{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "hello_world.ipynb",
"version": "0.3.2",
"views": {},
"default_view": {},
"collapsed_sections": ["JndnmDMp66FL"]
}
},
"cells": [
{
      "metadata": {
        "id": "JndnmDMp66FL",
        "colab_type": "text"
      },
      "source": [
        "#### Copyright 2017 Google LLC."
      ],
      "cell_type": "markdown"
    },
    {
      "metadata": {
        "id": "hMqWDc_m6rUC",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "cellView": "both"
      },
      "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": "code",
      "execution_count": 0,
      "outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "cH-YtyZs7Gcg",
"colab_type": "text"
},
"source": [
" # 准备工作：Hello World"]},
{
"cell_type": "markdown",
"metadata": {
"id": "r0QBC2kTixPn",
"colab_type": "text"
},
"source": [
" **学习目标：**在浏览器中运行 TensorFlow 程序。"]},
{
"cell_type": "markdown",
"metadata": {
"id": "33fL46pgixPo",
"colab_type": "text"
},
"source": [
" 以下是一个 \\'Hello World\\' TensorFlow 程序："]},
{
"metadata": {
"id": "bRuPN7qo7ICp",
"colab_type": "code",
"colab": {
"autoexec": {
"startup": false,
"wait_interval": 0
}
},
"cellView": "both"
},
"source": [
"import tensorflow as tf\n",
"\n",
"c = tf.constant('Hello, world!')\n",
"\n",
"with tf.Session() as sess:\n",
"\n",
"    print sess.run(c)"
],
"cell_type": "code",
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "Bl1nAshab6m5",
"colab_type": "text"
},
"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": {
"id": "UpzZ0Gv-uKf_",
"colab_type": "text"
},
"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://storage.googleapis.com/mledu-images/tf_constant_pop_up_doc.png)"]}
]
}