mlpack

Building mlpack from source on Windows

by German Lancioni, Miguel Canteras, Shikhar Jaiswal, Ziyang Jiang

This tutorial will show you how to build mlpack for Windows from source, so you can later create your own C++ applications, using two different ways:

Before you try building mlpack, you may want to install mlpack using vcpkg for Windows. If you don’t want to install using vcpkg, skip this section and continue with the build tutorial.

PS> .\vcpkg install mlpack:x64-windows

PS> .\vcpkg install mlpack[tools]:x64-windows

After installing, in Visual Studio, you can create a new project (or open an existing one). The library is immediately ready to be included (via preprocessor directives) and used in your project without additional configuration.

Note that when building mlpack, the /std:c++17 option is required for Visual Studio.

🔗 Build Environment

This tutorial has been designed and tested using:

The directories and paths used in this tutorial are just for reference purposes.

🔗 Pre-requisites

🔗 Windows build instructions

🔗 Dependencies

🔗 OpenBLAS Dependency

🔗 Building OpenBLAS from Source

Unfortunately, the support for building LAPACK and BLAS on Windows is quite poor, due to the need for Fortran compiler and libraries. The easiest method to get the necessary BLAS/LAPACK libraries built on Windows is to compile OpenBLAS with LLVM’s clang-cl and flang to produce the required static library (.lib) files compatible with the MSVC compiler. A comprehensive guide on the compilation of OpenBLAS for Windows can be found here.

One could always download prebuilt LAPACK and BLAS libraries for Windows. However, there are few official sources, and some of those libraries may require further dlls at runtime which may not be available in your system.

It you choose to build OpenBLAS from source, make sure that LAPACK functions are also built. Finally, make sure that the openblas.lib library is linked in your Armadillo build (see below), as well as the library path used for the CMake options BLAS_LIBRARIES and LAPACK_LIBRARIES in the mlpack CMake project.

🔗 Armadillo Dependency

cmake -G "Visual Studio 16 2019" -A x64 -DBLAS_LIBRARY:FILEPATH="C:/mlpack/mlpack/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" -DLAPACK_LIBRARY:FILEPATH="C:/mlpack/mlpack/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" ..

Note: If you are using different directory paths, a different configuration (e.g. Release) or a different VS version, update the cmake command accordingly. If CMake cannot identify the compiler version, check if the Visual Studio compiler and Windows SDK are installed correctly.

🔗 Building mlpack with CMake-generated Solution

cmake -G "Visual Studio 16 2019" -A x64 -DBLAS_LIBRARIES:FILEPATH="C:/mlpack/mlpack/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" -DLAPACK_LIBRARIES:FILEPATH="C:/mlpack/mlpack/packages/OpenBLAS.0.2.14.1/lib/native/lib/x64/libopenblas.dll.a" -DARMADILLO_INCLUDE_DIR="C:/mlpack/armadillo/include" -DARMADILLO_LIBRARY:FILEPATH="C:/mlpack/armadillo/build/Debug/armadillo.lib" -DDEBUG=OFF -DPROFILE=OFF ..

Note: CMake will attempt to automatically download the ensmallen dependency. If for some reason cmake can’t download the dependency, you will need to manually download ensmallen from http://ensmallen.org/ and extract it to C:\mlpack\mlpack\deps\. Then, specify the path to ensmallen using the flag: -DENSMALLEN_INCLUDE_DIR=C:/mlpack/mlpack/deps/ensmallen/include.

You are ready to create your first application; take a look at the Sample C++ ML App.

🔗 Building mlpack with Visual Studio’s CMake integration

This project can be directly built from the CMakeLists.txt with the latest version of MS Visual Studio, given you have CMake integration via the C++ CMake tools for Windows. To open the CMake project with Visual Studio, select File -> Open -> CMake in the top menu, followed by selecting the root CMakeLists.txt located in mlpack’s root directory.

In order to allow Visual Studio to configure the CMake project, the CMake configuration json will have to be edited to provide the relevant options shown in the README needed to find all the dependencies. The options that you must provide to Visual Studio’s CMake are:

The CMake configuration json can be edited in Visual Studio by right clicking the root CMakeLists.txt in the project view, selecting CMake settings for mlpack and finally clicking on edit JSON. Adding a new CMake option can be done by adding object fields with the following format to the variables array in the CMakeSettings.json:

{
    "name": "options_name_string",
    "value": "options_value_string",
    "type" : "{BOOL|FILEPATH|PATH|STRING}"
}

Here is a full example of the CMakeSettings.jsonfile:

{
  "configurations": [
    {
      "name": "x64-Debug (default)",
      "generator": "Ninja",
      "configurationType": "Debug",
      "inheritEnvironments": [ "msvc_x64_x64" ],
      "buildRoot": "${projectDir}\\out\\build\\${name}",
      "installRoot": "${projectDir}\\out\\install\\${name}",
      "cmakeCommandArgs": "",
      "buildCommandArgs": "",
      "ctestCommandArgs": "",
      "variables": [
        {
          "name": "ARMADILLO_INCLUDE_DIR",
          "value": "PATH/TO/CPP/DEPENDENCY/armadillo-10.1.2/include",
          "type": "PATH"
        },
        {
          "name": "ARMADILLO_LIBBRARY",
          "value": "PATH/TO/CPP/DEPENDENCY/armadillo-10.1.2/lib/armadillo.lib",
          "type": "PATH"
        },
        {
          "name": "CEREAL_INCLUDE_DIR",
          "value": "PATH/TO/CPP/DEPENDENCY/cereal-1.3.0/include",
          "type": "PATH"
        },
        {
          "name": "BLAS_LIBRARIES",
          "value": "PATH/TO/CPP/DEPENDENCY/OpenBLAS/lib/openblas.lib",
          "type": "PATH"
        },
        {
          "name": "LAPACK_LIBRARIES",
          "value": "PATH/TO/CPP/DEPENDENCY/OpenBLAS/lib/openblas.lib",
          "type": "PATH"
        }
      ]
    }
  ]
}

🔗 Appendix

If you prefer to use the CMake GUI, follow these instructions:

🔗 Additional information

If you are facing issues during the build process of mlpack, you may take a look at other third-party tutorials for Windows, but they may be out of date: