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    <li>Build PaddlePaddle for Raspberry Pi</li>
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  <div class="section" id="build-paddlepaddle-for-raspberry-pi">
<span id="build-paddlepaddle-for-raspberry-pi"></span><h1>Build PaddlePaddle for Raspberry Pi<a class="headerlink" href="#build-paddlepaddle-for-raspberry-pi" title="Permalink to this headline">¶</a></h1>
<p>You may use any of the following two approaches to build the inference library of PaddlePaddle for Raspberry Pi:</p>
<ol class="simple">
<li>Build using SSH: Log in to a Raspberry Pi using SSH and build the library. The required development tools and third-party dependencies are listed in here: <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/Dockerfile"><code class="docutils literal"><span class="pre">/Dockerfile</span></code></a>.</li>
<li>Cross-compile: We talk about how to cross-compile PaddlePaddle for Raspberry Pi on a Linux/x64 machine, in more detail in this article.</li>
</ol>
<div class="section" id="the-cross-compiling-toolchain">
<span id="the-cross-compiling-toolchain"></span><h2>The Cross-Compiling Toolchain<a class="headerlink" href="#the-cross-compiling-toolchain" title="Permalink to this headline">¶</a></h2>
<p>Step 1. Clone the Github repo by running the following command.</p>
<div class="highlight-bash"><div class="highlight"><pre><span></span>git clone https://github.com/raspberrypi/tools.git
</pre></div>
</div>
<p>Step 2. Use the pre-built cross-compiler found in <code class="docutils literal"><span class="pre">./tools/tree/master/arm-bcm2708/gcc-linaro-arm-linux-gnueabihf-raspbian-x64</span></code>.  To run it on a Linux computer, glibc version &gt;= 2.14 is needed.</p>
</div>
<div class="section" id="cmake-arguments">
<span id="cmake-arguments"></span><h2>CMake Arguments<a class="headerlink" href="#cmake-arguments" title="Permalink to this headline">¶</a></h2>
<p>CMake supports <a class="reference external" href="https://cmake.org/cmake/help/v3.0/manual/cmake-toolchains.7.html#cross-compiling">cross-compiling</a>.  All CMake configuration arguments required for the cross-compilation for Raspberry Pi can be found in <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/cmake/cross_compiling/raspberry_pi.cmake"><code class="docutils literal"><span class="pre">cmake/cross_compiling/raspberry_pi.cmake</span></code></a>.</p>
<p>Some important arguments that need to be set:</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">CMAKE_SYSTEM_NAME</span></code>: The target platform.  Must be <code class="docutils literal"><span class="pre">RPi</span></code>.</li>
<li><code class="docutils literal"><span class="pre">RPI_TOOLCHAIN</span></code>: The absolute path of the cross-compiling toolchain.</li>
<li><code class="docutils literal"><span class="pre">RPI_ARM_NEON</span></code>: Use ARM NEON Intrinsics. This is a required argument and set default to <code class="docutils literal"><span class="pre">ON</span></code>.</li>
<li><code class="docutils literal"><span class="pre">HOST_C/CXX_COMPILER</span></code>: The C/C++ compiler for the host.  It is used to build building tools running on the host, for example, protoc.</li>
</ul>
<p>A commonly-used CMake configuration is as follows:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">cmake</span> <span class="o">-</span><span class="n">DCMAKE_SYSTEM_NAME</span><span class="o">=</span><span class="n">RPi</span> \
      <span class="o">-</span><span class="n">DRPI_TOOLCHAIN</span><span class="o">=</span><span class="n">your</span><span class="o">/</span><span class="n">path</span><span class="o">/</span><span class="n">to</span><span class="o">/</span><span class="n">arm</span><span class="o">-</span><span class="n">bcm2708</span><span class="o">/</span><span class="n">gcc</span><span class="o">-</span><span class="n">linaro</span><span class="o">-</span><span class="n">arm</span><span class="o">-</span><span class="n">linux</span><span class="o">-</span><span class="n">gnueabihf</span><span class="o">-</span><span class="n">raspbian</span><span class="o">-</span><span class="n">x64</span> \
      <span class="o">-</span><span class="n">DRPI_ARM_NEON</span><span class="o">=</span><span class="n">ON</span> \
      <span class="o">-</span><span class="n">DCMAKE_INSTALL_PREFIX</span><span class="o">=</span><span class="n">your</span><span class="o">/</span><span class="n">path</span><span class="o">/</span><span class="n">to</span><span class="o">/</span><span class="n">install</span> \
      <span class="o">-</span><span class="n">DWITH_GPU</span><span class="o">=</span><span class="n">OFF</span> \
      <span class="o">-</span><span class="n">DWITH_C_API</span><span class="o">=</span><span class="n">ON</span> \
      <span class="o">-</span><span class="n">DWITH_PYTHON</span><span class="o">=</span><span class="n">OFF</span> \
      <span class="o">-</span><span class="n">DWITH_SWIG_PY</span><span class="o">=</span><span class="n">OFF</span> \
      <span class="o">..</span>
</pre></div>
</div>
<p>To build the inference library, please set the argument WITH_C_API to ON: <code class="docutils literal"><span class="pre">WITH_C_API=ON</span></code>.</p>
<p>You can add more arguments. For example, to minimize the size of the generated inference library, you may use <code class="docutils literal"><span class="pre">CMAKE_BUILD_TYPE=MinSizeRel</span></code>. For performance optimization, you may use <code class="docutils literal"><span class="pre">CMAKE_BUILD_TYPE=Release</span></code>.</p>
</div>
<div class="section" id="build-and-install">
<span id="build-and-install"></span><h2>Build and Install<a class="headerlink" href="#build-and-install" title="Permalink to this headline">¶</a></h2>
<p>The following commands build the inference library of PaddlePaddle for Raspberry Pi and third-party dependencies.</p>
<div class="highlight-bash"><div class="highlight"><pre><span></span>make
make install
</pre></div>
</div>
<p>The intermediate files will be stored in <code class="docutils literal"><span class="pre">build</span></code>. Third-party libraries will be located in <code class="docutils literal"><span class="pre">build/third_party</span></code>. If you have already built it for other platforms like Android or iOS, you may want to clear these directories by running the command: <code class="docutils literal"><span class="pre">rm</span> <span class="pre">-rf</span> <span class="pre">build</span></code>.</p>
<p>The infernece library will be in <code class="docutils literal"><span class="pre">your/path/to/install/lib</span></code>, with related header files in <code class="docutils literal"><span class="pre">your/path/to/install/include</span></code>.</p>
</div>
</div>


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