dispose();
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// 1 complex tensor should be disposed.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors + 3);
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// Byte count should not change because the refcounts are all 1.
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expect(tf.memory().numBytes)
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.toBe(memoryBefore.numBytes + 6 * BYTES_PER_COMPLEX_ELEMENT);
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a.dispose();
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// All the tensors should now be disposed.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors);
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// The underlying memory should now be released.
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expect(tf.memory().numBytes).toBe(memoryBefore.numBytes);
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return [2 /*return*/];
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}
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});
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}); });
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it('clone', function () { return __awaiter(_this, void 0, void 0, function () {
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var memoryBefore, a, b, _a, _b;
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return __generator(this, function (_c) {
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switch (_c.label) {
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case 0:
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memoryBefore = tf.memory();
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a = tf.complex([[1, 3, 5], [7, 9, 11]], [[2, 4, 6], [8, 10, 12]]);
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// 3 new tensors, the complex64 tensor and the 2 underlying float32 tensors.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors + 3);
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// Bytes should be counted once
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expect(tf.memory().numBytes)
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.toBe(memoryBefore.numBytes + 6 * BYTES_PER_COMPLEX_ELEMENT);
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b = a.clone();
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// 1 new tensor from the clone.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors + 4);
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// No new bytes from a clone.
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expect(tf.memory().numBytes)
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.toBe(memoryBefore.numBytes + 6 * BYTES_PER_COMPLEX_ELEMENT);
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expect(b.dtype).toBe('complex64');
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_a = test_util_1.expectArraysClose;
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return [4 /*yield*/, a.data()];
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case 1:
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_b = [_c.sent()];
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return [4 /*yield*/, b.data()];
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case 2:
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_a.apply(void 0, _b.concat([_c.sent()]));
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b.dispose();
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// 1 complex tensor should be disposed.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors + 3);
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// Byte count should not change because the refcounts are all 1.
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expect(tf.memory().numBytes)
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.toBe(memoryBefore.numBytes + 6 * BYTES_PER_COMPLEX_ELEMENT);
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a.dispose();
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// All the tensors should now be disposed.
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expect(tf.memory().numTensors).toBe(memoryBefore.numTensors);
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// The underlying memory should now be released.
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expect(tf.memory().numBytes).toBe(memoryBefore.numBytes);
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return [2 /*return*/];
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}
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});
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}); });
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});
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//# sourceMappingURL=complex_ops_test.js.map
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