107 lines
4.8 KiB
C++
107 lines
4.8 KiB
C++
/**
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* @file build_windows.hpp
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* @author German Lancioni
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@page build_windows Building mlpack From Source on Windows
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@section build_windows_intro Introduction
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This document discusses how to build mlpack for Windows from source, so you can
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later create your own C++ applications. There are a couple of other tutorials
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for Windows, but they may be out of date:
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* <a href="https://github.com/mlpack/mlpack/wiki/WindowsBuild">Github wiki Windows Build page</a>
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* <a href="http://keon.io/mlpack-on-windows">Keon's tutorial for mlpack 2.0.3</a>
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* <a href="https://overdosedblog.wordpress.com/2016/08/15/once_again/">Kirizaki's tutorial for mlpack 2</a>
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Those guides could be used in addition to this tutorial.
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@section build_windows_env Environment
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This tutorial has been designed and tested using:
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- Windows 10
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- Visual Studio 2017 (toolset v141)
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- mlpack-3.0.3
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- OpenBLAS.0.2.14.1
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- boost_1_66_0-msvc-14.1-64
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- armadillo-8.500.1
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- and x64 configuration
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The directories and paths used in this tutorial are just for reference purposes.
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@section build_windows_prereqs Pre-requisites
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- Install CMake for Windows (win64-x64 version from https://cmake.org/download/)
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and make sure you can use it from the Command Prompt (may need to add to the PATH)
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- Download the latest mlpack release from here:
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<a href="http://www.mlpack.org/download.html">mlpack</a>
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@section build_windows_instructions Windows build instructions
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- Unzip mlpack to "C:\mlpack\mlpack-3.0.3"
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- Open Visual Studio and select: File > New > Project from Existing Code
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- Type of project: Visual C++
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- Project location: "C:\mlpack\mlpack-3.0.3"
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- Project name: mlpack
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- Finish
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- We will use this Visual Studio project to get the OpenBLAS dependency in the next section
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@section build_windows_dependencies Dependencies
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<b> OpenBLAS Dependency </b>
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- Open the NuGet packages manager (Tools > NuGet Package Manager > Manage NuGet Packages for Solution...)
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- Click on the “Browse” tab and search for “openblas”
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- Click on OpenBlas and check the mlpack project, then click Install
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- Once it has finished installing, close Visual Studio
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<b> Boost Dependency </b>
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You can either get Boost via NuGet or you can download the prebuilt Windows binaries separately.
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This tutorial follows the second approach for simplicity.
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- Download the "Prebuilt Windows binaries" of the Boost library ("boost_1_66_0-msvc-14.1-64") from
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<a href="https://sourceforge.net/projects/boost/files/boost-binaries/">Sourceforge</a>
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@note Make sure you download the MSVC version that matches your Visual Studio
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- Install or unzip to "C:\boost\boost_1_66_0"
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<b> Armadillo Dependency </b>
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- Download "Armadillo" (armadillo-8.500.1.tar.xz) from <a href="http://arma.sourceforge.net/download.html">Sourceforge</a>
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- Unzip to "C:\mlpack\armadillo-8.500.1"
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- Create a "build" directory into "C:\mlpack\armadillo-8.500.1\"
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- Open the Command Prompt and navigate to "C:\mlpack\armadillo-8.500.1\build"
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- Run cmake:
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@code
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cmake -G "Visual Studio 15 2017 Win64" -DBLAS_LIBRARY:FILEPATH="C:/mlpack/mlpack-3.0.3/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" -DLAPACK_LIBRARY:FILEPATH="C:/mlpack/mlpack-3.0.3/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" -DCMAKE_PREFIX:FILEPATH="C:/mlpack/armadillo" -DBUILD_SHARED_LIBS=OFF ..
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@endcode
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@note If you are using different directory paths, a different configuration (e.g. Release)
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or a different VS version, update the cmake command accordingly.
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- Once it has successfully finished, open "C:\mlpack\armadillo-8.500.1\build\armadillo.sln"
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- Build > Build Solution
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- Once it has successfully finished, close Visual Studio
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@section build_windows_mlpack Building mlpack
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- Create a "build" directory into "C:\mlpack\mlpack-3.0.3\"
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- Open the Command Prompt and navigate to "C:\mlpack\mlpack-3.0.3\build"
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- Run cmake:
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@code
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cmake -G "Visual Studio 15 2017 Win64" -DBLAS_LIBRARY:FILEPATH="C:/mlpack/mlpack-3.0.3/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" -DLAPACK_LIBRARY:FILEPATH="C:/mlpack/mlpack-3.0.3/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" -DARMADILLO_INCLUDE_DIR="C:/mlpack/armadillo-8.500.1/include" -DARMADILLO_LIBRARY:FILEPATH="C:/mlpack/armadillo-8.500.1/build/Debug/armadillo.lib" -DBOOST_INCLUDEDIR:PATH="C:/boost/boost_1_66_0/" -DBOOST_LIBRARYDIR:PATH="C:/boost/boost_1_66_0/lib64-msvc-14.1" -DDEBUG=OFF -DPROFILE=OFF ..
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@endcode
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- Once it has successfully finished, open "C:\mlpack\mlpack-3.0.3\build\mlpack.sln"
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- Build > Build Solution (this may be by default in Debug mode)
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- Once it has sucessfully finished, you will find the library files you need in: "C:\mlpack\mlpack-3.0.3\build\Debug" (or "C:\mlpack\mlpack-3.0.3\build\Release" if you changed to Release mode)
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You are ready to create your first application, take a look at the @ref sample_ml_app "Sample C++ ML App"
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*/
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