| <!DOCTYPE html> |
| |
| <html lang="en"> |
| <head> |
| <meta charset="utf-8"> |
| <meta http-equiv="X-UA-Compatible" content="IE=edge"> |
| <meta name="viewport" content="width=device-width, initial-scale=1"> |
| |
| |
| <meta property="og:title" content="Installing MXNet on Windows" /> |
| <meta property="og:image" content="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/og-logo.png" /> |
| <meta property="og:image:secure_url" content="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/og-logo.png" /> |
| <meta property="og:description" content="Installing MXNet on Windows" /> |
| <title>Installing MXNet on Windows — mxnet documentation</title> |
| |
| <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap.min.css" integrity="sha384-1q8mTJOASx8j1Au+a5WDVnPi2lkFfwwEAa8hDDdjZlpLegxhjVME1fgjWPGmkzs7" crossorigin="anonymous"> |
| <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.5.0/css/font-awesome.min.css"> |
| |
| |
| <link rel="stylesheet" href="../_static/basic.css" type="text/css" /> |
| <link rel="stylesheet" href="../_static/pygments.css" type="text/css" /> |
| |
| <link rel="stylesheet" href="../_static/mxnet.css" type="text/css"> |
| |
| <script type="text/javascript"> |
| var DOCUMENTATION_OPTIONS = { |
| URL_ROOT: '../', |
| VERSION: '', |
| COLLAPSE_INDEX: false, |
| FILE_SUFFIX: '.html', |
| HAS_SOURCE: true, |
| SOURCELINK_SUFFIX: '.txt' |
| }; |
| </script> |
| |
| <script type="text/javascript" src="https://code.jquery.com/jquery-1.11.1.min.js"></script> |
| |
| <script type="text/javascript" src="../_static/underscore.js"></script> |
| |
| <script type="text/javascript" src="../_static/searchtools_custom.js"></script> |
| |
| <script type="text/javascript" src="../_static/doctools.js"></script> |
| |
| <script type="text/javascript" src="../_static/selectlang.js"></script> |
| |
| |
| <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script> |
| <script type="text/javascript"> jQuery(function() { Search.loadIndex("/versions/1.4.1/searchindex.js"); Search.init();}); </script> |
| |
| <script> |
| (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){ |
| (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new |
| Date();a=s.createElement(o), |
| m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) |
| })(window,document,'script','https://www.google-analytics.com/analytics.js','ga'); |
| |
| ga('create', 'UA-96378503-1', 'auto'); |
| ga('send', 'pageview'); |
| |
| </script> |
| |
| <!-- --> |
| <!-- <script type="text/javascript" src="../_static/jquery.js"></script> --> |
| <!-- --> |
| <!-- <script type="text/javascript" src="../_static/underscore.js"></script> --> |
| <!-- --> |
| <!-- <script type="text/javascript" src="../_static/doctools.js"></script> --> |
| <!-- --> |
| <!-- <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script> --> |
| <!-- --> |
| <link rel="index" title="Index" href="../genindex.html" /> |
| <link rel="search" title="Search" href="../search.html" /> |
| <link rel="up" title="Installing MXNet" href="index.html" /> |
| <link rel="next" title="MXNet Model Zoo" href="../model_zoo/index.html" /> |
| <link rel="prev" title="Validate Your MXNet Installation" href="validate_mxnet.html" /> |
| |
| <link rel="icon" type="image/png" href="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-icon.png"> |
| </head> |
| <body role="document" background="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-background-compressed.jpeg"> |
| <div class='content-block'><div class="navbar navbar-fixed-top"> |
| <div class="container" id="navContainer"> |
| <div id="header-inner" class="innder"> |
| <h1 id="logo-wrap"> |
| <a href="../" id="logo"><img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet_logo.png"></a> |
| </h1> |
| <nav class="nav-bar" id="main-nav"> |
| <a class="main-nav-link" href="/versions/1.4.1/install/index.html">Install</a> |
| <span id="dropdown-menu-position-anchor"> |
| <a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Gluon <span class="caret"></span></a> |
| <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu"> |
| <li><a class="main-nav-link" href="/versions/1.4.1/tutorials/gluon/gluon.html">About</a></li> |
| <li><a class="main-nav-link" href="https://www.d2l.ai/">Dive into Deep Learning</a></li> |
| <li><a class="main-nav-link" href="https://gluon-cv.mxnet.io">GluonCV Toolkit</a></li> |
| <li><a class="main-nav-link" href="https://gluon-nlp.mxnet.io/">GluonNLP Toolkit</a></li> |
| </ul> |
| </span> |
| <span id="dropdown-menu-position-anchor"> |
| <a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">API <span class="caret"></span></a> |
| <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu"> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/python/index.html">Python</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/c++/index.html">C++</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/clojure/index.html">Clojure</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/java/index.html">Java</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/julia/index.html">Julia</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/perl/index.html">Perl</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/r/index.html">R</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/scala/index.html">Scala</a></li> |
| </ul> |
| </span> |
| <span id="dropdown-menu-position-anchor-docs"> |
| <a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Docs <span class="caret"></span></a> |
| <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu-docs"> |
| <li><a class="main-nav-link" href="/versions/1.4.1/faq/index.html">FAQ</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/tutorials/index.html">Tutorials</a> |
| <li><a class="main-nav-link" href="https://github.com/apache/incubator-mxnet/tree/1.4.1/example">Examples</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/architecture/index.html">Architecture</a></li> |
| <li><a class="main-nav-link" href="https://cwiki.apache.org/confluence/display/MXNET/Apache+MXNet+Home">Developer Wiki</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/model_zoo/index.html">Model Zoo</a></li> |
| <li><a class="main-nav-link" href="https://github.com/onnx/onnx-mxnet">ONNX</a></li> |
| </li></ul> |
| </span> |
| <span id="dropdown-menu-position-anchor-community"> |
| <a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Community <span class="caret"></span></a> |
| <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu-community"> |
| <li><a class="main-nav-link" href="http://discuss.mxnet.io">Forum</a></li> |
| <li><a class="main-nav-link" href="https://github.com/apache/incubator-mxnet/tree/1.4.1">Github</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/community/contribute.html">Contribute</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/community/ecosystem.html">Ecosystem</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/community/powered_by.html">Powered By</a></li> |
| </ul> |
| </span> |
| <span id="dropdown-menu-position-anchor-version" style="position: relative"><a href="#" class="main-nav-link dropdown-toggle" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="true">1.4.1<span class="caret"></span></a><ul id="package-dropdown-menu" class="dropdown-menu"><li><a href="/">master</a></li><li><a href="/versions/1.7.0/">1.7.0</a></li><li><a href=/versions/1.6.0/>1.6.0</a></li><li><a href=/versions/1.5.0/>1.5.0</a></li><li><a href=/versions/1.4.1/>1.4.1</a></li><li><a href=/versions/1.3.1/>1.3.1</a></li><li><a href=/versions/1.2.1/>1.2.1</a></li><li><a href=/versions/1.1.0/>1.1.0</a></li><li><a href=/versions/1.0.0/>1.0.0</a></li><li><a href=/versions/0.12.1/>0.12.1</a></li><li><a href=/versions/0.11.0/>0.11.0</a></li></ul></span></nav> |
| |
| <script> function getRootPath(){ return "../" } </script> |
| <div class="burgerIcon dropdown"> |
| <a class="dropdown-toggle" data-toggle="dropdown" href="#" role="button">☰</a> |
| <ul class="dropdown-menu" id="burgerMenu"> |
| <li><a href="/versions/1.4.1/install/index.html">Install</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/tutorials/index.html">Tutorials</a></li> |
| <li class="dropdown-submenu dropdown"> |
| <a aria-expanded="true" aria-haspopup="true" class="dropdown-toggle burger-link" data-toggle="dropdown" href="#" tabindex="-1">Gluon</a> |
| <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu"> |
| <li><a class="main-nav-link" href="/versions/1.4.1/tutorials/gluon/gluon.html">About</a></li> |
| <li><a class="main-nav-link" href="http://gluon.mxnet.io">The Straight Dope (Tutorials)</a></li> |
| <li><a class="main-nav-link" href="https://gluon-cv.mxnet.io">GluonCV Toolkit</a></li> |
| <li><a class="main-nav-link" href="https://gluon-nlp.mxnet.io/">GluonNLP Toolkit</a></li> |
| </ul> |
| </li> |
| <li class="dropdown-submenu"> |
| <a aria-expanded="true" aria-haspopup="true" class="dropdown-toggle burger-link" data-toggle="dropdown" href="#" tabindex="-1">API</a> |
| <ul class="dropdown-menu"> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/python/index.html">Python</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/c++/index.html">C++</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/clojure/index.html">Clojure</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/java/index.html">Java</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/julia/index.html">Julia</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/perl/index.html">Perl</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/r/index.html">R</a></li> |
| <li><a class="main-nav-link" href="/versions/1.4.1/api/scala/index.html">Scala</a></li> |
| </ul> |
| </li> |
| <li class="dropdown-submenu"> |
| <a aria-expanded="true" aria-haspopup="true" class="dropdown-toggle burger-link" data-toggle="dropdown" href="#" tabindex="-1">Docs</a> |
| <ul class="dropdown-menu"> |
| <li><a href="/versions/1.4.1/faq/index.html" tabindex="-1">FAQ</a></li> |
| <li><a href="/versions/1.4.1/tutorials/index.html" tabindex="-1">Tutorials</a></li> |
| <li><a href="https://github.com/apache/incubator-mxnet/tree/1.4.1/example" tabindex="-1">Examples</a></li> |
| <li><a href="/versions/1.4.1/architecture/index.html" tabindex="-1">Architecture</a></li> |
| <li><a href="https://cwiki.apache.org/confluence/display/MXNET/Apache+MXNet+Home" tabindex="-1">Developer Wiki</a></li> |
| <li><a href="/versions/1.4.1/model_zoo/index.html" tabindex="-1">Gluon Model Zoo</a></li> |
| <li><a href="https://github.com/onnx/onnx-mxnet" tabindex="-1">ONNX</a></li> |
| </ul> |
| </li> |
| <li class="dropdown-submenu dropdown"> |
| <a aria-haspopup="true" class="dropdown-toggle burger-link" data-toggle="dropdown" href="#" role="button" tabindex="-1">Community</a> |
| <ul class="dropdown-menu"> |
| <li><a href="http://discuss.mxnet.io" tabindex="-1">Forum</a></li> |
| <li><a href="https://github.com/apache/incubator-mxnet/tree/1.4.1" tabindex="-1">Github</a></li> |
| <li><a href="/versions/1.4.1/community/contribute.html" tabindex="-1">Contribute</a></li> |
| <li><a href="/versions/1.4.1/community/ecosystem.html" tabindex="-1">Ecosystem</a></li> |
| <li><a href="/versions/1.4.1/community/powered_by.html" tabindex="-1">Powered By</a></li> |
| </ul> |
| </li> |
| <li id="dropdown-menu-position-anchor-version-mobile" class="dropdown-submenu" style="position: relative"><a href="#" tabindex="-1">1.4.1</a><ul class="dropdown-menu"><li><a tabindex="-1" href=/>master</a></li><li><a tabindex="-1" href=/versions/1.6.0/>1.6.0</a></li><li><a tabindex="-1" href=/versions/1.5.0/>1.5.0</a></li><li><a tabindex="-1" href=/versions/1.4.1/>1.4.1</a></li><li><a tabindex="-1" href=/versions/1.3.1/>1.3.1</a></li><li><a tabindex="-1" href=/versions/1.2.1/>1.2.1</a></li><li><a tabindex="-1" href=/versions/1.1.0/>1.1.0</a></li><li><a tabindex="-1" href=/versions/1.0.0/>1.0.0</a></li><li><a tabindex="-1" href=/versions/0.12.1/>0.12.1</a></li><li><a tabindex="-1" href=/versions/0.11.0/>0.11.0</a></li></ul></li></ul> |
| </div> |
| |
| <div class="plusIcon dropdown"> |
| <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button"><span class="glyphicon glyphicon-plus" aria-hidden="true"></span></a> |
| <ul id="plusMenu" class="dropdown-menu dropdown-menu-right"></ul> |
| </div> |
| <div id="search-input-wrap"> |
| |
| <form class="" role="search" action="../search.html" method="get" autocomplete="off"> |
| <div class="form-group inner-addon left-addon"> |
| <i class="glyphicon glyphicon-search"></i> |
| <input type="text" name="q" class="form-control" placeholder="Search"> |
| </div> |
| <input type="hidden" name="check_keywords" value="yes" /> |
| <input type="hidden" name="area" value="default" /> |
| |
| </form> |
| <div id="search-preview"></div> |
| </div> |
| <div id='searchIcon'> |
| <span class="glyphicon glyphicon-search" aria-hidden="true"></span> |
| </div> |
| |
| <!-- <div id="lang-select-wrap"> --> |
| <!-- <label id="lang-select-label"> --> |
| <!-- <\!-- <i class="fa fa-globe"></i> -\-> --> |
| <!-- <span></span> --> |
| <!-- </label> --> |
| <!-- <select id="lang-select"> --> |
| <!-- <option value="en">Eng</option> --> |
| <!-- <option value="zh">中文</option> --> |
| <!-- </select> --> |
| <!-- </div> --> |
| <!-- <a id="mobile-nav-toggle"> |
| <span class="mobile-nav-toggle-bar"></span> |
| <span class="mobile-nav-toggle-bar"></span> |
| <span class="mobile-nav-toggle-bar"></span> |
| </a> --> |
| </div> |
| </div> |
| </div> |
| |
| |
| <script type="text/javascript"> |
| $('body').css('background', 'white'); |
| </script> |
| <div class="container"> |
| <div class="row"> |
| <div class="sphinxsidebar leftsidebar" role="navigation" aria-label="main navigation"> |
| <div class="sphinxsidebarwrapper"> |
| |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="../api/index.html">MXNet APIs</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="../architecture/index.html">MXNet Architecture</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="../community/index.html">MXNet Community</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="../faq/index.html">MXNet FAQ</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="../gluon/index.html">About Gluon</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="index.html">Installing MXNet</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="index.html#nvidia-jetson-tx-family">Nvidia Jetson TX family</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="index.html#source-download">Source Download</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="../model_zoo/index.html">MXNet Model Zoo</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="../tutorials/index.html">Tutorials</a></li> |
| </ul> |
| |
| </div> |
| </div> |
| <div class="content"> |
| <div class="page-tracker"></div> |
| |
| <!--- Licensed to the Apache Software Foundation (ASF) under one --> |
| <!--- or more contributor license agreements. See the NOTICE file --> |
| <!--- distributed with this work for additional information --> |
| <!--- regarding copyright ownership. The ASF licenses this file --> |
| <!--- to you under the Apache License, Version 2.0 (the --> |
| <!--- "License"); you may not use this file except in compliance --> |
| <!--- with the License. You may obtain a copy of the License at --><!--- http://www.apache.org/licenses/LICENSE-2.0 --><!--- Unless required by applicable law or agreed to in writing, --> |
| <!--- software distributed under the License is distributed on an --> |
| <!--- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY --> |
| <!--- KIND, either express or implied. See the License for the --> |
| <!--- specific language governing permissions and limitations --> |
| <!--- under the License. --><div class="section" id="installing-mxnet-on-windows"> |
| <span id="installing-mxnet-on-windows"></span><h1>Installing MXNet on Windows<a class="headerlink" href="#installing-mxnet-on-windows" title="Permalink to this headline">¶</a></h1> |
| <p>The following describes how to install with pip for computers with CPUs, Intel CPUs, and NVIDIA GPUs. Further along in the document you can learn how to build MXNet from source on Windows, or how to install packages that support different language APIs to MXNet.</p> |
| <ul class="simple"> |
| <li><a class="reference external" href="#prerequisites">Prerequisites</a></li> |
| <li><a class="reference external" href="#install-mxnet-with-python">Install MXNet with Python</a><ul> |
| <li><a class="reference external" href="#install-with-cpus">Install with CPUs</a></li> |
| <li><a class="reference external" href="#install-with-intel-cpus">Install with Intel CPUs</a></li> |
| <li><a class="reference external" href="#install-with-gpus">Install with GPUs</a></li> |
| <li><a class="reference external" href="#notes-on-the-python-packages">Notes on the Python Packages</a></li> |
| </ul> |
| </li> |
| <li><a class="reference external" href="#build-from-source">Build from Source</a></li> |
| <li>Install MXNet with a Programming Language API<ul> |
| <li><a class="reference external" href="#install-the-mxnet-package-for-python">Python</a></li> |
| <li><a class="reference external" href="#install-the-mxnet-package-for-r">R</a></li> |
| <li><a class="reference external" href="#install-the-mxnet-package-for-julia">Julia</a></li> |
| </ul> |
| </li> |
| </ul> |
| <div class="section" id="prerequisites"> |
| <span id="prerequisites"></span><h2>Prerequisites<a class="headerlink" href="#prerequisites" title="Permalink to this headline">¶</a></h2> |
| <div class="section" id="minimum-system-requirements"> |
| <span id="minimum-system-requirements"></span><h3>Minimum System Requirements<a class="headerlink" href="#minimum-system-requirements" title="Permalink to this headline">¶</a></h3> |
| <ul class="simple"> |
| <li>Windows 7<sup><a href="#fn1" id="ref1">1</a></sup>, 10, Server 2012 R2, or Server 2016</li> |
| <li>Visual Studio 2015 or 2017 (any type)</li> |
| <li>Python 2.7 or 3.6</li> |
| <li>pip</li> |
| </ul> |
| <p><sup id="fn1">1. There are <a class="reference external" href="https://github.com/apache/incubator-mxnet/issues?utf8=%E2%9C%93&q=is%3Aissue+windows7+label%3AWindows+">known issues</a> with Windows 7. <a href="#ref1" title="Return to source text.">↩</a></sup></p> |
| </div> |
| <div class="section" id="recommended-system-requirements"> |
| <span id="recommended-system-requirements"></span><h3>Recommended System Requirements<a class="headerlink" href="#recommended-system-requirements" title="Permalink to this headline">¶</a></h3> |
| <ul class="simple"> |
| <li>Windows 10, Server 2012 R2, or Server 2016</li> |
| <li>Visual Studio 2017 (any type)</li> |
| <li>At least one <a class="reference external" href="https://developer.nvidia.com/cuda-gpus">NVIDIA CUDA-enabled GPU</a></li> |
| <li>MKL-enabled CPU: Intel® Xeon® processor, Intel® Core™ processor family, Intel Atom® processor, or Intel® Xeon Phi™ processor</li> |
| <li>Python 2.7 or 3.6</li> |
| <li>pip</li> |
| </ul> |
| </div> |
| </div> |
| <div class="section" id="install-mxnet-with-python"> |
| <span id="install-mxnet-with-python"></span><h2>Install MXNet with Python<a class="headerlink" href="#install-mxnet-with-python" title="Permalink to this headline">¶</a></h2> |
| <p>The easiest way to install MXNet on Windows is by using a <a class="reference external" href="https://pip.pypa.io/en/stable/installing/">Python pip package</a>.</p> |
| <p><strong>Note</strong>: Windows pip packages typically release a few days after a new version MXNet is released. Make sure you verify which version gets installed.</p> |
| <div class="section" id="install-with-cpus"> |
| <span id="install-with-cpus"></span><h3>Install with CPUs<a class="headerlink" href="#install-with-cpus" title="Permalink to this headline">¶</a></h3> |
| <p>Install MXNet with CPU support with Python:</p> |
| <div class="highlight-bash"><div class="highlight"><pre><span></span>pip install mxnet |
| </pre></div> |
| </div> |
| <p>Now <a class="reference internal" href="validate_mxnet.html"><span class="doc">validate your MXNet installation with Python</span></a>.</p> |
| </div> |
| <div class="section" id="install-with-intel-cpus"> |
| <span id="install-with-intel-cpus"></span><h3>Install with Intel CPUs<a class="headerlink" href="#install-with-intel-cpus" title="Permalink to this headline">¶</a></h3> |
| <p>MXNet has experimental support for Intel <a class="reference external" href="https://software.intel.com/en-us/mkl">MKL</a> and <a class="reference external" href="https://github.com/intel/mkl-dnn">MKL-DNN</a>. When using supported Intel hardware, inference and training can be vastly faster when using MXNet with <a class="reference external" href="https://software.intel.com/en-us/mkl">MKL</a> or <a class="reference external" href="https://github.com/intel/mkl-dnn">MKL-DNN</a>.</p> |
| <p>The following steps will setup MXNet with MKL. MKL-DNN can be enabled only when building from source.</p> |
| <ol class="simple"> |
| <li>Download and install <a class="reference external" href="https://software.intel.com/en-us/mkl/choose-download/windows">Intel MKL</a> (registration required).</li> |
| <li>Install MXNet with MKL support with Python:</li> |
| </ol> |
| <div class="highlight-bash"><div class="highlight"><pre><span></span>pip install mxnet-mkl |
| </pre></div> |
| </div> |
| <p>Now <a class="reference internal" href="validate_mxnet.html"><span class="doc">validate your MXNet installation with Python</span></a>.</p> |
| </div> |
| <div class="section" id="install-with-nvidia-gpus"> |
| <span id="install-with-nvidia-gpus"></span><h3>Install with NVIDIA GPUs<a class="headerlink" href="#install-with-nvidia-gpus" title="Permalink to this headline">¶</a></h3> |
| <p>When using supported NVIDIA GPU hardware, inference and training can be vastly faster with <a class="reference external" href="https://developer.nvidia.com/cuda-toolkit">NVIDIA CUDA</a> and <a class="reference external" href="https://developer.nvidia.com/cudnn">cuDNN</a>. You have two options for installing MXNet with CUDA support with a Python package.</p> |
| <ul class="simple"> |
| <li><a class="reference external" href="#install-with-cuda-support">Install with CUDA support</a></li> |
| <li><a class="reference external" href="#install-with-cuda-and-mkl-support">Install with CUDA and MKL support</a></li> |
| </ul> |
| <div class="section" id="install-with-cuda-support"> |
| <span id="install-with-cuda-support"></span><h4>Install with CUDA Support<a class="headerlink" href="#install-with-cuda-support" title="Permalink to this headline">¶</a></h4> |
| <p>The following steps will setup MXNet with CUDA. cuDNN can be enabled only when building from source.</p> |
| <ol class="simple"> |
| <li>Install <a class="reference external" href="https://www.visualstudio.com/downloads/">Microsoft Visual Studio 2017</a> or <a class="reference external" href="https://www.visualstudio.com/vs/older-downloads/">Microsoft Visual Studio 2015</a>.</li> |
| <li>Download and install <a class="reference external" href="https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal">NVIDIA CUDA</a>. CUDA versions 9.2 or 9.0 are recommended. Some <a class="reference external" href="https://github.com/apache/incubator-mxnet/labels/CUDA">issues with CUDA 9.1</a> have been identified in the past.</li> |
| <li>Download and install <a class="reference external" href="https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows">NVIDIA_CUDA_DNN</a></li> |
| <li>Install MXNet with CUDA support with pip:</li> |
| </ol> |
| <div class="highlight-bash"><div class="highlight"><pre><span></span>pip install mxnet-cu92 |
| </pre></div> |
| </div> |
| <p>Once you have installed a version of MXNet, <a class="reference internal" href="validate_mxnet.html"><span class="doc">validate your MXNet installation with Python</span></a>.</p> |
| </div> |
| <div class="section" id="install-with-cuda-and-mkl-support"> |
| <span id="install-with-cuda-and-mkl-support"></span><h4>Install with CUDA and MKL Support<a class="headerlink" href="#install-with-cuda-and-mkl-support" title="Permalink to this headline">¶</a></h4> |
| <p>You can also use a combination of CPU/GPU enhancements provided by Intel and NVIDIA.</p> |
| <p>The following steps will setup MXNet with CUDA and MKL.</p> |
| <ol class="simple"> |
| <li>Install <a class="reference external" href="https://www.visualstudio.com/downloads/">Microsoft Visual Studio 2017</a> or <a class="reference external" href="https://www.visualstudio.com/vs/older-downloads/">Microsoft Visual Studio 2015</a>.</li> |
| <li>Download and install <a class="reference external" href="https://software.intel.com/en-us/mkl/choose-download/windows">Intel MKL</a> (registration required).</li> |
| <li>Download and install <a class="reference external" href="https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal">NVIDIA CUDA</a>.</li> |
| <li>Download and install <a class="reference external" href="https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows">NVIDIA_CUDA_DNN</a></li> |
| <li>Install MXNet with MKL support with pip:</li> |
| </ol> |
| <div class="highlight-bash"><div class="highlight"><pre><span></span>pip install mxnet-cu92mkl |
| </pre></div> |
| </div> |
| <p>Once you have installed a version of MXNet, <a class="reference internal" href="validate_mxnet.html"><span class="doc">validate your MXNet installation with Python</span></a>.</p> |
| </div> |
| </div> |
| <div class="section" id="notes-on-the-python-packages"> |
| <span id="notes-on-the-python-packages"></span><h3>Notes on the Python Packages<a class="headerlink" href="#notes-on-the-python-packages" title="Permalink to this headline">¶</a></h3> |
| <p>To get further enhancements for deep neural networks, you may want to enable MKL-DNN and/or cuDNN. Each of these require you to <a class="reference external" href="#build-from-source">build from source</a> and to enable the build flags for each.</p> |
| <p>Check the chart below for other options or refer to <a class="reference external" href="https://pypi.org/project/mxnet/">PyPI for other MXNet pip packages</a>.</p> |
| <p><img alt="pip packages" src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/install/pip-packages.png" /></p> |
| </div> |
| </div> |
| <div class="section" id="build-from-source"> |
| <span id="build-from-source"></span><h2>Build from Source<a class="headerlink" href="#build-from-source" title="Permalink to this headline">¶</a></h2> |
| <p><strong>IMPORTANT: It is recommended that you review the <a class="reference internal" href="build_from_source.html"><span class="doc">build from source guide</span></a> first.</strong> It describes many of the build options that come with MXNet in more detail. You may decide to install additional dependencies and modify your build flags after reviewing this material.</p> |
| <p>We provide two primary options to build and install MXNet yourself using <a class="reference external" href="https://www.visualstudio.com/downloads/">Microsoft Visual Studio 2017</a> or <a class="reference external" href="https://www.visualstudio.com/vs/older-downloads/">Microsoft Visual Studio 2015</a>.</p> |
| <p><strong>NOTE:</strong> Visual Studio 2017’s compiler is <code class="docutils literal"><span class="pre">vc15</span></code>. This is not to be confused with Visual Studio 2015’s compiler, <code class="docutils literal"><span class="pre">vc14</span></code>.</p> |
| <p>You also have the option to install MXNet with MKL or MKL-DNN. In this case it is recommended that you refer to the <a class="reference external" href="https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md">MKLDNN_README</a>.</p> |
| <p><strong>Option 1: Build with Microsoft Visual Studio 2017 (VS2017)</strong></p> |
| <p>To build and install MXNet yourself using <a class="reference external" href="https://www.visualstudio.com/downloads/">VS2017</a>, you need the following dependencies. You may try a newer version of a particular dependency, but please open a pull request or <a class="reference external" href="https://github.com/apache/incubator-mxnet/issues/new">issue</a> to update this guide if a newer version is validated.</p> |
| <ol class="simple"> |
| <li>Install or update VS2017.<ul> |
| <li>If <a class="reference external" href="https://www.visualstudio.com/downloads/">VS2017</a> is not already installed, download and install it. You can download and install the free community edition.</li> |
| <li>When prompted about installing Git, go ahead and install it.</li> |
| <li>If VS2017 is already installed you will want to update it. Proceed to the next step to modify your installation. You will be given the opportunity to update VS2017 as well</li> |
| </ul> |
| </li> |
| <li>Follow the <a class="reference external" href="https://docs.microsoft.com/en-us/visualstudio/install/modify-visual-studio">instructions for opening the Visual Studio Installer</a> to modify <code class="docutils literal"><span class="pre">Individual</span> <span class="pre">components</span></code>.</li> |
| <li>Once in the Visual Studio Installer application, update as needed, then look for and check <code class="docutils literal"><span class="pre">VC++</span> <span class="pre">2017</span> <span class="pre">version</span> <span class="pre">15.4</span> <span class="pre">v14.11</span> <span class="pre">toolset</span></code>, and click <code class="docutils literal"><span class="pre">Modify</span></code>.</li> |
| <li>Change the version of the Visual studio 2017 to v14.11 using the following command (by default the VS2017 is installed in the following path):</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="s2">"C:\Program Files (x86)\Microsoft Visual Studio</span><span class="se">\201</span><span class="s2">7\Community\VC\Auxiliary\Build</span><span class="se">\v</span><span class="s2">cvars64.bat"</span> <span class="o">-</span><span class="n">vcvars_ver</span><span class="o">=</span><span class="mf">14.11</span> |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Download and install <a class="reference external" href="https://cmake.org/download">CMake</a> if it is not already installed. <a class="reference external" href="https://cmake.org/files/v3.12/cmake-3.12.2-win64-x64.msi">CMake v3.12.2</a> has been tested with MXNet.</li> |
| <li>Download and run the <a class="reference external" href="https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.4.1/opencv-3.4.1-vc14_vc15.exe/download">OpenCV</a> package. There are more recent versions of OpenCV, so please create an issue/PR to update this info if you validate one of these later versions.</li> |
| <li>This will unzip several files. You can place them in another directory if you wish. We will use <code class="docutils literal"><span class="pre">C:\utils</span></code>(<code class="docutils literal"><span class="pre">mkdir</span> <span class="pre">C:\utils</span></code>) as our default path.</li> |
| <li>Set the environment variable <code class="docutils literal"><span class="pre">OpenCV_DIR</span></code> to point to the OpenCV build directory that you just unzipped. Start <code class="docutils literal"><span class="pre">cmd</span></code> and type <code class="docutils literal"><span class="pre">set</span> <span class="pre">OpenCV_DIR=C:\utils\opencv\build</span></code>.</li> |
| <li>If you don’t have the Intel Math Kernel Library (MKL) installed, you can install it and follow the <a class="reference external" href="https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md">MKLDNN_README</a> from here, or you can use OpenBLAS. These instructions will assume you’re using OpenBLAS.</li> |
| <li>Download the <a class="reference external" href="https://sourceforge.net/projects/openblas/files/v0.2.19/OpenBLAS-v0.2.19-Win64-int32.zip/download">OpenBlas</a> package. Later versions of OpenBLAS are available, but you would need to build from source. v0.2.19 is the most recent version that ships with binaries. Contributions of more recent binaries would be appreciated.</li> |
| <li>Unzip the file, rename it to <code class="docutils literal"><span class="pre">OpenBLAS</span></code> and put it under <code class="docutils literal"><span class="pre">C:\utils</span></code>. You can place the unzipped files and folders in another directory if you wish.</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 and type <code class="docutils literal"><span class="pre">set</span> <span class="pre">OpenBLAS_HOME=C:\utils\OpenBLAS</span></code> on the command prompt(<code class="docutils literal"><span class="pre">cmd</span></code>).</li> |
| <li>Download and install <a class="reference external" href="https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal">CUDA</a>. If you already had CUDA, then installed VS2017, you should reinstall CUDA now so that you get the CUDA toolkit components for VS2017 integration. Note that the latest CUDA version supported by MXNet is <a class="reference external" href="https://developer.nvidia.com/cuda-92-download-archive">9.2</a>. You might also want to find other CUDA verion on the <a class="reference external" href="https://developer.nvidia.com/cuda-toolkit-archive">Legacy Releases</a>.</li> |
| <li>Download and install cuDNN. To get access to the download link, register as an NVIDIA community user. Then follow the <a class="reference external" href="http://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows">link</a> to install the cuDNN and put those libraries into <code class="docutils literal"><span class="pre">C:\cuda</span></code>.</li> |
| <li>Download and install <a class="reference external" href="https://git-for-windows.github.io/">git</a> if you haven’t already.</li> |
| </ol> |
| <p>After you have installed all of the required dependencies, build the MXNet source code:</p> |
| <ol class="simple"> |
| <li>Start <code class="docutils literal"><span class="pre">cmd</span></code> in windows.</li> |
| <li>Download the MXNet source code from GitHub by using following command:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">cd</span> <span class="n">C</span><span class="p">:</span>\ |
| <span class="n">git</span> <span class="n">clone</span> <span class="n">https</span><span class="p">:</span><span class="o">//</span><span class="n">github</span><span class="o">.</span><span class="n">com</span><span class="o">/</span><span class="n">apache</span><span class="o">/</span><span class="n">incubator</span><span class="o">-</span><span class="n">mxnet</span><span class="o">.</span><span class="n">git</span> <span class="o">--</span><span class="n">recursive</span> |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Verify that the <code class="docutils literal"><span class="pre">DCUDNN_INCLUDE</span></code> and <code class="docutils literal"><span class="pre">DCUDNN_LIBRARY</span></code> environment variables are pointing to the <code class="docutils literal"><span class="pre">include</span></code> folder and <code class="docutils literal"><span class="pre">cudnn.lib</span></code> file of your CUDA installed location, and <code class="docutils literal"><span class="pre">C:\incubator-mxnet</span></code> is the location of the source code you just cloned in the previous step.</li> |
| <li>Create a build dir using the following command and go to the directory, for example:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">mkdir</span> <span class="n">C</span><span class="p">:</span>\<span class="n">incubator</span><span class="o">-</span><span class="n">mxnet</span>\<span class="n">build</span> |
| <span class="n">cd</span> <span class="n">C</span><span class="p">:</span>\<span class="n">incubator</span><span class="o">-</span><span class="n">mxnet</span>\<span class="n">build</span> |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Compile the MXNet source code with <code class="docutils literal"><span class="pre">cmake</span></code> by using following command:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio 15 2017 Win64"</span> <span class="o">-</span><span class="n">T</span> <span class="n">cuda</span><span class="o">=</span><span class="mf">9.2</span><span class="p">,</span><span class="n">host</span><span class="o">=</span><span class="n">x64</span> <span class="o">-</span><span class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">1</span> <span class="o">-</span><span class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">1</span> <span class="o">-</span><span class="n">DUSE_NVRTC</span><span class="o">=</span><span class="mi">1</span> <span class="o">-</span><span class="n">DUSE_OPENCV</span><span class="o">=</span><span class="mi">1</span> <span class="o">-</span><span class="n">DUSE_OPENMP</span><span class="o">=</span><span class="mi">1</span> <span class="o">-</span><span class="n">DUSE_BLAS</span><span class="o">=</span><span class="nb">open</span> <span class="o">-</span><span class="n">DUSE_LAPACK</span><span class="o">=</span><span class="mi">1</span> <span class="o">-</span><span class="n">DUSE_DIST_KVSTORE</span><span class="o">=</span><span class="mi">0</span> <span class="o">-</span><span class="n">DCUDA_ARCH_LIST</span><span class="o">=</span><span class="n">Common</span> <span class="o">-</span><span class="n">DCUDA_TOOLSET</span><span class="o">=</span><span class="mf">9.2</span> <span class="o">-</span><span class="n">DCUDNN_INCLUDE</span><span class="o">=</span><span class="n">C</span><span class="p">:</span>\<span class="n">cuda</span>\<span class="n">include</span> <span class="o">-</span><span class="n">DCUDNN_LIBRARY</span><span class="o">=</span><span class="n">C</span><span class="p">:</span>\<span class="n">cuda</span>\<span class="n">lib</span>\<span class="n">x64</span>\<span class="n">cudnn</span><span class="o">.</span><span class="n">lib</span> <span class="s2">"C:\incubator-mxnet"</span> |
| </pre></div> |
| </div> |
| <ul class="simple"> |
| <li>Make sure you set the environment variables correctly (OpenBLAS_HOME, OpenCV_DIR) and change the version of the Visual studio 2017 to v14.11 before enter above command.</li> |
| </ul> |
| <ol class="simple"> |
| <li>After the CMake successfully completed, compile the the MXNet source code by using following command:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">msbuild</span> <span class="n">mxnet</span><span class="o">.</span><span class="n">sln</span> <span class="o">/</span><span class="n">p</span><span class="p">:</span><span class="n">Configuration</span><span class="o">=</span><span class="n">Release</span><span class="p">;</span><span class="n">Platform</span><span class="o">=</span><span class="n">x64</span> <span class="o">/</span><span class="n">maxcpucount</span> |
| </pre></div> |
| </div> |
| <p><strong>Option 2: Build with Visual Studio 2015</strong></p> |
| <p>To build and install MXNet yourself using <a class="reference external" href="https://www.visualstudio.com/vs/older-downloads/">Microsoft Visual Studio 2015</a>, you need the following dependencies. You may try a newer version of a particular dependency, but please open a pull request or <a class="reference external" href="https://github.com/apache/incubator-mxnet/issues/new">issue</a> to update this guide if a newer version is validated.</p> |
| <ol class="simple"> |
| <li>If <a class="reference external" href="https://www.visualstudio.com/vs/older-downloads/">Microsoft Visual Studio 2015</a> is not already installed, download and install it. You can download and install the free community edition. At least Update 3 of Microsoft Visual Studio 2015 is required to build MXNet from source. Upgrade via it’s <code class="docutils literal"><span class="pre">Tools</span> <span class="pre">-></span> <span class="pre">Extensions</span> <span class="pre">and</span> <span class="pre">Updates...</span> <span class="pre">|</span> <span class="pre">Product</span> <span class="pre">Updates</span></code> menu.</li> |
| <li>Download and install <a class="reference external" href="https://cmake.org/">CMake</a> if it is not already installed.</li> |
| <li>Download and install <a class="reference external" href="http://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.0.0/opencv-3.0.0.exe/download">OpenCV</a>.</li> |
| <li>Unzip the OpenCV package.</li> |
| <li>Set the environment variable <code class="docutils literal"><span class="pre">OpenCV_DIR</span></code> to point to the <code class="docutils literal"><span class="pre">OpenCV</span> <span class="pre">build</span> <span class="pre">directory</span></code> (<code class="docutils literal"><span class="pre">C:\opencv\build\x64\vc14</span></code> for example). Also, you need to add the OpenCV bin directory (<code class="docutils literal"><span class="pre">C:\opencv\build\x64\vc14\bin</span></code> for example) to the <code class="docutils literal"><span class="pre">PATH</span></code> variable.</li> |
| <li>If you don’t have the Intel Math Kernel Library (MKL) installed, download and install <a class="reference external" href="http://sourceforge.net/projects/openblas/files/v0.2.14/">OpenBlas</a>.</li> |
| <li>Set the environment variable <code class="docutils literal"><span class="pre">OpenBLAS_HOME</span></code> to point to the <code class="docutils literal"><span class="pre">OpenBLAS</span></code> 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> |
| <li>Download and install <a class="reference external" href="https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64">CUDA</a> and <a class="reference external" href="https://developer.nvidia.com/cudnn">cuDNN</a>. To get access to the download link, register as an NVIDIA community user.</li> |
| <li>Set the environment variable <code class="docutils literal"><span class="pre">CUDACXX</span></code> to point to the <code class="docutils literal"><span class="pre">CUDA</span> <span class="pre">Compiler</span></code>(<code class="docutils literal"><span class="pre">C:\Program</span> <span class="pre">Files\NVIDIA</span> <span class="pre">GPU</span> <span class="pre">Computing</span> <span class="pre">Toolkit\CUDA\v9.1\bin\nvcc.exe</span></code> for example).</li> |
| <li>Set the environment variable <code class="docutils literal"><span class="pre">CUDNN_ROOT</span></code> to point to the <code class="docutils literal"><span class="pre">cuDNN</span></code> directory that contains the <code class="docutils literal"><span class="pre">include</span></code>, <code class="docutils literal"><span class="pre">lib</span></code> and <code class="docutils literal"><span class="pre">bin</span></code> directories (<code class="docutils literal"><span class="pre">C:\Downloads\cudnn-9.1-windows7-x64-v7\cuda</span></code> for example).</li> |
| </ol> |
| <p>After you have installed all of the required dependencies, build the MXNet source code:</p> |
| <ol class="simple"> |
| <li>Download the MXNet source code from <a class="reference external" href="https://github.com/apache/incubator-mxnet">GitHub</a> (make sure you also download third parties submodules e.g. <code class="docutils literal"><span class="pre">git</span> <span class="pre">clone</span> <span class="pre">--recurse-submodules</span></code>).</li> |
| <li>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>.</li> |
| <li>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.</li> |
| </ol> |
| <p><p> </p> |
| |
| Next, we install <code class="docutils literal"><span class="pre">graphviz</span></code> library that we use for visualizing network graphs you build on MXNet. We will also install <a class="reference external" href="http://jupyter.readthedocs.io/">Jupyter Notebook</a> used for running MXNet tutorials and examples.</p> |
| <ul class="simple"> |
| <li>Install <code class="docutils literal"><span class="pre">graphviz</span></code> by downloading MSI installer from <a class="reference external" href="https://graphviz.gitlab.io/_pages/Download/Download_windows.html">Graphviz Download Page</a>. |
| <strong>Note</strong> Make sure to add graphviz executable path to PATH environment variable. Refer <a class="reference external" href="http://stackoverflow.com/questions/35064304/runtimeerror-make-sure-the-graphviz-executables-are-on-your-systems-path-aft">here for more details</a></li> |
| <li>Install <code class="docutils literal"><span class="pre">Jupyter</span></code> by installing <a class="reference external" href="https://www.anaconda.com/download/">Anaconda for Python 2.7</a> |
| <strong>Note</strong> Do not install Anaconda for Python 3.5. MXNet has a few compatibility issues with Python 3.5.</li> |
| </ul> |
| <p>We have installed MXNet core library. Next, we will install MXNet interface package for programming language of your choice:</p> |
| <ul class="simple"> |
| <li><a class="reference external" href="#install-the-mxnet-package-for-python">Python</a></li> |
| <li><a class="reference external" href="#install-mxnet-package-for-r">R</a></li> |
| <li><a class="reference external" href="#install-the-mxnet-package-for-julia">Julia</a></li> |
| <li><strong>Scala</strong> is not yet available for Windows</li> |
| </ul> |
| </div> |
| <div class="section" id="install-the-mxnet-package-for-python"> |
| <span id="install-the-mxnet-package-for-python"></span><h2>Install the MXNet Package for Python<a class="headerlink" href="#install-the-mxnet-package-for-python" title="Permalink to this headline">¶</a></h2> |
| <p>These steps are required after building from source. If you already installed MXNet by using pip, you do not need to do these steps to use MXNet with Python.</p> |
| <ol class="simple"> |
| <li>Install <code class="docutils literal"><span class="pre">Python</span></code> using windows installer available <a class="reference external" href="https://www.python.org/downloads/release/python-2712/">here</a>.</li> |
| <li>Install <code class="docutils literal"><span class="pre">Numpy</span></code> using windows installer available <a class="reference external" href="https://scipy.org/index.html">here</a>.</li> |
| <li>Start <code class="docutils literal"><span class="pre">cmd</span></code> and create a folder named <code class="docutils literal"><span class="pre">common</span></code>(<code class="docutils literal"><span class="pre">mkdir</span> <span class="pre">C:\common</span></code>)</li> |
| <li>Download the <a class="reference external" href="https://sourceforge.net/projects/openblas/files/v0.2.12/mingw64_dll.zip/download">mingw64_dll.zip</a>, unzip and copy three libraries (.dll files) that openblas.dll depends on to <code class="docutils literal"><span class="pre">C:\common</span></code>.</li> |
| <li>Copy the required .dll file to <code class="docutils literal"><span class="pre">C:\common</span></code> and make sure following libraries (.dll files) in the folder.</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">libgcc_s_seh</span><span class="o">-</span><span class="mf">1.</span><span class="n">dll</span> <span class="p">(</span><span class="ow">in</span> <span class="n">mingw64_dll</span><span class="p">)</span> |
| <span class="n">libgfortran</span><span class="o">-</span><span class="mf">3.</span><span class="n">dll</span> <span class="p">(</span><span class="ow">in</span> <span class="n">mingw64_dll</span><span class="p">)</span> |
| <span class="n">libquadmath</span><span class="o">-</span><span class="mf">0.</span><span class="n">dll</span> <span class="p">(</span><span class="ow">in</span> <span class="n">mingw64_dll</span><span class="p">)</span> |
| <span class="n">libopenblas</span><span class="o">.</span><span class="n">dll</span> <span class="p">(</span><span class="ow">in</span> <span class="n">OpenBlas</span> <span class="n">folder</span> <span class="n">you</span> <span class="n">download</span><span class="p">)</span> |
| <span class="n">opencv_world341</span><span class="o">.</span><span class="n">dll</span> <span class="p">(</span><span class="ow">in</span> <span class="n">OpenCV</span> <span class="n">folder</span> <span class="n">you</span> <span class="n">download</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Add <code class="docutils literal"><span class="pre">C:\common</span></code> to Environment Variables.</li> |
| </ol> |
| <ul class="simple"> |
| <li>Type <code class="docutils literal"><span class="pre">control</span> <span class="pre">sysdm.cpl</span></code> on <code class="docutils literal"><span class="pre">cmp</span></code></li> |
| <li>Select the <strong>Advanced tab</strong> and click <strong>Environment Variables</strong></li> |
| <li>Double click the <strong>Path</strong> and click <strong>New</strong></li> |
| <li>Add <code class="docutils literal"><span class="pre">C:\common</span></code> and click OK</li> |
| </ul> |
| <ol class="simple"> |
| <li>Use setup.py to install the package.</li> |
| </ol> |
| <div class="highlight-bash"><div class="highlight"><pre><span></span> <span class="c1"># Assuming you are in root mxnet source code folder</span> |
| <span class="nb">cd</span> python |
| python setup.py install |
| </pre></div> |
| </div> |
| <p>Done! We have installed MXNet with Python interface.</p> |
| <p>You can continue with using MXNet-Python, or if you want to try a different language API for MXNet, keep reading. Otherwise, jump ahead to <a class="reference external" href="#next-steps">next steps</a>.</p> |
| </div> |
| <div class="section" id="install-the-mxnet-package-for-r"> |
| <span id="install-the-mxnet-package-for-r"></span><h2>Install the MXNet Package for R<a class="headerlink" href="#install-the-mxnet-package-for-r" title="Permalink to this headline">¶</a></h2> |
| <p>MXNet for R is available for both CPUs and GPUs.</p> |
| <div class="section" id="installing-mxnet-r-on-a-computer-with-a-cpu-processor"> |
| <span id="installing-mxnet-r-on-a-computer-with-a-cpu-processor"></span><h3>Installing MXNet-R on a Computer with a CPU Processor<a class="headerlink" href="#installing-mxnet-r-on-a-computer-with-a-cpu-processor" title="Permalink to this headline">¶</a></h3> |
| <p>To install MXNet on a computer with a CPU processor, choose from two options:</p> |
| <ul class="simple"> |
| <li>Use the prebuilt binary package</li> |
| <li>Build the library from source code</li> |
| </ul> |
| <div class="section" id="installing-mxnet-r-with-the-prebuilt-binary-package-cpu"> |
| <span id="installing-mxnet-r-with-the-prebuilt-binary-package-cpu"></span><h4>Installing MXNet-R with the Prebuilt Binary Package(CPU)<a class="headerlink" href="#installing-mxnet-r-with-the-prebuilt-binary-package-cpu" title="Permalink to this headline">¶</a></h4> |
| <p>For Windows users, MXNet provides prebuilt binary packages. |
| You can install the package directly in the R console.</p> |
| <p>For CPU-only package:</p> |
| <div class="highlight-r"><div class="highlight"><pre><span></span> <span class="n">cran</span> <span class="o"><-</span> <span class="nf">getOption</span><span class="p">(</span><span class="s">"repos"</span><span class="p">)</span> |
| <span class="n">cran[</span><span class="s">"dmlc"</span><span class="n">]</span> <span class="o"><-</span> <span class="s">"https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/R/CRAN/"</span> |
| <span class="nf">options</span><span class="p">(</span><span class="n">repos</span> <span class="o">=</span> <span class="n">cran</span><span class="p">)</span> |
| <span class="nf">install.packages</span><span class="p">(</span><span class="s">"mxnet"</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <div class="section" id="building-mxnet-r-from-source-code-cpu"> |
| <span id="building-mxnet-r-from-source-code-cpu"></span><h4>Building MXNet-R from Source Code(CPU)<a class="headerlink" href="#building-mxnet-r-from-source-code-cpu" title="Permalink to this headline">¶</a></h4> |
| <ol class="simple"> |
| <li>Clone the MXNet github repo.</li> |
| </ol> |
| <div class="highlight-sh"><div class="highlight"><pre><span></span>git clone --recursive https://github.com/apache/incubator-mxnet |
| </pre></div> |
| </div> |
| <p>The <code class="docutils literal"><span class="pre">--recursive</span></code> is to clone all the submodules used by MXNet. You will be editing the <code class="docutils literal"><span class="pre">"/mxnet/R-package"</span></code> folder.</p> |
| <ol class="simple"> |
| <li>Download prebuilt GPU-enabled MXNet libraries for Windows from <a class="reference external" href="https://github.com/yajiedesign/mxnet/releases">Windows release</a>. You will need <code class="docutils literal"><span class="pre">mxnet_x64_vc14_cpu.7z</span></code> and <code class="docutils literal"><span class="pre">prebuildbase_win10_x64_vc14.7z</span></code> where X stands for your CUDA toolkit version</li> |
| <li>Create a folder called <code class="docutils literal"><span class="pre">R-package/inst/libs/x64</span></code>. MXNet supports only 64-bit operating systems, so you need the x64 folder.</li> |
| <li>Copy the following shared libraries (.dll files) into the <code class="docutils literal"><span class="pre">R-package/inst/libs/x64</span></code> folder:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">libgcc_s_seh</span><span class="o">-</span><span class="mf">1.</span><span class="n">dll</span> |
| <span class="n">libgfortran</span><span class="o">-</span><span class="mf">3.</span><span class="n">dll</span> |
| <span class="n">libmxnet</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">libmxnet</span><span class="o">.</span><span class="n">lib</span> |
| <span class="n">libopenblas</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">libquadmath</span><span class="o">-</span><span class="mf">0.</span><span class="n">dll</span> |
| <span class="n">mxnet</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">unzip</span><span class="o">.</span><span class="n">exe</span> |
| <span class="n">unzip32</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">vcomp140</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">wget</span><span class="o">.</span><span class="n">exe</span> |
| </pre></div> |
| </div> |
| <p>These dlls can be found in <code class="docutils literal"><span class="pre">prebuildbase_win10_x64_vc14/3rdparty</span></code>, <code class="docutils literal"><span class="pre">mxnet_x64_vc14_cpu/build</span></code>, <code class="docutils literal"><span class="pre">mxnet_x64_vc14_cpu/lib</span></code>.</p> |
| <ol class="simple"> |
| <li>Copy the header files from <code class="docutils literal"><span class="pre">dmlc</span></code>, <code class="docutils literal"><span class="pre">mxnet</span></code>, <code class="docutils literal"><span class="pre">mxshadow</span></code> and <code class="docutils literal"><span class="pre">nnvm</span></code> from mxnet_x64_vc14_cpu/include and mxnet_x64_vc14_cpu/nvnm/include into <code class="docutils literal"><span class="pre">./R-package/inst/include</span></code>. It should look like:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span>./R-package/inst |
| └── include |
| ├── dmlc |
| ├── mxnet |
| ├── mshadow |
| └── nnvm |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Make sure that R executable is added to your <code class="docutils literal"><span class="pre">PATH</span></code> in the environment variables. Running the <code class="docutils literal"><span class="pre">where</span> <span class="pre">R</span></code> command at the command prompt should return the location.</li> |
| <li>Also make sure that Rtools is installed and the executable is added to your <code class="docutils literal"><span class="pre">PATH</span></code> in the environment variables.</li> |
| <li>Temporary patch - im2rec currently results in crashes during the build. Remove the im2rec.h and im2rec.cc files in R-package/src/ from cloned repository and comment out the two im2rec lines in <a class="reference external" href="https://github.com/apache/incubator-mxnet/blob/master/R-package/src/mxnet.cc">R-package/src/mxnet.cc</a> as shown below.</li> |
| </ol> |
| <div class="highlight-bat"><div class="highlight"><pre><span></span>#include <span class="s2">"./kvstore.h"</span> |
| #include <span class="s2">"./export.h"</span> |
| //#include <span class="s2">"./im2rec.h"</span> |
| ...... |
| ...... |
| DataIterCreateFunction::InitRcppModule(); |
| KVStore::InitRcppModule(); |
| Exporter::InitRcppModule(); |
| // IM2REC::InitRcppModule(); |
| } |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Now open the Windows CMD with admin rights and change the directory to the <code class="docutils literal"><span class="pre">mxnet</span></code> folder(cloned repository). Then use the following commands |
| to build R package:</li> |
| </ol> |
| <div class="highlight-bat"><div class="highlight"><pre><span></span><span class="k">echo</span> import(Rcpp) <span class="p">></span> R-package\NAMESPACE |
| <span class="k">echo</span> import(methods) <span class="p">>></span> R-package\NAMESPACE |
| Rscript -e <span class="s2">"install.packages('devtools', repos = 'https://cloud.r-project.org')"</span> |
| <span class="k">cd</span> R-package |
| Rscript -e <span class="s2">"library(devtools); library(methods); options(repos=c(CRAN='https://cloud.r-project.org')); install_deps(dependencies = TRUE)"</span> |
| <span class="k">cd</span> .. |
| |
| R CMD INSTALL --no-multiarch R-package |
| |
| Rscript -e <span class="s2">"require(mxnet); mxnet:::mxnet.export('R-package')"</span> |
| rm R-package/NAMESPACE |
| Rscript -e <span class="s2">"require(devtools); install_version('roxygen2', version = '5.0.1', repos = 'https://cloud.r-project.org/', quiet = TRUE)"</span> |
| Rscript -e <span class="s2">"require(roxygen2); roxygen2::roxygenise('R-package')"</span> |
| |
| R CMD INSTALL --build --no-multiarch R-package |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="installing-mxnet-r-on-a-computer-with-a-gpu-processor"> |
| <span id="installing-mxnet-r-on-a-computer-with-a-gpu-processor"></span><h3>Installing MXNet-R on a Computer with a GPU Processor<a class="headerlink" href="#installing-mxnet-r-on-a-computer-with-a-gpu-processor" title="Permalink to this headline">¶</a></h3> |
| <p>To install MXNet on a computer with a GPU processor, choose from two options:</p> |
| <ul class="simple"> |
| <li>Use the prebuilt binary package</li> |
| <li>Build the library from source code</li> |
| </ul> |
| <p>However, a few dependencies remain for both options. You will need the following:</p> |
| <ul class="simple"> |
| <li>Install <a class="reference external" href="http://www.nvidia.com/Download/index.aspx?lang=en-us">Nvidia-drivers</a> if not installed. Latest driver based on your system configuration is recommended.</li> |
| <li>Install <a class="reference external" href="https://visualstudio.microsoft.com/downloads/">Microsoft Visual Studio</a> (VS2015 or VS2017 is required by CUDA)</li> |
| <li>Install <a class="reference external" href="https://developer.nvidia.com/cuda-toolkit">NVidia CUDA Toolkit</a>(cu92 is recommended though we support cu80, cu90, cu91 and cu92)</li> |
| <li>Download and install <a class="reference external" href="https://developer.nvidia.com/cudnn">CuDNN</a> (to provide a Deep Neural Network library). Latest version recommended.</li> |
| </ul> |
| <p>Note: A pre-requisite to above softwares is <a class="reference external" href="http://www.nvidia.com/Download/index.aspx?lang=en-us">Nvidia-drivers</a> which we assume is installed.</p> |
| <div class="section" id="installing-mxnet-r-with-the-prebuilt-binary-package-gpu"> |
| <span id="installing-mxnet-r-with-the-prebuilt-binary-package-gpu"></span><h4>Installing MXNet-R with the Prebuilt Binary Package(GPU)<a class="headerlink" href="#installing-mxnet-r-with-the-prebuilt-binary-package-gpu" title="Permalink to this headline">¶</a></h4> |
| <p>For Windows users, MXNet provides prebuilt binary packages. |
| You can install the package directly in the R console after you have the above software installed.</p> |
| <p>For GPU package:</p> |
| <div class="highlight-r"><div class="highlight"><pre><span></span> <span class="n">cran</span> <span class="o"><-</span> <span class="nf">getOption</span><span class="p">(</span><span class="s">"repos"</span><span class="p">)</span> |
| <span class="n">cran[</span><span class="s">"dmlc"</span><span class="n">]</span> <span class="o"><-</span> <span class="s">"https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/R/CRAN/GPU/cu92"</span> |
| <span class="nf">options</span><span class="p">(</span><span class="n">repos</span> <span class="o">=</span> <span class="n">cran</span><span class="p">)</span> |
| <span class="nf">install.packages</span><span class="p">(</span><span class="s">"mxnet"</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Change cu92 to cu80, cu90 or cu91 based on your CUDA toolkit version. Currently, MXNet supports these versions of CUDA.</p> |
| </div> |
| <div class="section" id="building-mxnet-r-from-source-code-gpu"> |
| <span id="building-mxnet-r-from-source-code-gpu"></span><h4>Building MXNet-R from Source Code(GPU)<a class="headerlink" href="#building-mxnet-r-from-source-code-gpu" title="Permalink to this headline">¶</a></h4> |
| <p>After you have installed above software, continue with the following steps to build MXNet-R:</p> |
| <ol class="simple"> |
| <li>Clone the MXNet github repo.</li> |
| </ol> |
| <div class="highlight-sh"><div class="highlight"><pre><span></span>git clone --recursive https://github.com/apache/incubator-mxnet |
| </pre></div> |
| </div> |
| <p>The <code class="docutils literal"><span class="pre">--recursive</span></code> is to clone all the submodules used by MXNet. You will be editing the <code class="docutils literal"><span class="pre">"/mxnet/R-package"</span></code> folder.</p> |
| <ol class="simple"> |
| <li>Download prebuilt GPU-enabled MXNet libraries for Windows from https://github.com/yajiedesign/mxnet/releases. You will need <code class="docutils literal"><span class="pre">mxnet_x64_vc14_gpu_cuX.7z</span></code> and <code class="docutils literal"><span class="pre">prebuildbase_win10_x64_vc14.7z</span></code> where X stands for your CUDA toolkit version</li> |
| <li>Create a folder called <code class="docutils literal"><span class="pre">R-package/inst/libs/x64</span></code>. MXNet supports only 64-bit operating systems, so you need the x64 folder.</li> |
| <li>Copy the following shared libraries (.dll files) into the <code class="docutils literal"><span class="pre">R-package/inst/libs/x64</span></code> folder:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">libgcc_s_seh</span><span class="o">-</span><span class="mf">1.</span><span class="n">dll</span> |
| <span class="n">libgfortran</span><span class="o">-</span><span class="mf">3.</span><span class="n">dll</span> |
| <span class="n">libmxnet</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">libmxnet</span><span class="o">.</span><span class="n">lib</span> |
| <span class="n">libopenblas</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">libquadmath</span><span class="o">-</span><span class="mf">0.</span><span class="n">dll</span> |
| <span class="n">mxnet</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">unzip</span><span class="o">.</span><span class="n">exe</span> |
| <span class="n">unzip32</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">vcomp140</span><span class="o">.</span><span class="n">dll</span> |
| <span class="n">wget</span><span class="o">.</span><span class="n">exe</span> |
| </pre></div> |
| </div> |
| <p>These dlls can be found in <code class="docutils literal"><span class="pre">prebuildbase_win10_x64_vc14/3rdparty</span></code>, <code class="docutils literal"><span class="pre">mxnet_x64_vc14_gpu_cuX/build</span></code>, <code class="docutils literal"><span class="pre">mxnet_x64_vc14_gpu_cuX/lib</span></code>.</p> |
| <ol class="simple"> |
| <li>Copy the header files from <code class="docutils literal"><span class="pre">dmlc</span></code>, <code class="docutils literal"><span class="pre">mxnet</span></code>, <code class="docutils literal"><span class="pre">mxshadow</span></code> and <code class="docutils literal"><span class="pre">nnvm</span></code> from mxnet_x64_vc14_gpuX/include and mxnet_x64_vc14_gpuX/nvnm/include into <code class="docutils literal"><span class="pre">./R-package/inst/include</span></code>. It should look like:</li> |
| </ol> |
| <div class="highlight-default"><div class="highlight"><pre><span></span>./R-package/inst |
| └── include |
| ├── dmlc |
| ├── mxnet |
| ├── mshadow |
| └── nnvm |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Make sure that R executable is added to your <code class="docutils literal"><span class="pre">PATH</span></code> in the environment variables. Running the <code class="docutils literal"><span class="pre">where</span> <span class="pre">R</span></code> command at the command prompt should return the location.</li> |
| <li>Also make sure that Rtools is installed and the executable is added to your <code class="docutils literal"><span class="pre">PATH</span></code> in the environment variables.</li> |
| <li>Temporary patch - im2rec currently results in crashes during the build. Remove the im2rec.h and im2rec.cc files in R-package/src/ from cloned repository and comment out the two im2rec lines in <a class="reference external" href="https://github.com/apache/incubator-mxnet/blob/master/R-package/src/mxnet.cc">R-package/src/mxnet.cc</a> as shown below.</li> |
| </ol> |
| <div class="highlight-bat"><div class="highlight"><pre><span></span>#include <span class="s2">"./kvstore.h"</span> |
| #include <span class="s2">"./export.h"</span> |
| //#include <span class="s2">"./im2rec.h"</span> |
| ...... |
| ...... |
| DataIterCreateFunction::InitRcppModule(); |
| KVStore::InitRcppModule(); |
| Exporter::InitRcppModule(); |
| // IM2REC::InitRcppModule(); |
| } |
| </pre></div> |
| </div> |
| <ol class="simple"> |
| <li>Now open the Windows CMD with admin rights and change the directory to the <code class="docutils literal"><span class="pre">mxnet</span></code> folder(cloned repository). Then use the following commands |
| to build R package:</li> |
| </ol> |
| <div class="highlight-bat"><div class="highlight"><pre><span></span><span class="k">echo</span> import(Rcpp) <span class="p">></span> R-package\NAMESPACE |
| <span class="k">echo</span> import(methods) <span class="p">>></span> R-package\NAMESPACE |
| Rscript -e <span class="s2">"install.packages('devtools', repos = 'https://cloud.r-project.org')"</span> |
| <span class="k">cd</span> R-package |
| Rscript -e <span class="s2">"library(devtools); library(methods); options(repos=c(CRAN='https://cloud.r-project.org')); install_deps(dependencies = TRUE)"</span> |
| <span class="k">cd</span> .. |
| |
| R CMD INSTALL --no-multiarch R-package |
| |
| Rscript -e <span class="s2">"require(mxnet); mxnet:::mxnet.export('R-package')"</span> |
| rm R-package/NAMESPACE |
| Rscript -e <span class="s2">"require(devtools); install_version('roxygen2', version = '5.0.1', repos = 'https://cloud.r-project.org/', quiet = TRUE)"</span> |
| Rscript -e <span class="s2">"require(roxygen2); roxygen2::roxygenise('R-package')"</span> |
| |
| R CMD INSTALL --build --no-multiarch R-package |
| </pre></div> |
| </div> |
| <p><strong>Note:</strong> To maximize its portability, the MXNet library is built with the Rcpp end. Computers running Windows need <a class="reference external" href="https://en.wikipedia.org/wiki/Visual_C%2B%2B">MSVC</a> (Microsoft Visual C++) to handle CUDA toolchain compatibilities.</p> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="install-the-mxnet-package-for-julia"> |
| <span id="install-the-mxnet-package-for-julia"></span><h2>Install the MXNet Package for Julia<a class="headerlink" href="#install-the-mxnet-package-for-julia" title="Permalink to this headline">¶</a></h2> |
| <p>The MXNet package for Julia is hosted in a separate repository, MXNet.jl, which is available on <a class="reference external" href="https://github.com/dmlc/MXNet.jl">GitHub</a>. To use Julia binding it with an existing libmxnet installation, set the <code class="docutils literal"><span class="pre">MXNET_HOME</span></code> environment variable by running the following command:</p> |
| <div class="highlight-bash"><div class="highlight"><pre><span></span><span class="nb">export</span> <span class="nv">MXNET_HOME</span><span class="o">=</span>/<path to>/libmxnet |
| </pre></div> |
| </div> |
| <p>The path to the existing libmxnet installation should be the root directory of libmxnet. In other words, you should be able to find the <code class="docutils literal"><span class="pre">libmxnet.so</span></code> file at <code class="docutils literal"><span class="pre">$MXNET_HOME/lib</span></code>. For example, if the root directory of libmxnet is <code class="docutils literal"><span class="pre">~</span></code>, you would run the following command:</p> |
| <div class="highlight-bash"><div class="highlight"><pre><span></span> <span class="nb">export</span> <span class="nv">MXNET_HOME</span><span class="o">=</span>/~/libmxnet |
| </pre></div> |
| </div> |
| <p>You might want to add this command to your <code class="docutils literal"><span class="pre">~/.bashrc</span></code> file. If you do, you can install the Julia package in the Julia console using the following command:</p> |
| <div class="highlight-julia"><div class="highlight"><pre><span></span> <span class="n">Pkg</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s">"MXNet"</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>For more details about installing and using MXNet with Julia, see the <a class="reference external" href="http://dmlc.ml/MXNet.jl/latest/user-guide/install/">MXNet Julia documentation</a>.</p> |
| </div> |
| <div class="section" id="installing-the-mxnet-package-for-scala"> |
| <span id="installing-the-mxnet-package-for-scala"></span><h2>Installing the MXNet Package for Scala<a class="headerlink" href="#installing-the-mxnet-package-for-scala" title="Permalink to this headline">¶</a></h2> |
| <p>MXNet-Scala is not yet available for Windows.</p> |
| </div> |
| <div class="section" id="next-steps"> |
| <span id="next-steps"></span><h2>Next Steps<a class="headerlink" href="#next-steps" title="Permalink to this headline">¶</a></h2> |
| <div class="toctree-wrapper compound"> |
| <ul> |
| <li class="toctree-l1"><a class="reference external" href="/versions/1.4.1/tutorials/index.html">Tutorials</a></li> |
| <li class="toctree-l1"><a class="reference external" href="/versions/1.4.1/faq/index.html">How To</a></li> |
| <li class="toctree-l1"><a class="reference external" href="/versions/1.4.1/architecture/index.html">Architecture</a></li> |
| </ul> |
| </div> |
| </div> |
| </div> |
| |
| |
| </div> |
| </div> |
| |
| <div class="sphinxsidebar rightsidebar" role="navigation" aria-label="main navigation"> |
| <div class="sphinxsidebarwrapper"> |
| <h3><a href="../index.html">Table Of Contents</a></h3> |
| <ul> |
| <li><a class="reference internal" href="#">Installing MXNet on Windows</a><ul> |
| <li><a class="reference internal" href="#prerequisites">Prerequisites</a><ul> |
| <li><a class="reference internal" href="#minimum-system-requirements">Minimum System Requirements</a></li> |
| <li><a class="reference internal" href="#recommended-system-requirements">Recommended System Requirements</a></li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#install-mxnet-with-python">Install MXNet with Python</a><ul> |
| <li><a class="reference internal" href="#install-with-cpus">Install with CPUs</a></li> |
| <li><a class="reference internal" href="#install-with-intel-cpus">Install with Intel CPUs</a></li> |
| <li><a class="reference internal" href="#install-with-nvidia-gpus">Install with NVIDIA GPUs</a><ul> |
| <li><a class="reference internal" href="#install-with-cuda-support">Install with CUDA Support</a></li> |
| <li><a class="reference internal" href="#install-with-cuda-and-mkl-support">Install with CUDA and MKL Support</a></li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#notes-on-the-python-packages">Notes on the Python Packages</a></li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#build-from-source">Build from Source</a></li> |
| <li><a class="reference internal" href="#install-the-mxnet-package-for-python">Install the MXNet Package for Python</a></li> |
| <li><a class="reference internal" href="#install-the-mxnet-package-for-r">Install the MXNet Package for R</a><ul> |
| <li><a class="reference internal" href="#installing-mxnet-r-on-a-computer-with-a-cpu-processor">Installing MXNet-R on a Computer with a CPU Processor</a><ul> |
| <li><a class="reference internal" href="#installing-mxnet-r-with-the-prebuilt-binary-package-cpu">Installing MXNet-R with the Prebuilt Binary Package(CPU)</a></li> |
| <li><a class="reference internal" href="#building-mxnet-r-from-source-code-cpu">Building MXNet-R from Source Code(CPU)</a></li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#installing-mxnet-r-on-a-computer-with-a-gpu-processor">Installing MXNet-R on a Computer with a GPU Processor</a><ul> |
| <li><a class="reference internal" href="#installing-mxnet-r-with-the-prebuilt-binary-package-gpu">Installing MXNet-R with the Prebuilt Binary Package(GPU)</a></li> |
| <li><a class="reference internal" href="#building-mxnet-r-from-source-code-gpu">Building MXNet-R from Source Code(GPU)</a></li> |
| </ul> |
| </li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#install-the-mxnet-package-for-julia">Install the MXNet Package for Julia</a></li> |
| <li><a class="reference internal" href="#installing-the-mxnet-package-for-scala">Installing the MXNet Package for Scala</a></li> |
| <li><a class="reference internal" href="#next-steps">Next Steps</a></li> |
| </ul> |
| </li> |
| </ul> |
| |
| </div> |
| </div> |
| </div><div class="footer"> |
| <div class="section-disclaimer"> |
| <div class="container"> |
| <div> |
| <img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/apache_incubator_logo.png" height=60> |
| <p> |
| Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), <strong>sponsored by the <i>Apache Incubator</i></strong>. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF. |
| </p> |
| <p> |
| "Copyright © 2017-2018, The Apache Software Foundation |
| Apache MXNet, MXNet, Apache, the Apache feather, and the Apache MXNet project logo are either registered trademarks or trademarks of the Apache Software Foundation." |
| </p> |
| </div> |
| </div> |
| </div> |
| </div> <!-- pagename != index --> |
| </div> |
| |
| <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js" integrity="sha384-0mSbJDEHialfmuBBQP6A4Qrprq5OVfW37PRR3j5ELqxss1yVqOtnepnHVP9aJ7xS" crossorigin="anonymous"></script> |
| <script type="text/javascript" src="../_static/js/sidebar.js"></script> |
| <script type="text/javascript" src="../_static/js/search.js"></script> |
| <script type="text/javascript" src="../_static/js/navbar.js"></script> |
| <script type="text/javascript" src="../_static/js/clipboard.min.js"></script> |
| <script type="text/javascript" src="../_static/js/copycode.js"></script> |
| <script type="text/javascript" src="../_static/js/page.js"></script> |
| <script type="text/javascript" src="../_static/js/docversion.js"></script> |
| <script type="text/javascript"> |
| $('body').ready(function () { |
| $('body').css('visibility', 'visible'); |
| }); |
| </script> |
| </body> |
| </html> |
