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| <h1 class="post-title">Jetson Setup</h1> |
| <h3></h3><a style="float:left; margin-top:20px" href="/versions/master/get_started" class="btn btn-action">Get Started |
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| <!--- Licensed to the Apache Software Foundation (ASF) under one --> |
| <!--- or more contributor license agreements. See the NOTICE file --> |
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| |
| <h1 id="install-mxnet-on-a-jetson">Install MXNet on a Jetson</h1> |
| |
| <p>MXNet supports Ubuntu AArch64 based operating system so you can run MXNet on all <a href="https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/">NVIDIA Jetson modules</a>, such as Jetson Nano, TX1, TX2, Xavier NX and AGX Xavier.</p> |
| |
| <p>These instructions will walk through how to build MXNet and install MXNet’s Python language binding.</p> |
| |
| <p>For the purposes of this install guide we will assume that CUDA is already installed on your Jetson device. NVIDIA Jetpack comes with the latest OS image for Jetson mdoule, and developer tools for both host computer and developer kit, and this also includes CUDA. You should double check what versions are installed and which version you plan to use.</p> |
| |
| <p>After installing the prerequisites, you have several options for installing MXNet:</p> |
| <ol> |
| <li>Build MXNet from source |
| <ul> |
| <li>On a faster Linux computer using cross-compilation</li> |
| <li>On the Jetson itself (very slow and not recommended)</li> |
| </ul> |
| </li> |
| <li>Use a Jetson MXNet pip wheel for Python development and use a precompiled Jetson MXNet binary (not provided on this page as CUDA enabled wheels are not in accordance with ASF policy, users can download them from other 3rd party sources)</li> |
| </ol> |
| |
| <h2 id="prerequisites">Prerequisites</h2> |
| <p>To build from source or to use the Python wheel, you must install the following dependencies on your Jetson. |
| Cross-compiling will require dependencies installed on that machine as well.</p> |
| |
| <h3 id="python-dependencies">Python Dependencies</h3> |
| |
| <p>To use the Python API you need the following dependencies:</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">sudo </span>apt-get update |
| <span class="nb">sudo </span>apt-get <span class="nb">install</span> <span class="nt">-y</span> <span class="se">\</span> |
| build-essential <span class="se">\</span> |
| git <span class="se">\</span> |
| libopenblas-dev <span class="se">\</span> |
| libopencv-dev <span class="se">\</span> |
| python3-pip <span class="se">\</span> |
| python-numpy |
| |
| <span class="nb">sudo </span>pip3 <span class="nb">install</span> <span class="nt">--upgrade</span> <span class="se">\</span> |
| pip <span class="se">\</span> |
| setuptools <span class="se">\</span> |
| numpy |
| </code></pre></div></div> |
| |
| <p>If you plan to cross-compile you will need to install these dependencies on that computer as well.</p> |
| |
| <h3 id="download-the-source--setup-some-environment-variables">Download the source & setup some environment variables:</h3> |
| |
| <p>These steps are optional, but some of the following instructions expect MXNet source files and the <code class="highlighter-rouge">MXNET_HOME</code> environment variable. Also, CUDA commands will not work out of the box without updating your path.</p> |
| |
| <p>Clone the MXNet source code repository using the following <code class="highlighter-rouge">git</code> command in your home directory:</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>git clone <span class="nt">--recursive</span> https://github.com/apache/mxnet.git mxnet |
| </code></pre></div></div> |
| |
| <p>You can also checkout a particular branch of MXNet. For example, to install MXNet v1.6:</p> |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>git clone <span class="nt">--recursive</span> <span class="nt">-b</span> v1.6.x https://github.com/apache/mxnet.git mxnet |
| </code></pre></div></div> |
| |
| <p>Setup your environment variables for MXNet and CUDA in your <code class="highlighter-rouge">.profile</code> file in your home directory. |
| Add the following to the file.</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">export </span><span class="nv">PATH</span><span class="o">=</span>/usr/local/cuda/bin:<span class="nv">$PATH</span> |
| <span class="nb">export </span><span class="nv">MXNET_HOME</span><span class="o">=</span><span class="nv">$HOME</span>/mxnet/ |
| <span class="nb">export </span><span class="nv">PYTHONPATH</span><span class="o">=</span><span class="nv">$MXNET_HOME</span>/python:<span class="nv">$PYTHONPATH</span> |
| </code></pre></div></div> |
| |
| <p>You can then apply this change immediately with the following:</p> |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">source</span> .profile |
| </code></pre></div></div> |
| |
| <p><strong>Note:</strong> Change the <code class="highlighter-rouge">~/.profile</code> steps according to how you prefer to use your shell. Otherwise, your environment variables will be gone after you logout.</p> |
| |
| <h3 id="configure-cuda">Configure CUDA</h3> |
| |
| <p>You can check to see what version of CUDA is running with <code class="highlighter-rouge">nvcc</code>.</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>nvcc <span class="nt">--version</span> |
| </code></pre></div></div> |
| |
| <p>To switch CUDA versions on a device or computer that has more than one version installed, use the following and replace the symbolic link to the version you want. This one uses CUDA 10.2, which comes with Jetpack 4.4.</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">sudo rm</span> /usr/local/cuda |
| <span class="nb">sudo ln</span> <span class="nt">-s</span> /usr/local/cuda-10.2 /usr/local/cuda |
| </code></pre></div></div> |
| |
| <p><strong>Note:</strong> When cross-compiling, change the CUDA version on the host computer you’re using to match the version you’re running on your Jetson device.</p> |
| |
| <h2 id="build-mxnet-from-source">Build MXNet from Source</h2> |
| |
| <p>Installing MXNet from source is a two-step process:</p> |
| |
| <ol> |
| <li>Build the shared library from the MXNet C++ source code.</li> |
| <li>Install the supported language-specific packages for MXNet.</li> |
| </ol> |
| |
| <p>You can use a Docker method or you can build from source manually.</p> |
| |
| <h3 id="docker">Docker</h3> |
| |
| <p>You must have installed Docker and be able to run <code class="highlighter-rouge">docker</code> without <code class="highlighter-rouge">sudo</code>. |
| Follow these <a href="https://docs.docker.com/install/linux/#manage-docker-as-a-non-root-user">setup instructions to get to this point</a>. |
| Then run the following to execute cross-compilation via Docker.</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nv">$MXNET_HOME</span>/ci/build.py <span class="nt">-p</span> jetson |
| </code></pre></div></div> |
| |
| <h3 id="manually-on-the-jetson-module-slow">Manually on the Jetson module (Slow)</h3> |
| |
| <p><strong>Step 1</strong> Build the Shared Library</p> |
| |
| <p>Use the config_jetson.mk Makefile to install MXNet with CUDA bindings to leverage the GPU on the Jetson module.</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">cp</span> <span class="nv">$MXNET_HOME</span>/make/config_jetson.mk config.mk |
| </code></pre></div></div> |
| |
| <p>The pre-existing Makefile builds for all Jetson architectures. Edit <code class="highlighter-rouge">config.mk</code> if you want to specifically build for a particular architecture or if you want to build without CUDA bindings (CPU only). You can make the following changes:</p> |
| |
| <ol> |
| <li> |
| <p>Modify <code class="highlighter-rouge">CUDA_ARCH</code> to build for specific architectures. Currently, we have <code class="highlighter-rouge">CUDA_ARCH = -gencode arch=compute_53,code=sm_53 -gencode arch=compute_62,code=sm_62 -gencode arch=compute_72,code=sm_72</code>. Keep <code class="highlighter-rouge">-gencode arch=compute_53,code=sm_53</code> for Nano and TX1, <code class="highlighter-rouge">-gencode arch=compute_62,code=sm_62</code> for TX2, <code class="highlighter-rouge">-gencode arch=compute_72,code=sm_72</code> for Xavier NX and AGX Xavier.</p> |
| </li> |
| <li> |
| <p>For CPU only builds, remove <code class="highlighter-rouge">USE_CUDA_PATH</code>, <code class="highlighter-rouge">CUDA_ARCH</code>, <code class="highlighter-rouge">USE_CUDNN</code> flags.</p> |
| </li> |
| </ol> |
| |
| <p>Now you can build the complete MXNet library with the following command:</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">cd</span> <span class="nv">$MXNET_HOME</span> |
| make <span class="nt">-j</span> <span class="si">$(</span><span class="nb">nproc</span><span class="si">)</span> |
| </code></pre></div></div> |
| |
| <p>Executing this command creates a file called <code class="highlighter-rouge">libmxnet.so</code> in the <code class="highlighter-rouge">mxnet/lib</code> directory.</p> |
| |
| <p><strong>Step 2</strong> Install MXNet Python Bindings (optional)</p> |
| |
| <p>To install Python bindings run the following commands in the MXNet directory:</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">cd</span> <span class="nv">$MXNET_HOME</span>/python |
| <span class="nb">sudo </span>pip3 <span class="nb">install</span> <span class="nt">-e</span> <span class="nb">.</span> |
| </code></pre></div></div> |
| |
| <p>Note that the <code class="highlighter-rouge">-e</code> flag is optional. It is equivalent to <code class="highlighter-rouge">--editable</code> and means that if you edit the source files, these changes will be reflected in the package installed.</p> |
| |
| <p><strong>Step 3</strong> Install the MXNet Java & Scala Bindings (optional)</p> |
| |
| <p>Change directories to <code class="highlighter-rouge">scala-package</code> and run <code class="highlighter-rouge">mvn install</code>.</p> |
| |
| <div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nb">cd</span> <span class="nv">$MXNET_HOME</span>/scala-package |
| mvn <span class="nb">install</span> |
| </code></pre></div></div> |
| |
| <p>This creates the required <code class="highlighter-rouge">.jar</code> file to use in your Java or Scala projects.</p> |
| |
| <h2 id="conclusion-and-next-steps">Conclusion and Next Steps</h2> |
| |
| <p>You are now ready to run MXNet on your NVIDIA module. |
| You can verify your MXNet Python installation with the following:</p> |
| |
| <div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">mxnet</span> |
| <span class="n">mxnet</span><span class="o">.</span><span class="n">__version__</span> |
| </code></pre></div></div> |
| |
| <p>You can also verify MXNet can use your GPU with the following test:</p> |
| |
| <div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">mxnet</span> <span class="k">as</span> <span class="n">mx</span> |
| <span class="n">a</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="n">mx</span><span class="o">.</span><span class="n">gpu</span><span class="p">())</span> |
| <span class="n">b</span> <span class="o">=</span> <span class="n">a</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">1</span> |
| <span class="n">b</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> |
| </code></pre></div></div> |
| |
| <p>If everything is working, it will report the version number. |
| For assistance, head over to the <a href="https://discuss.mxnet.io/">MXNet Forum</a>.</p> |
| |
| </div> |
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