{ "cells": [ { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "JndnmDMp66FL" }, "source": [ "#### Copyright 2017 Google LLC." ] }, { "cell_type": "code", "execution_count": 0, "metadata": { "cellView": "both", "colab": { "autoexec": { "startup": false, "wait_interval": 0 } }, "colab_type": "code", "id": "hMqWDc_m6rUC" }, "outputs": [], "source": [ "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", "# you may not use this file except in compliance with the License.\n", "# You may obtain a copy of the License at\n", "#\n", "# https://www.apache.org/licenses/LICENSE-2.0\n", "#\n", "# Unless required by applicable law or agreed to in writing, software\n", "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", "# See the License for the specific language governing permissions and\n", "# limitations under the License." ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "cH-YtyZs7Gcg" }, "source": [ "# 准备工作:Hello World" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "r0QBC2kTixPn" }, "source": [ "**学习目标:**在浏览器中运行 TensorFlow 程序。" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "33fL46pgixPo" }, "source": [ "以下代码块为“Hello World”TensorFlow 程序。\n", "\n", "其中包含初始化代码(导入 TensorFlow 模块并启用“eager execution”,我们将在后续练习中详细介绍此操作),然后输出“Hello, world!”字符串常量。" ] }, { "cell_type": "code", "execution_count": 0, "metadata": { "cellView": "both", "colab": { "autoexec": { "startup": false, "wait_interval": 0 } }, "colab_type": "code", "id": "bRuPN7qo7ICp" }, "outputs": [], "source": [ "from __future__ import print_function\n", "\n", "import tensorflow as tf\n", "try:\n", " tf.contrib.eager.enable_eager_execution()\n", "except ValueError:\n", " pass # enable_eager_execution errors after its first call\n", "\n", "tensor = tf.constant('Hello, world!')\n", "tensor_value = tensor.numpy()\n", "print(tensor_value)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "Bl1nAshab6m5" }, "source": [ "## 要运行此程序,请执行以下操作\n", "\n", " 1. 点击代码块中的任意位置(例如,点击字词 `import`)。\n", "\n", " 2. 点击代码块左上角的右向三角图标,或按 ⌘/Ctrl+Enter 键。\n", "\n", " 程序需要几秒钟才会运行。如果一切顺利,程序会在代码块正下方显示 `Hello, world!` 字样\n", "\n", "整个程序仅包含一个代码块。不过,大部分练习都会包含多个代码块,在这种情况下,您应**按从上到下的顺序逐个运行代码块。**\n", "\n", "不按顺序运行代码块通常会导致错误。" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "UpzZ0Gv-uKf_" }, "source": [ "## 实用的键盘快捷键\n", "\n", "* **⌘/Ctrl+m,b:**在当前选择的单元格下方创建一个空白代码单元格\n", "* **⌘/Ctrl+m,i:**中断单元格的运行\n", "* **⌘/Ctrl+m,h:**显示所有键盘快捷键列表\n", "* 要查看关于任何 TensorFlow API 方法的文档,请将光标放置在其左括号的正后方,然后按 **Tab** 键:\n", "\n", " ![TensorFlow tf.constant 方法的弹出式文档](https://download.mlcc.google.cn/mledu-images/tf_pop_up_doc_example.png)" ] } ], "metadata": { "colab": { "collapsed_sections": [ "JndnmDMp66FL" ], "default_view": {}, "name": "hello_world.ipynb", "provenance": [], "version": "0.3.2", "views": {} }, "kernelspec": { "name": "python3", "display_name": "Python 3" } }, "nbformat": 4, "nbformat_minor": 0 }