PyTorch深度学习入门笔记（一）PyTorch环境配置及安装

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<p>@</p><p></p>
<p><strong>OS：</strong> ubuntu 20.04（虚拟机）</p>
<h1 id="一工具安装">一、工具安装</h1>
<h2 id="11-anaconda-安装">1.1 Anaconda 安装</h2>
! }/ }8 R( G* I. r6 s2 r: Q<p>首先安装Anaconda ,我是去<a  href="https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/">清华大学镜像站</a>下载，版本为<br>
# ~3 m, l5 h- E, z<code>Anaconda3-5.2.0-Linux-x86_64.sh</code><br>
参考<a  href="https://blog.csdn.net/m0_50117360/article/details/108403586?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522164187185416780357286476%2522%252C%2522scm%2522%253A%252220140713.130102334..%2522%257D&request_id=164187185416780357286476&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~top_positive~default-1-108403586.pc_search_insert_ulrmf&utm_term=ubuntu20.04%E5%AE%89%E8%A3%85anaconda&spm=1018.2226.3001.4187">这篇CSDN博客</a>安装好。<br>
安装成功测试：<br>
1 z) B& c3 W& h% e/ I<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102427806-11701860.png" ><br>
7 @7 i# f8 L9 f2 g首先创建一个虚拟环境：</p>
! I+ U5 g7 E! W( u0 L8 a<pre><code class="language-c">conda create -n pytorch python=3.6
8 ^8 X' [+ T- }8 ?' Q. }" {& ^</code></pre>
  Y4 @, T9 x* T4 B4 O7 N<p><img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102428555-1044758357.png" ><br>
输入</p>
<pre><code class="language-c">source activate pytorch
</code></pre>
<p>激活环境</p>
<h2 id="12-pytorch安装">1.2 Pytorch安装</h2>
<p>进入<a  href="https://pytorch.org/get-started/locally/">官网</a>,选择合适版本安装，因为我是用的ubuntu20.04虚拟机，不支持CUDA，所以选择了CPU：<br>
7 I7 h$ H6 q% ?- ?<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102429086-588112728.png" ></p>
<p>选择合适版本并复制Run this Command:即可进行安装(不推荐使用方法，因为下载速度很慢)。<br>
安装过程可能比较缓慢，可以用以下命令（推荐）‘</p>
<pre><code class="language-c">pip3 --default-timeout=1000 install --index-url https://mirrors.aliyun.com/pypi/simple torch==1.10.1+cpu torchvision==0.11.2+cpu torchaudio==0.10.1+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
& \. F3 s, o: E& |2 t0 @: @3 m</code></pre>
2 w, W3 {" e. j0 a5 ?, h: H3 {0 d<p>注意：先进入所创建的 Pytorch虚拟环境，再输入指令进行安装。<br>
<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102429678-1764231985.png" ><br>
安装好后进行测试：<br>
) g; a2 I2 q# k% W( f& s% x<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102430213-1770020069.png" ></p>
. D" i7 L6 Z5 C# ^7 L1 k<h1 id="二编辑器安装">二、编辑器安装</h1>
<h2 id="21-pycharm安装">2.1 Pycharm安装</h2>
1 Y$ }! G! s4 \5 A. V<p>官方下载地址是：<a  href="https://www.jetbrains.com/pycharm/download/#section=linux">https://www.jetbrains.com/pycharm/download/#section=linux</a><br>
9 n9 G, u! |5 p' E/ X选择免费的社区版安装：<br>
6 Z# P1 @. q+ }  y, a<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102431391-2074783399.png" ><br>
下载下来就是解压，放到一个合适的文件夹下，然后添加环境变量</p>
<pre><code class="language-bash">gedit .bashrc
</code></pre>
<p>在最下面一行输入：</p>
<pre><code class="language-c"># pycharm
alias pycharm="sh /home/jc-cao/app_download_address/Pycharm2021/pycharm-community-2021.3.1/bin/pycharm.sh"
</code></pre>
<p>注：将上面的路径改为自己的pycharm安装路径即可<br>
5 Y1 _8 [, m1 e/ G; q然后使配置生效</p>
: ]6 v( h3 e! _* z, q<pre><code class="language-c">source .bashrc
</code></pre>
  m6 U- _) M/ ^<p>这样在终端输入 <code>pycharm</code> 就能打开软件了<br>
<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102432003-1803611031.png" ><br>
接下来创建一个名为 learn_pytorch的工程：<br>
<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102433439-420704314.png" ><br>
选择解释器为之前所创建的名为pytorch的虚拟环境的python解释器</p>
$ ?" ^! ?# a0 D- U& R<h2 id="22-jupyter安装">2.2 Jupyter安装</h2>
" r. R9 A4 v$ K/ D<p>在pytorch 虚拟环境中，输入</p>
, N' F2 ]6 {7 H9 u* f+ E2 v+ m<pre><code class="language-c">conda install nb_conda
</code></pre>
  c- C2 B" i  v- Y: l, z/ K7 }<p>安装jupyter：<br>
<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102433994-347380977.png" ><br>
3 p- m4 `6 Q+ ?) a% }7 Q: o安装好后输入 <code>jupyter notebook</code> 测试<br>
<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102434545-226958772.png" ><br>
在jupyter中新建一个notebook，采用pytorch虚拟环境的python解释器，即可导入torch包进行使用了。<br>
<img src="https://img2022.cnblogs.com/other/1772025/202202/1772025-20220212102434869-1058987249.png" ></p>
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