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            <h1 id="seo-header">【记录】win10 通过 docker 调用 nvidia</h1>
            
              <p id="updated-time" class="note note-info" style="">
                
                  
                    Last updated on March 19, 2024 pm
                  
                
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              <div class="markdown-body">
                
                <h2 id="新版WSL">新版WSL</h2>
<ol>
<li>访问商店获取 <a target="_blank" rel="noopener" href="https://www.microsoft.com/store/productId/9P9TQF7MRM4R">Windows Subsystem for Linux</a></li>
<li><code>wsl --version</code> 直接跳转到 <code>4. 安装 Docker</code></li>
<li><s>过时教程害人</s></li>
<li>如果已经执行了第2、3步，更新后需要再执行 <code>wsl -s docker-desktop</code> <a target="_blank" rel="noopener" href="https://askubuntu.com/questions/1423048/i-am-getting-error-on-windows-subsystem#:~:text=I%20think%20this%20link%20might%20help.%20One%20cause,to%20right%20one%20with%20wsl%20-s%20%3Cdistro_name%3E%20command.">切换回正确的 distro</a></li>
<li>关闭 Hyper-V，只开启 WSL 和 虚拟化平台 两个可选功能</li>
<li><code>netsh winsock reset</code> 然后重启</li>
</ol>
<h2 id="开启-Hyper-V-by-壹佰">开启 Hyper-V by <a target="_blank" rel="noopener" href="https://developer.aliyun.com/article/1144836">壹佰</a></h2>
<ol>
<li>将下面内容复制到文本文件中，然后将文件命名为Hyper-V.bat，然后以管理员身份运行，运行完成后重启电脑（可能需要BIOS中开启处理器虚拟化支持）。</li>
</ol>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line">pushd &quot;%~dp0&quot;</span><br><span class="line">dir /b %SystemRoot%\servicing\Packages\*Hyper-V*.mum &gt;hyper-v.txt</span><br><span class="line">for /f %%i in (&#x27;findstr /i . hyper-v.txt 2^&gt;nul&#x27;) do dism /online /norestart /add-package:&quot;%SystemRoot%\servicing\Packages\%%i&quot;</span><br><span class="line">del hyper-v.txt</span><br><span class="line">Dism /online /enable-feature /featurename:Microsoft-Hyper-V-All /LimitAccess /ALL</span><br></pre></td></tr></table></figure>
<ol start="2">
<li>使用 PowerShell 启用 Hyper-V，以管理员身份打开 PowerShell 控制台，运行以下命令：</li>
</ol>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">Enable-WindowsOptionalFeature -Online -FeatureName Microsoft-Hyper-V -All</span><br></pre></td></tr></table></figure>
<h2 id="安装-WSL2-by-Ali7-MS">安装 WSL2 by <a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/599286889">Ali7</a>&amp;<a target="_blank" rel="noopener" href="https://learn.microsoft.com/zh-cn/windows/wsl/install-manual#step-3---enable-virtual-machine-feature">MS</a></h2>
<ol>
<li>应用商店搜索 <a target="_blank" rel="noopener" href="https://www.microsoft.com/store/productId/9PN20MSR04DW">Ubuntu 22.04.2 LTS</a> 并安装（可以不装）</li>
<li>开启Windows Subsystem for Linux</li>
</ol>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">dism.exe /online /enable-feature /featurename:Microsoft-Windows-Subsystem-Linux /all /norestart</span><br></pre></td></tr></table></figure>
<ol start="3">
<li>开启虚拟机特性</li>
</ol>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">dism.exe /online /enable-feature /featurename:VirtualMachinePlatform /all /norestart</span><br></pre></td></tr></table></figure>
<ol start="4">
<li>下载并安装 <a target="_blank" rel="noopener" href="https://wslstorestorage.blob.core.windows.net/wslblob/wsl_update_x64.msi">WSL2更新包</a></li>
<li>将WSL2设置成默认</li>
</ol>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">wsl --set-default-version 2</span><br></pre></td></tr></table></figure>
<ol start="6">
<li>运行商店中安装的 Ubuntu 22.04.2 LTS （可以不装）</li>
</ol>
<h2 id="安装-Docker-Desktop-by-追逐时光者">安装 Docker Desktop  by <a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/441965046">追逐时光者</a></h2>
<ol>
<li>下载 <a target="_blank" rel="noopener" href="https://desktop.docker.com/win/stable/amd64/Docker%20Desktop%20Installer.exe">Docker Desktop Installer</a></li>
<li>换源，在系统右下角托盘图标内右键菜单选择 Settings，打开配置窗口后左侧导航菜单选择 Docker Desktop。编辑窗口内的JSON串：</li>
</ol>
<figure class="highlight json"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br></pre></td><td class="code"><pre><span class="line"><span class="punctuation">&#123;</span></span><br><span class="line">  <span class="attr">&quot;builder&quot;</span><span class="punctuation">:</span> <span class="punctuation">&#123;</span></span><br><span class="line">    <span class="attr">&quot;features&quot;</span><span class="punctuation">:</span> <span class="punctuation">&#123;</span></span><br><span class="line">      <span class="attr">&quot;buildkit&quot;</span><span class="punctuation">:</span> <span class="literal"><span class="keyword">true</span></span></span><br><span class="line">    <span class="punctuation">&#125;</span><span class="punctuation">,</span></span><br><span class="line">    <span class="attr">&quot;gc&quot;</span><span class="punctuation">:</span> <span class="punctuation">&#123;</span></span><br><span class="line">      <span class="attr">&quot;defaultKeepStorage&quot;</span><span class="punctuation">:</span> <span class="string">&quot;20GB&quot;</span><span class="punctuation">,</span></span><br><span class="line">      <span class="attr">&quot;enabled&quot;</span><span class="punctuation">:</span> <span class="literal"><span class="keyword">true</span></span></span><br><span class="line">    <span class="punctuation">&#125;</span></span><br><span class="line">  <span class="punctuation">&#125;</span><span class="punctuation">,</span></span><br><span class="line">  <span class="attr">&quot;experimental&quot;</span><span class="punctuation">:</span> <span class="literal"><span class="keyword">false</span></span><span class="punctuation">,</span></span><br><span class="line">  <span class="attr">&quot;registry-mirrors&quot;</span><span class="punctuation">:</span> <span class="punctuation">[</span></span><br><span class="line">    <span class="string">&quot;https://hub-mirror.c.163.com/&quot;</span><span class="punctuation">,</span></span><br><span class="line">    <span class="string">&quot;https://docker.mirrors.ustc.edu.cn/&quot;</span></span><br><span class="line">  <span class="punctuation">]</span></span><br><span class="line"><span class="punctuation">&#125;</span></span><br></pre></td></tr></table></figure>
<ol start="3">
<li>测试，Powershell 中运行 <code>docker run hello-world</code></li>
</ol>
<h2 id="调用-nvidia-by-无人知晓-bpq">调用 nvidia by <a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/543280130">无人知晓</a>&amp;<a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/610319395">bpq</a></h2>
<ol>
<li>Ubuntu 22.04.2 LTS 中 运行 <code>nvidia-smi</code><br>
<img src="https://img.limour.top/2023/08/30/64ef3604b91e0.webp" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt=""></li>
<li>右键卸载 Ubuntu 22.04.2 LTS，<code>wsl -l -v</code> 保证有 docker-desktop 和 docker-desktop-data 就行</li>
<li>Powershell 中运行 <code>docker pull anibali/pytorch:2.0.0-cuda11.8-ubuntu22.04</code></li>
<li>启动容器并测试 cuda</li>
</ol>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">docker run -p 0.0.0.0:8001:8001 --rm -it --name torch --gpus all anibali/pytorch:2.0.0-cuda11.8-ubuntu22.04 /bin/bash</span><br><span class="line">python</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> torch <span class="comment"># 如果pytorch安装成功即可导入</span></span><br><span class="line"><span class="built_in">print</span>(torch.cuda.is_available()) <span class="comment"># 查看CUDA是否可用</span></span><br><span class="line"><span class="built_in">print</span>(torch.cuda.device_count()) <span class="comment"># 查看可用的CUDA数量</span></span><br><span class="line"><span class="built_in">print</span>(torch.version.cuda) <span class="comment"># 查看CUDA的版本号</span></span><br></pre></td></tr></table></figure>
<ol>
<li>测试网络访问，注意 <strong><code>-p 0.0.0.0</code></strong></li>
</ol>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">docker run -p 0.0.0.0:8001:8001 --rm -it --name torch --gpus all anibali/pytorch:2.0.0-cuda11.8-ubuntu22.04 python -m http.server 8001</span><br></pre></td></tr></table></figure>
<h2 id="conda-by-bpq-LATLAJ">conda by <a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/610319395">bpq</a>&amp;<a target="_blank" rel="noopener" href="https://www.jianshu.com/p/e1bd6e13d8e4">LATLAJ</a></h2>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><span class="line">mkdir data # G:\data</span><br><span class="line">docker run -p 0.0.0.0:8001:8001 -it --name torch --gpus all -v //g/data:/app/data anibali/pytorch:2.0.0-cuda11.8-ubuntu22.04 /bin/bash</span><br><span class="line">conda init # 然后退出 bash</span><br><span class="line">docker start torch</span><br><span class="line">docker exec -it torch /bin/bash</span><br><span class="line">conda install nano -c conda-forge</span><br><span class="line">nano ~/.condarc</span><br></pre></td></tr></table></figure>
<ul>
<li><a href="/-ji-lu--an-zhuang-conda-bing-geng-huan-qing-hua-yuan">更换清华源</a></li>
</ul>
<h2 id="jupyter">jupyter</h2>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><span class="line">conda create -n jupyter jupyter notebook -c conda-forge</span><br><span class="line">conda activate jupyter</span><br><span class="line">jupyter notebook --ip 0.0.0.0 --port 8001</span><br><span class="line">jupyter notebook --generate-config</span><br><span class="line">nano ~/.jupyter/jupyter_notebook_config.py</span><br><span class="line">jupyter notebook # http://localhost:8001/lab?token=limour</span><br></pre></td></tr></table></figure>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line">c.ServerApp.ip = <span class="string">&#x27;*&#x27;</span></span><br><span class="line">c.ServerApp.port = <span class="number">8001</span></span><br><span class="line">c.ExtensionApp.open_browser = <span class="literal">False</span></span><br><span class="line">c.ServerApp.token = <span class="string">&#x27;limour&#x27;</span></span><br></pre></td></tr></table></figure>
<h2 id="添加内核">添加内核</h2>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">conda activate base</span><br><span class="line">conda install ipykernel -c conda-forge</span><br><span class="line">python -m ipykernel install --user --name pytorch</span><br></pre></td></tr></table></figure>
<p><img src="https://img.limour.top/2023/08/30/64ef3633df990.webp" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt=""><br>
快速启动：<code>docker exec -it torch /home/user/micromamba/envs/jupyter/bin/jupyter notebook</code></p>

                
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