133 lines
6.8 KiB
Plaintext
133 lines
6.8 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "5d3957b1",
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"metadata": {
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"origin_pos": 0
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},
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"source": [
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"# 使用Jupyter Notebook\n",
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":label:`sec_jupyter`\n",
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"\n",
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"本节介绍如何使用Jupyter Notebook编辑和运行本书各章中的代码。确保你已按照 :ref:`chap_installation`中的说明安装了Jupyter并下载了代码。如果你想了解更多关于Jupyter的信息，请参阅其[文档](https://jupyter.readthedocs.io/en/latest/)中的优秀教程。 \n",
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"\n",
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"## 在本地编辑和运行代码\n",
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"\n",
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"假设本书代码的本地路径为`xx/yy/d2l-en/`。使用shell将目录更改为此路径（`cd xx/yy/d2l-en`）并运行命令`jupyter notebook`。如果浏览器未自动打开，请打开http://localhost:8888。此时你将看到Jupyter的界面以及包含本书代码的所有文件夹，如 :numref:`fig_jupyter00`所示\n",
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"\n",
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"\n",
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":width:`600px`\n",
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":label:`fig_jupyter00`\n",
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"\n",
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"你可以通过单击网页上显示的文件夹来访问notebook文件。它们通常有后缀“.ipynb”。为了简洁起见，我们创建了一个临时的“test.ipynb”文件。单击后显示的内容如 :numref:`fig_jupyter01`所示。此notebook包括一个标记单元格和一个代码单元格。标记单元格中的内容包括“This Is a Title”和“This is text.”。代码单元包含两行Python代码。 \n",
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"\n",
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"\n",
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":width:`600px`\n",
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":label:`fig_jupyter01`\n",
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"\n",
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"双击标记单元格以进入编辑模式。在单元格末尾添加一个新的文本字符串“Hello world.”，如 :numref:`fig_jupyter02`所示。 \n",
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"\n",
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"\n",
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":width:`600px`\n",
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":label:`fig_jupyter02`\n",
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"\n",
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"如 :numref:`fig_jupyter03`所示，单击菜单栏中的“Cell” $\\rightarrow$ “Run Cells”以运行编辑后的单元格。 \n",
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"\n",
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"\n",
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":width:`600px`\n",
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":label:`fig_jupyter03`\n",
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"\n",
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"运行后，markdown单元格如 :numref:`fig_jupyter04`所示。 \n",
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"\n",
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"\n",
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":width:`600px`\n",
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":label:`fig_jupyter04`\n",
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"\n",
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"接下来，单击代码单元。将最后一行代码后的元素乘以2，如 :numref:`fig_jupyter05`所示。 \n",
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"\n",
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"\n",
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":width:`600px`\n",
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":label:`fig_jupyter05`\n",
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"\n",
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"你还可以使用快捷键（默认情况下为Ctrl+Enter）运行单元格，并从 :numref:`fig_jupyter06`获取输出结果。 \n",
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"\n",
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"\n",
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":width:`600px`\n",
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":label:`fig_jupyter06`\n",
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"\n",
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"当一个notebook包含更多单元格时，我们可以单击菜单栏中的“Kernel”$\\rightarrow$“Restart & Run All”来运行整个notebook中的所有单元格。通过单击菜单栏中的“Help”$\\rightarrow$“Edit Keyboard Shortcuts”，可以根据你的首选项编辑快捷键。 \n",
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"\n",
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"## 高级选项\n",
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"\n",
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"除了本地编辑，还有两件事非常重要：以markdown格式编辑notebook和远程运行Jupyter。当我们想要在更快的服务器上运行代码时，后者很重要。前者很重要，因为Jupyter原生的ipynb格式存储了大量辅助数据，这些数据实际上并不特定于notebook中的内容，主要与代码的运行方式和运行位置有关。这让git感到困惑，并且使得合并贡献非常困难。幸运的是，还有另一种选择——在markdown中进行本地编辑。 \n",
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"\n",
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"### Jupyter中的Markdown文件\n",
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"\n",
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"如果你希望对本书的内容有所贡献，则需要在GitHub上修改源文件（md文件，而不是ipynb文件）。使用notedown插件，我们可以直接在Jupyter中修改md格式的notebook。 \n",
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"\n",
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"首先，安装notedown插件，运行Jupyter Notebook并加载插件：\n",
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"\n",
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"```\n",
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"pip install d2l-notedown # 你可能需要卸载原始notedown\n",
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"jupyter notebook --NotebookApp.contents_manager_class='notedown.NotedownContentsManager'\n",
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"```\n",
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"\n",
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"要在运行Jupyter Notebook时默认打开notedown插件，请执行以下操作：首先，生成一个Jupyter Notebook配置文件（如果已经生成了，可以跳过此步骤）。\n",
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"\n",
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"```\n",
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"jupyter notebook --generate-config\n",
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"```\n",
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"\n",
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"然后，在Jupyter Notebook配置文件的末尾添加以下行（对于Linux/macOS，通常位于`~/.jupyter/jupyter_notebook_config.py`）：\n",
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"\n",
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"```\n",
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"c.NotebookApp.contents_manager_class = 'notedown.NotedownContentsManager'\n",
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"```\n",
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"\n",
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"在这之后，你只需要运行`jupyter notebook`命令就可以默认打开notedown插件。 \n",
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"\n",
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"### 在远程服务器上运行Jupyter Notebook\n",
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"\n",
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"有时，你可能希望在远程服务器上运行Jupyter Notebook，并通过本地计算机上的浏览器访问它。如果本地计算机上安装了Linux或MacOS（Windows也可以通过PuTTY等第三方软件支持此功能），则可以使用端口转发：\n",
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"\n",
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"```\n",
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"ssh myserver -L 8888:localhost:8888\n",
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"```\n",
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"\n",
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"以上是远程服务器`myserver`的地址。然后我们可以使用http://localhost:8888 访问运行Jupyter Notebook的远程服务器`myserver`。下一节将详细介绍如何在AWS实例上运行Jupyter Notebook。 \n",
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"\n",
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"### 执行时间\n",
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"\n",
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"我们可以使用`ExecuteTime`插件来计算Jupyter Notebook中每个代码单元的执行时间。使用以下命令安装插件：\n",
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"\n",
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"```\n",
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"pip install jupyter_contrib_nbextensions\n",
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"jupyter contrib nbextension install --user\n",
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"jupyter nbextension enable execute_time/ExecuteTime\n",
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"```\n",
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"\n",
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"## 小结\n",
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"\n",
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"* 使用Jupyter Notebook工具，我们可以编辑、运行和为本书做贡献。\n",
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"* 使用端口转发在远程服务器上运行Jupyter Notebook。\n",
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"\n",
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"## 练习\n",
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"\n",
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"1. 在本地计算机上使用Jupyter Notebook编辑并运行本书中的代码。\n",
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"1. 使用Jupyter Notebook通过端口转发来远程编辑和运行本书中的代码。\n",
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"1. 对于两个方矩阵，测量$\\mathbf{A}^\\top \\mathbf{B}$与$\\mathbf{A} \\mathbf{B}$在$\\mathbb{R}^{1024 \\times 1024}$中的运行时间。哪一个更快？\n",
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"\n",
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"[Discussions](https://discuss.d2l.ai/t/5731)\n"
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]
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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},
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"required_libs": []
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},
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"nbformat": 4,
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"nbformat_minor": 5
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} |