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<h2><a class="anchor" aria-hidden="true" id="使用pip"></a><a href="#使用pip" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>使用pip</h2>
<p>推荐使用<a href="https://conda.io/miniconda.html">Miniconda3</a>来配合SINGA使用，安装miniconda后，执行以下命令之一安装SINGA。</p>
<ol>
<li>只使用CPU
<a href="https://colab.research.google.com/drive/17RA056Brwk0vBQTFaZ-l9EbqwADO0NA9?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a></li>
</ol>
<pre><code class="hljs css language-bash">pip install singa -f http://singa.apache.org/docs/next/wheel-cpu.html --trusted-host singa.apache.org
</code></pre>
<p>您可以通过<code>singa==&lt;version&gt;</code>安装特定版本的SINGA，其中<code>&lt;version&gt;</code>字段应被替换，例如<code>4.0.0</code>。可用的SINGA版本在链接中列出。</p>
<p>要安装最新的开发版本，请将链接替换为
<a href="http://singa.apache.org/docs/next/wheel-cpu-dev.html">http://singa.apache.org/docs/next/wheel-cpu-dev.html</a></p>
<ol start="2">
<li>使用CUDA和cuDNN的GPU
<a href="https://colab.research.google.com/drive/1W30IPCqj5fG8ADAQsFqclaCLyIclVcJL?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a></li>
</ol>
<pre><code class="hljs css language-bash">pip install singa -f http://singa.apache.org/docs/next/wheel-gpu.html --trusted-host singa.apache.org
</code></pre>
<p>您也可以配置SINGA版本和CUDA版本，比如<code>singa==4.0.0+cuda10.2</code>，SINGA版本和CUDA版本的可用组合在链接中列出。</p>
<p>要安装最新的开发版本，请将链接替换为
<a href="http://singa.apache.org/docs/next/wheel-gpu-dev.html">http://singa.apache.org/docs/next/wheel-gpu-dev.html</a></p>
<p>注意：你本地Python环境的Python版本将被用来寻找相应的wheel包。例如，如果你本地的Python是3.6，那么就会通过pip选择在Python 3.6上编译的wheel包并安装。事实上，wheel文件的名称包括SINGA版本、CUDA版本和Python版本。因此，<code>pip</code>知道要下载和安装哪个wheel文件。</p>
<p>参考setup.py文件顶部的注释，了解如何构建wheel包。</p>
<p>如果运行以下命令没有报错：</p>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> python -c <span class="hljs-string">"from singa import tensor"</span></span>
</code></pre>
<p>那么SINGA就安装成功了。</p>
<h2><a class="anchor" aria-hidden="true" id="使用docker"></a><a href="#使用docker" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>使用Docker</h2>
<p>按照<a href="https://docs.docker.com/install/">说明</a>在你的本地主机上安装Docker。将您的用户添加到<a href="https://docs.docker.com/install/linux/linux-postinstall/">docker组</a>中，以便在没有<code>sudo</code>的情况下运行docker命令。</p>
<ol>
<li>仅使用CPU</li>
</ol>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> docker run -it apache/singa:X.Y.Z-cpu-ubuntu16.04 /bin/bash</span>
</code></pre>
<ol start="2">
<li>要使用GPU，在安装Docker后安装
<a href="https://github.com/NVIDIA/nvidia-docker">Nvidia-Docker</a></li>
</ol>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> nvidia-docker run -it apache/singa:X.Y.Z-cuda9.0-cudnn7.4.2-ubuntu16.04 /bin/bash</span>
</code></pre>
<ol start="3">
<li>关于SINGA Docker镜像（标签）的完整列表，请访问<a href="https://hub.docker.com/r/apache/singa/">docker hub site</a>。对于每个docker镜像，标签的命名为：</li>
</ol>
<pre><code class="hljs css language-shell">version-(cpu|gpu)[-devel]
</code></pre>
<table>
<thead>
<tr><th>Tag</th><th>Description</th><th>Example value</th></tr>
</thead>
<tbody>
<tr><td><code>version</code></td><td>SINGA version</td><td>'2.0.0-rc0', '2.0.0', '1.2.0'</td></tr>
<tr><td><code>cpu</code></td><td>the image cannot run on GPUs</td><td>'cpu'</td></tr>
<tr><td><code>gpu</code></td><td>the image can run on Nvidia GPUs</td><td>'gpu', or 'cudax.x-cudnnx.x' e.g., 'cuda10.0-cudnn7.3'</td></tr>
<tr><td><code>devel</code></td><td>indicator for development</td><td>if absent, SINGA Python package is installed for runtime only; if present, the building environment is also created, you can recompile SINGA from source at '/root/singa'</td></tr>
<tr><td><code>OS</code></td><td>indicate OS version number</td><td>'ubuntu16.04', 'ubuntu18.04'</td></tr>
</tbody>
</table>
<h2><a class="anchor" aria-hidden="true" id="从源码编译"></a><a href="#从源码编译" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>从源码编译</h2>
<p>您可以使用本地构建工具或conda-build在本地主机操作系统上或在Docker容器中从源代码<a href="/docs/4.0.0_Chinese/build">构建和安装SINGA</a>。</p>
<h2><a class="anchor" aria-hidden="true" id="faq"></a><a href="#faq" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>FAQ</h2>
<ul>
<li><p>Q: <code>from singa import tensor</code>错误</p>
<p>A: 执行下面的命令，检查详细的错误：</p>
<pre><code class="hljs css language-shell">python -c "from singa import _singa_wrap"
<span class="hljs-meta">#</span><span class="bash"> go to the folder of _singa_wrap.so</span>
ldd path to _singa_wrap.so
python
<span class="hljs-meta">&gt;</span><span class="bash">&gt; import importlib</span>
<span class="hljs-meta">&gt;</span><span class="bash">&gt; importlib.import_module(<span class="hljs-string">'_singa_wrap'</span>)</span>
</code></pre>
<p><code>_singa_wrap.so</code> 的文件夹是 <code>~/miniconda3/lib/python3.7/site-packages/singa</code>。通常情况下，这个错误是由于依赖的库不匹配或缺失造成的，例如 cuDNN 或 protobuf。解决方法是创建一个新的虚拟环境，并在该环境中安装SINGA，例如：</p></li>
</ul>
<pre><code class="hljs css language-shell">conda create -n singa
conda activate singa
conda install -c nusdbsystem -c conda-forge singa-cpu
</code></pre>
<ul>
<li><p>Q: 使用虚拟环境时，每次安装SINGA时，都会重新安装numpy。但是，当我运行<code>import numpy</code>时，numpy没有被使用。</p>
<p>A:
这可能是由<code>PYTHONPATH</code>环境变量引起的，在使用虚拟环境时，应将其设置为空，以避免与虚拟环境的路径冲突。</p></li>
<li><p>Q: 当我在Mac OS X中运行SINGA时，得到如下错误 &quot;Fatal Python error:
PyThreadState_Get: no current thread Abort trap: 6&quot;</p>
<p>A: 这个错误通常发生在系统中有多个 Python 版本的时候，例如，操作系统自带的版本和 Homebrew 安装的版本。SINGA链接的Python必须与Python解释器相同。您可以通过<code>which python</code>来检查解释器python版本并通过<code>otool -L &lt;path to _singa_wrap.so&gt;</code> 检查 SINGA 链接的 Python，如果通过conda安装SINGA，这个问题应该可以解决。</p></li>
</ul>
</span></div></article></div><div class="docs-prevnext"><a class="docs-next button" href="/docs/4.0.0_Chinese/software-stack"><span>Software Stack</span><span class="arrow-next"> →</span></a></div></div></div><nav class="onPageNav"><ul class="toc-headings"><li><a href="#使用pip">使用pip</a></li><li><a href="#使用docker">使用Docker</a></li><li><a href="#从源码编译">从源码编译</a></li><li><a href="#faq">FAQ</a></li></ul></nav></div><footer class="nav-footer" id="footer"><section class="sitemap"><a href="/" class="nav-home"><img src="/img/singa-logo-square.png" alt="Apache SINGA" width="66" height="58"/></a><div><h5>Docs</h5><a href="/docs/installation">Getting Started</a><a href="/docs/device">Guides</a><a href="/en/https://apache-singa.readthedocs.io/en/latest/">API Reference</a><a href="/docs/examples">Examples</a><a href="/docs/download-singa">Development</a></div><div><h5>Community</h5><a href="/en/users.html">User Showcase</a><a href="/docs/history-singa">SINGA History</a><a href="/docs/team-list">SINGA Team</a><a href="/blog">SINGA News</a><a href="https://github.com/apache/singa">GitHub</a><div class="social"><a class="github-button" href="https://github.com/apache/singa" data-count-href="/apache/singa/stargazers" data-show-count="true" data-count-aria-label="# stargazers on GitHub" aria-label="Star this project on GitHub">apache/singa-doc</a></div><div class="social"><a href="https://twitter.com/ApacheSINGA" class="twitter-follow-button">Follow @ApacheSINGA</a></div></div><div><h5>Apache Software Foundation</h5><a href="https://apache.org/" target="_blank" rel="noreferrer noopener">Foundation</a><a href="http://www.apache.org/licenses/" target="_blank" rel="noreferrer noopener">License</a><a href="http://www.apache.org/foundation/sponsorship.html" target="_blank" rel="noreferrer noopener">Sponsorship</a><a href="http://www.apache.org/foundation/thanks.html" target="_blank" rel="noreferrer noopener">Thanks</a><a href="http://www.apache.org/events/current-event" target="_blank" rel="noreferrer noopener">Events</a><a href="http://www.apache.org/security/" target="_blank" rel="noreferrer noopener">Security</a></div></section><div style="width:100%;text-align:center"><a href="https://apache.org/" target="_blank" rel="noreferrer noopener" class="ApacheOpenSource"><img src="/img/asf_logo_wide.svg" alt="Apache Open Source"/></a><section class="copyright" style="max-width:60%;margin:0 auto">Copyright © 2023
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Apache SINGA, Apache, the Apache feather logo, and
the Apache SINGA project logos are trademarks of The
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