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| "use strict";
| /**
| * @license
| * Copyright 2017 Google Inc. All Rights Reserved.
| * Licensed under the Apache License, Version 2.0 (the "License");
| * you may not use this file except in compliance with the License.
| * You may obtain a copy of the License at
| *
| * http://www.apache.org/licenses/LICENSE-2.0
| *
| * Unless required by applicable law or agreed to in writing, software
| * distributed under the License is distributed on an "AS IS" BASIS,
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
| * See the License for the specific language governing permissions and
| * limitations under the License.
| * =============================================================================
| */
| var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
| return new (P || (P = Promise))(function (resolve, reject) {
| function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
| function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
| function step(result) { result.done ? resolve(result.value) : new P(function (resolve) { resolve(result.value); }).then(fulfilled, rejected); }
| step((generator = generator.apply(thisArg, _arguments || [])).next());
| });
| };
| var __generator = (this && this.__generator) || function (thisArg, body) {
| var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;
| return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
| function verb(n) { return function (v) { return step([n, v]); }; }
| function step(op) {
| if (f) throw new TypeError("Generator is already executing.");
| while (_) try {
| 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;
| if (y = 0, t) op = [op[0] & 2, t.value];
| switch (op[0]) {
| case 0: case 1: t = op; break;
| case 4: _.label++; return { value: op[1], done: false };
| case 5: _.label++; y = op[1]; op = [0]; continue;
| case 7: op = _.ops.pop(); _.trys.pop(); continue;
| default:
| if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
| if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
| if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
| if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
| if (t[2]) _.ops.pop();
| _.trys.pop(); continue;
| }
| op = body.call(thisArg, _);
| } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
| if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
| }
| };
| var _this = this;
| Object.defineProperty(exports, "__esModule", { value: true });
| var tf = require("../index");
| var jasmine_util_1 = require("../jasmine_util");
| var test_util_1 = require("../test_util");
| jasmine_util_1.describeWithFlags('conv3dTranspose', jasmine_util_1.ALL_ENVS, function () {
| // Reference Python TensorFlow code
| // ```python
| // import numpy as np
| // import tensorflow as tf
| // tf.enable_eager_execution()
| // x = np.array([2], dtype = np.float32).reshape(1, 1, 1, 1, 1)
| // w = np.array([5, 4, 8, 7, 1, 2, 6, 3], dtype = np.float32).reshape(2, 2, 2,
| // 1, 1)
| // tf.nn.conv3d_transpose(x, w, output_shape=[1, 2, 2, 2, 1], padding='VALID')
| // ```
| it('input=2x2x2x1,d2=1,f=2,s=1,p=valid', function () { return __awaiter(_this, void 0, void 0, function () {
| var origInputDepth, origOutputDepth, inputShape, fSize, origPad, origStride, x, w, result, expected, _a;
| return __generator(this, function (_b) {
| switch (_b.label) {
| case 0:
| origInputDepth = 1;
| origOutputDepth = 1;
| inputShape = [1, 1, 1, origOutputDepth];
| fSize = 2;
| origPad = 'valid';
| origStride = 1;
| x = tf.tensor4d([2], inputShape);
| w = tf.tensor5d([5, 4, 8, 7, 1, 2, 6, 3], [fSize, fSize, fSize, origInputDepth, origOutputDepth]);
| result = tf.conv3dTranspose(x, w, [2, 2, 2, 1], origStride, origPad);
| expected = [10, 8, 16, 14, 2, 4, 12, 6];
| expect(result.shape).toEqual([2, 2, 2, 1]);
| _a = test_util_1.expectArraysClose;
| return [4 /*yield*/, result.data()];
| case 1:
| _a.apply(void 0, [_b.sent(), expected]);
| return [2 /*return*/];
| }
| });
| }); });
| // Reference Python TensorFlow code
| // ```python
| // import numpy as np
| // import tensorflow as tf
| // tf.enable_eager_execution()
| // x = np.array([2, 3], dtype = np.float32).reshape(2, 1, 1, 1, 1, 1)
| // w = np.array([5, 4, 8, 7, 1, 2, 6, 3], dtype = np.float32).reshape(2,
| // 2, 2, 1, 1)
| // tf.nn.conv3d_transpose(x, w, output_shape=[2, 2, 2, 2, 1], padding='VALID')
| // ```
| it('input=2x2x2x1,d2=1,f=2,s=1,p=valid, batch=2', function () { return __awaiter(_this, void 0, void 0, function () {
| var origInputDepth, origOutputDepth, inputShape, fSize, origPad, origStride, x, w, result, expected, _a;
| return __generator(this, function (_b) {
| switch (_b.label) {
| case 0:
| origInputDepth = 1;
| origOutputDepth = 1;
| inputShape = [2, 1, 1, 1, origOutputDepth];
| fSize = 2;
| origPad = 'valid';
| origStride = 1;
| x = tf.tensor5d([2, 3], inputShape);
| w = tf.tensor5d([5, 4, 8, 7, 1, 2, 6, 3], [fSize, fSize, fSize, origInputDepth, origOutputDepth]);
| result = tf.conv3dTranspose(x, w, [2, 2, 2, 2, 1], origStride, origPad);
| expected = [10, 8, 16, 14, 2, 4, 12, 6, 15, 12, 24, 21, 3, 6, 18, 9];
| expect(result.shape).toEqual([2, 2, 2, 2, 1]);
| _a = test_util_1.expectArraysClose;
| return [4 /*yield*/, result.data()];
| case 1:
| _a.apply(void 0, [_b.sent(), expected]);
| return [2 /*return*/];
| }
| });
| }); });
| });
| //# sourceMappingURL=conv3d_transpose_test.js.map
|
|
