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 <div class="section" id="build-mxnet-from-source">
 <span id="build-mxnet-from-source"></span><h1>Build MXNet from Source<a class="headerlink" href="#build-mxnet-from-source" title="Permalink to this headline">¶</a></h1>
 <p><strong>NOTE:</strong> For MXNet with Python installation, please refer to the <a class="reference external" href="http://mxnet.io/get_started/install.html">new install guide</a>.</p>
 <p>This document explains how to build MXNet from sources. Building MXNet from sources is a 2 step process.</p>
 <ol class="simple">
 <li>Build the MXNet shared library, <code class="docutils literal"><span class="pre">libmxnet.so</span></code>, from <a class="reference external" href="#build-the-shared-library">C++ source files</a></li>
 <li>Install the language binding for MXNet. MXNet supports -
 <a class="reference external" href="#build-the-c-package">C++</a>,
 <a class="reference external" href="#build-the-scala-package">Scala</a>, <a class="reference external" href="#build-the-r-package">R</a>, and
 <a class="reference external" href="#build-the-julia-package">Julia</a>.</li>
 </ol>
 <div class="section" id="build-the-shared-library">
 <span id="build-the-shared-library"></span><h2>Build the shared library<a class="headerlink" href="#build-the-shared-library" title="Permalink to this headline">¶</a></h2>
 <div class="section" id="prerequisites">
 <span id="prerequisites"></span><h3>Prerequisites<a class="headerlink" href="#prerequisites" title="Permalink to this headline">¶</a></h3>
 <p>You need C++ build tools and BLAS library to build MXNet shared library. If you want to run MXNet on GPUs, you need to install CUDA and CuDNN.</p>
 <div class="section" id="c-build-tools">
 <span id="c-build-tools"></span><h4>C++ build tools<a class="headerlink" href="#c-build-tools" title="Permalink to this headline">¶</a></h4>
 <ol class="simple">
 <li>A C++ compiler that supports C++ 11.
 <a class="reference external" href="https://gcc.gnu.org/gcc-4.8/">G++ (4.8 or later)</a> or
 <a class="reference external" href="http://clang.llvm.org/">Clang</a> is required.</li>
 <li><a class="reference external" href="https://git-scm.com/downloads">Git</a> for downloading the sources from Github repository.</li>
 <li><a class="reference external" href="https://www.gnu.org/software/make/">GNU Make</a> (<a class="reference external" href="https://cmake.org/">cmake</a>
 for Windows) to build the library.</li>
 </ol>
 <p>Select your preferences and follow the instructions to install MXNet from sources.</p>
 <div class="btn-group opt-group" role="group">
 <button class="btn btn-default opt active" type="button">Linux</button>
 <button class="btn btn-default opt" type="button">macOS</button>
 <button class="btn btn-default opt" type="button">Windows</button>
 </div>
 <script src="../../_static/js/options.js" type="text/javascript"></script><div class="linux"><p>Then select the Linux distribution:</p>
 <div class="btn-group opt-group" role="group">
 <button class="btn btn-default opt active" type="button">Ubuntu</button>
 <button class="btn btn-default opt" type="button">CentOS</button>
 <button class="btn btn-default opt" type="button">Others</button>
 </div><ul class="simple">
 <li><strong>Ubuntu</strong> for systems supporting the <code class="docutils literal"><span class="pre">apt-get</span></code>
 package management program</li>
 <li><strong>CentOS</strong> for systems supporting the <code class="docutils literal"><span class="pre">yum</span></code> package
 management program</li>
 <li><strong>Others</strong> for general Linux-like systems building dependencies from scratch.</li>
 </ul>
 <div class="ubuntu"><p>Install build tools and git on <code class="docutils literal"><span class="pre">Ubuntu</span> <span class="pre">>=</span> <span class="pre">13.10</span></code> and <code class="docutils literal"><span class="pre">Debian</span> <span class="pre">>=</span> <span class="pre">8</span></code>.</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>sudo apt-get update <span class="o">&amp;&amp;</span> sudo apt-get install build-essential git
 </pre></div>
 </div>
 </div><div class="centos"><p>Install build tools and git on <code class="docutils literal"><span class="pre">CentOS</span> <span class="pre">>=</span> <span class="pre">7</span></code> and <code class="docutils literal"><span class="pre">Fedora</span> <span class="pre">>=</span> <span class="pre">19</span></code>.</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>sudo yum groupinstall -y <span class="s2">"Development Tools"</span> <span class="o">&amp;&amp;</span> sudo yum install -y git
 </pre></div>
 </div>
 </div><div class="others"><p>Installing both <code class="docutils literal"><span class="pre">git</span></code> and <code class="docutils literal"><span class="pre">make</span></code> by following instructions on the websites is
 straightforward. Here we provide the instructions to build <code class="docutils literal"><span class="pre">gcc-4.8</span></code> from source codes.</p>
 <ol>
 <li><p class="first">Install the 32-bit <code class="docutils literal"><span class="pre">libc</span></code> with one of the following system-specific commands:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>sudo apt-get install libc6-dev-i386 <span class="c1"># In Ubuntu</span>
 sudo yum install glibc-devel.i686   <span class="c1"># In RHEL (Red Hat Linux)</span>
 sudo yum install glibc-devel.i386   <span class="c1"># In CentOS 5.8</span>
 sudo yum install glibc-devel.i686   <span class="c1"># In CentOS 6/7</span>
 </pre></div>
 </div>
 </li>
 <li><p class="first">Download and extract the <code class="docutils literal"><span class="pre">gcc</span></code> source code with the prerequisites:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>wget http://mirrors.concertpass.com/gcc/releases/gcc-4.8.5/gcc-4.8.5.tar.gz
 tar -zxf gcc-4.8.5.tar.gz
 <span class="nb">cd</span> gcc-4.8.5
 ./contrib/download_prerequisites
 </pre></div>
 </div>
 </li>
 <li><p class="first">Build <code class="docutils literal"><span class="pre">gcc</span></code> by using 10 threads and then install to <code class="docutils literal"><span class="pre">/usr/local</span></code></p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>mkdir release <span class="o">&amp;&amp;</span> <span class="nb">cd</span> release
 ../configure --prefix<span class="o">=</span>/usr/local --enable-languages<span class="o">=</span>c,c++
 make -j10
 sudo make install
 </pre></div>
 </div>
 </li>
 <li><p class="first">Add the lib path to your configure file such as <code class="docutils literal"><span class="pre">~/.bashrc</span></code>:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">export</span> <span class="nv">LD_LIBRARY_PATH</span><span class="o">=</span><span class="si">${</span><span class="nv">LD_LIBRARY_PATH</span><span class="si">}</span>:/usr/local/lib64
 </pre></div>
 </div>
 </li>
 </ol>
 </div>
 </div> <!-- linux --><div class="windows"><ol class="simple">
 <li>If <a class="reference external" href="https://www.visualstudio.com/downloads/">Microsoft Visual Studio 2015</a> is not already installed, download and install it. You can download and install the free community edition.</li>
 <li>Download and Install <a class="reference external" href="https://cmake.org/">CMake</a> if it is not already installed.</li>
 </ol>
 </div><div class="macos"><p>Install <a class="reference external" href="https://developer.apple.com/xcode/">Xcode</a>.</p>
 </div></div>
 <div class="section" id="blas-library">
 <span id="blas-library"></span><h4>BLAS library<a class="headerlink" href="#blas-library" title="Permalink to this headline">¶</a></h4>
 <p>MXNet relies on the
 <a class="reference external" href="https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms">BLAS</a> (Basic
 Linear Algebra Subprograms) library for numerical computations. You can install
 any one among <a class="reference external" href="http://math-atlas.sourceforge.net/">ATLAS</a>,
 <a class="reference external" href="http://www.openblas.net/">OpenBLAS</a> and
 <a class="reference external" href="https://software.intel.com/en-us/intel-mkl">MKL</a>.</p>
 <div class="linux">
 <div class="ubuntu"><div class="highlight-bash"><div class="highlight"><pre><span></span>sudo apt-get install libatlas-base-dev
 </pre></div>
 </div>
 </div><div class="centos"><div class="highlight-bash"><div class="highlight"><pre><span></span>sudo yum install atlas-devel
 </pre></div>
 </div>
 </div><div class="linux"><p>You can follow this link to build
 <a class="reference external" href="https://github.com/xianyi/OpenBLAS#installation-from-source">OpenBlas from source</a>.</p>
 </div>
 </div><div class="macos"><p>macOS users can skip this step as <code class="docutils literal"><span class="pre">xcode</span></code> ships with a BLAS library.</p>
 </div><div class="windows"><ol class="simple">
 <li>Download pre-built binaries for <a class="reference external" href="https://sourceforge.net/projects/openblas/files/">OpenBLAS</a></li>
 <li>Set the environment variable <code class="docutils literal"><span class="pre">OpenBLAS_HOME</span></code> to point to the OpenBLAS
 directory that contains the <code class="docutils literal"><span class="pre">include/</span></code> and <code class="docutils literal"><span class="pre">lib/</span></code> directories. Typically, you
 can find the directory in <code class="docutils literal"><span class="pre">C:\Program</span> <span class="pre">files</span> <span class="pre">(x86)\OpenBLAS\</span></code>.</li>
 </ol>
 </div></div>
 <div class="section" id="optional-opencv-for-image-loading-and-augmentation">
 <span id="optional-opencv-for-image-loading-and-augmentation"></span><h4>Optional: <a class="reference external" href="http://opencv.org/">OpenCV</a> for Image Loading and Augmentation<a class="headerlink" href="#optional-opencv-for-image-loading-and-augmentation" title="Permalink to this headline">¶</a></h4>
 <div class="linux">
 <div class="ubuntu"><div class="highlight-bash"><div class="highlight"><pre><span></span>sudo apt-get install libopencv-dev
 </pre></div>
 </div>
 </div><div class="centos"><div class="highlight-bash"><div class="highlight"><pre><span></span>sudo apt-get install opencv-devel
 </pre></div>
 </div>
 </div><div class="others"><p>To build OpenCV from source code, you need the <a class="reference external" href="https://cmake.org">cmake</a> library.</p>
 <ol>
 <li><p class="first">If you don’t have cmake or if your version of cmake is earlier than 3.6.1, run the following commands to install a newer version of cmake:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>wget https://cmake.org/files/v3.6/cmake-3.6.1-Linux-x86_64.tar.gz
 tar -zxvf cmake-3.6.1-Linux-x86_64.tar.gz
 <span class="nb">alias</span> <span class="nv">cmake</span><span class="o">=</span><span class="s2">"cmake-3.6.1-Linux-x86_64/bin/cmake"</span>
 </pre></div>
 </div>
 </li>
 <li><p class="first">To download and extract the OpenCV source code, run the following commands:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>wget https://codeload.github.com/opencv/opencv/zip/2.4.13
 unzip <span class="m">2</span>.4.13
 <span class="nb">cd</span> opencv-2.4.13
 mkdir release
 <span class="nb">cd</span> release/
 </pre></div>
 </div>
 </li>
 <li><p class="first">Build OpenCV. The following commands build OpenCV with 10 threads. We
 disabled GPU support, which might significantly slow down an MXNet program
 running on a GPU processor. It also disables 1394 which might generate a
 warning. Then install it on <code class="docutils literal"><span class="pre">/usr/local</span></code>.</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>cmake -D <span class="nv">BUILD_opencv_gpu</span><span class="o">=</span>OFF -D <span class="nv">WITH_CUDA</span><span class="o">=</span>OFF -D <span class="nv">WITH_1394</span><span class="o">=</span>OFF -D <span class="nv">CMAKE_BUILD_TYPE</span><span class="o">=</span>RELEASE -D <span class="nv">CMAKE_INSTALL_PREFIX</span><span class="o">=</span>/usr/local ..
 make -j10
 sudo make install
 </pre></div>
 </div>
 </li>
 <li><p class="first">Add the lib path to your configuration such as <code class="docutils literal"><span class="pre">~/.bashrc</span></code>.</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">export</span> <span class="nv">PKG_CONFIG_PATH</span><span class="o">=</span><span class="nv">$PKG_CONFIG_PATH</span>:/usr/local/lib/pkgconfig/
 </pre></div>
 </div>
 </li>
 </ol>
 </div>
 </div><div class="windows"><p>First download and install <a class="reference external" href="http://opencv.org/releases.html">OpenCV</a>, then set
 the environment variable <code class="docutils literal"><span class="pre">OpenCV_DIR</span></code> to point to the OpenCV build directory.</p>
 </div></div>
 <div class="section" id="optional-cuda-cudnn-for-nvidia-gpus">
 <span id="optional-cuda-cudnn-for-nvidia-gpus"></span><h4>Optional: <a class="reference external" href="https://developer.nvidia.com/cuda-downloads">CUDA</a>/<a class="reference external" href="https://developer.nvidia.com/cudnn">cuDNN</a> for Nvidia GPUs<a class="headerlink" href="#optional-cuda-cudnn-for-nvidia-gpus" title="Permalink to this headline">¶</a></h4>
 <p>MXNet is compatible with both CUDA 7.5 and 8.0. It is recommended to use cuDNN 5.</p>
 <div class="linux">
 <div class="ubuntu"><p>Install CUDA 7.5 and cuDNN 5 on Ubuntu 14.04</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_7.5-18_amd64.deb
 sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_amd64.deb
 <span class="nb">echo</span> <span class="s2">"deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1404/x86_64 /"</span> <span class="p">|</span> sudo tee /etc/apt/sources.list.d/nvidia-ml.list
 sudo apt-get update
 sudo apt-get install -y linux-image-extra-<span class="sb">`</span>uname -r<span class="sb">`</span> linux-headers-<span class="sb">`</span>uname -r<span class="sb">`</span> linux-image-<span class="sb">`</span>uname -r<span class="sb">`</span>
 sudo apt-get install -y cuda libcudnn5-dev<span class="o">=</span><span class="m">5</span>.0.5-1+cuda7.5
 </pre></div>
 </div>
 </div>
 </div></div>
 </div>
 <div class="section" id="build">
 <span id="build"></span><h3>Build<a class="headerlink" href="#build" title="Permalink to this headline">¶</a></h3>
 <div class="linux macos"><p>First clone the recent codes</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>git clone --recursive https://github.com/dmlc/mxnet
 <span class="nb">cd</span> mxnet
 </pre></div>
 </div>
 <p>File
 <a class="reference external" href="https://github.com/dmlc/mxnet/blob/master/make/config.mk"><code class="docutils literal"><span class="pre">make/config.mk</span></code></a>
 contains all the compilation options. You can edit it and then <code class="docutils literal"><span class="pre">make</span></code>. There are
 some example build options</p>
 <p>If you want to build MXNet with C++ language binding, please make sure you read <a class="reference external" href="#build-the-c-package">Build the C++ package</a> first.</p>
 </div><div class="linux"><ul>
 <li><p class="first">Build without using OpenCV. <code class="docutils literal"><span class="pre">-j</span></code> runs multiple jobs against multi-core CPUs.</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>make -j <span class="nv">USE_OPENCV</span><span class="o">=</span><span class="m">0</span>
 </pre></div>
 </div>
 </li>
 <li><p class="first">Build with both GPU and OpenCV support</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>make -j <span class="nv">USE_BLAS</span><span class="o">=</span>openblas <span class="nv">USE_CUDA</span><span class="o">=</span><span class="m">1</span> <span class="nv">USE_CUDA_PATH</span><span class="o">=</span>/usr/local/cuda <span class="nv">USE_CUDNN</span><span class="o">=</span><span class="m">1</span>
 </pre></div>
 </div>
 </li>
 </ul>
 </div><div class="macos"><ul>
 <li><p class="first">Build with the default BLAS library and clang installed with <code class="docutils literal"><span class="pre">xcode</span></code> (OPENMP
 is disabled because it is not supported in default by clang).</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>make -j <span class="nv">USE_BLAS</span><span class="o">=</span>apple <span class="nv">USE_OPENCV</span><span class="o">=</span><span class="m">0</span> <span class="nv">USE_OPENMP</span><span class="o">=</span><span class="m">0</span>
 </pre></div>
 </div>
 </li>
 </ul>
 </div><div class="windows"><p>Use <a class="reference external" href="https://cmake.org/">CMake</a> to create a Visual Studio solution in <code class="docutils literal"><span class="pre">./build</span></code>.</p>
 <p>In Visual Studio, open the solution file,<code class="docutils literal"><span class="pre">.sln</span></code>, and compile it.
 These commands produce a library called <code class="docutils literal"><span class="pre">mxnet.dll</span></code> in the <code class="docutils literal"><span class="pre">./build/Release/</span></code> or <code class="docutils literal"><span class="pre">./build/Debug</span></code> folder.</p>
 </div></div>
 </div>
 <div class="section" id="build-the-c-package">
 <span id="build-the-c-package"></span><h2>Build the C++ package<a class="headerlink" href="#build-the-c-package" title="Permalink to this headline">¶</a></h2>
 <p>The C++ package has the same prerequisites as the MXNet library, you should also have <code class="docutils literal"><span class="pre">python</span></code> installed. (Both <code class="docutils literal"><span class="pre">python</span></code> 2 and 3 are supported)</p>
 <p>To enable C++ package, just add <code class="docutils literal"><span class="pre">USE_CPP_PACKAGE=1</span></code> in the build options when building the MXNet shared library.</p>
 </div>
 <div class="section" id="build-the-r-package">
 <span id="build-the-r-package"></span><h2>Build the R package<a class="headerlink" href="#build-the-r-package" title="Permalink to this headline">¶</a></h2>
 <p>The R package requires <code class="docutils literal"><span class="pre">R</span></code> to be installed.</p>
 <div class="ubuntu"><p>Follow the below instructions to install the latest R on Ubuntu 14.04 (trusty) and also the libraries used
 to build other R package dependencies.</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">echo</span> <span class="s2">"deb http://cran.rstudio.com/bin/linux/ubuntu trusty/"</span> >> /etc/apt/sources.list
 gpg --keyserver keyserver.ubuntu.com --recv-key E084DAB9
 gpg -a --export E084DAB9 <span class="p">|</span> apt-key add -

 apt-get update
 apt-get install -y r-base r-base-dev libxml2-dev libxt-dev libssl-dev
 </pre></div>
 </div>
 </div><p>Install the required R package dependencies:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">cd</span> R-package
 Rscript -e <span class="s2">"install.packages('devtools', repo = 'https://cran.rstudio.com')"</span>
 Rscript -e <span class="s2">"library(devtools); library(methods); options(repos=c(CRAN='https://cran.rstudio.com')); install_deps(dependencies = TRUE)"</span>
 </pre></div>
 </div>
 <p>Next, build and install the MXNet R package:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">cd</span> ..
 make rpkg
 R CMD INSTALL mxnet_current_r.tar.gz
 </pre></div>
 </div>
 </div>
 <div class="section" id="build-the-scala-package">
 <span id="build-the-scala-package"></span><h2>Build the Scala package<a class="headerlink" href="#build-the-scala-package" title="Permalink to this headline">¶</a></h2>
 <p>Both JDK and Maven are required to build the Scala package.</p>
 <div class="ubuntu"><div class="highlight-bash"><div class="highlight"><pre><span></span>sudo apt-get install -y maven default-jdk
 </pre></div>
 </div>
 </div><p>The following command builds the <code class="docutils literal"><span class="pre">.jar</span></code> package:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>make scalapkg
 </pre></div>
 </div>
 <p>which can be found by <code class="docutils literal"><span class="pre">ls</span> <span class="pre">scala-package/assembly/*/target/*SNAPSHOT.jar</span></code>.</p>
 <p>Optionally, we can install Scala for the interactive interface.</p>
 <div class="ubuntu"><div class="highlight-bash"><div class="highlight"><pre><span></span>wget http://downloads.lightbend.com/scala/2.11.8/scala-2.11.8.deb
 dpkg -i scala-2.11.8.deb
 rm scala-2.11.8.deb
 </pre></div>
 </div>
 </div><p>Then we can start <code class="docutils literal"><span class="pre">scala</span></code> with <code class="docutils literal"><span class="pre">mxnet</span></code> imported by</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>scala -cp scala-package/assembly/*/target/*SNAPSHOT.jar
 </pre></div>
 </div>
 </div>
 <div class="section" id="build-the-julia-package">
 <span id="build-the-julia-package"></span><h2>Build the Julia package<a class="headerlink" href="#build-the-julia-package" title="Permalink to this headline">¶</a></h2>
 <p>We need to first install Julia.</p>
 <div class="ubuntu centos linux"><p>The following commands install Julia 0.5.1</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>wget -q https://julialang.s3.amazonaws.com/bin/linux/x64/0.5/julia-0.5.1-linux-x86_64.tar.gz
 tar -zxf julia-0.5.1-linux-x86_64.tar.gz
 rm julia-0.5.1-linux-x86_64.tar.gz
 ln -s <span class="k">$(</span><span class="nb">pwd</span><span class="k">)</span>/julia-6445c82d00/bin/julia /usr/bin/julia
 </pre></div>
 </div>
 </div><p>Next set the environment variable <code class="docutils literal"><span class="pre">MXNET_HOME=/path/to/mxnet</span></code> so that Julia
 can find the pre-built library.</p>
 <p>Install the Julia package for MXNet with:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>julia -e <span class="s1">'Pkg.add("MXNet")'</span>
 </pre></div>
 </div>
 <div class="section" id="build-the-perl-package">
 <span id="build-the-perl-package"></span><h3>Build the Perl package<a class="headerlink" href="#build-the-perl-package" title="Permalink to this headline">¶</a></h3>
 <p>Run the following command from the MXNet source root directory to build the MXNet Perl package:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>    sudo apt-get install libmouse-perl pdl cpanminus swig libgraphviz-perl
     cpanm -q -L <span class="s2">"</span><span class="si">${</span><span class="nv">HOME</span><span class="si">}</span><span class="s2">/perl5"</span> Function::Parameters

     <span class="nv">MXNET_HOME</span><span class="o">=</span><span class="si">${</span><span class="nv">PWD</span><span class="si">}</span>
     <span class="nb">export</span> <span class="nv">LD_LIBRARY_PATH</span><span class="o">=</span><span class="si">${</span><span class="nv">MXNET_HOME</span><span class="si">}</span>/lib
     <span class="nb">export</span> <span class="nv">PERL5LIB</span><span class="o">=</span><span class="si">${</span><span class="nv">HOME</span><span class="si">}</span>/perl5/lib/perl5

     <span class="nb">cd</span> <span class="si">${</span><span class="nv">MXNET_HOME</span><span class="si">}</span>/perl-package/AI-MXNetCAPI/
     perl Makefile.PL <span class="nv">INSTALL_BASE</span><span class="o">=</span><span class="si">${</span><span class="nv">HOME</span><span class="si">}</span>/perl5
     make install

     <span class="nb">cd</span> <span class="si">${</span><span class="nv">MXNET_HOME</span><span class="si">}</span>/perl-package/AI-NNVMCAPI/
     perl Makefile.PL <span class="nv">INSTALL_BASE</span><span class="o">=</span><span class="si">${</span><span class="nv">HOME</span><span class="si">}</span>/perl5
     make install

     <span class="nb">cd</span> <span class="si">${</span><span class="nv">MXNET_HOME</span><span class="si">}</span>/perl-package/AI-MXNet/
     perl Makefile.PL <span class="nv">INSTALL_BASE</span><span class="o">=</span><span class="si">${</span><span class="nv">HOME</span><span class="si">}</span>/perl5
     make install
 </pre></div>
 </div>
 </div>
 </div>
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 <h3><a href="../index.html">Table Of Contents</a></h3>
 <ul>
 <li><a class="reference internal" href="#">Build MXNet from Source</a><ul>
 <li><a class="reference internal" href="#build-the-shared-library">Build the shared library</a><ul>
 <li><a class="reference internal" href="#prerequisites">Prerequisites</a><ul>
 <li><a class="reference internal" href="#c-build-tools">C++ build tools</a></li>
 <li><a class="reference internal" href="#blas-library">BLAS library</a></li>
 <li><a class="reference internal" href="#optional-opencv-for-image-loading-and-augmentation">Optional: OpenCV for Image Loading and Augmentation</a></li>
 <li><a class="reference internal" href="#optional-cuda-cudnn-for-nvidia-gpus">Optional: CUDA/cuDNN for Nvidia GPUs</a></li>
 </ul>
 </li>
 <li><a class="reference internal" href="#build">Build</a></li>
 </ul>
 </li>
 <li><a class="reference internal" href="#build-the-c-package">Build the C++ package</a></li>
 <li><a class="reference internal" href="#build-the-r-package">Build the R package</a></li>
 <li><a class="reference internal" href="#build-the-scala-package">Build the Scala package</a></li>
 <li><a class="reference internal" href="#build-the-julia-package">Build the Julia package</a><ul>
 <li><a class="reference internal" href="#build-the-perl-package">Build the Perl package</a></li>
 </ul>
 </li>
 </ul>
 </li>
 </ul>
 </div>
 </div>
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