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Machine Learning Build Machine Setup for Windows (simple)

These instructions are an alternative to the "from scratch" instructions in windows.md.

This setup relies on pre-built 3rd party components previously built by the "from scratch" instructions and uploaded to s3. However, you get a fully working dev environment for ml-cpp.

Operating system

64 bit Windows is required.

It is possible to build on Windows Server 2012r2, Windows Server 2016 and Windows 10. Other versions may encounter problems.

Base requirements

Follow the instructions (only!) for Windows 8 SDK and Git for Windows from windows.md.

Microsoft C++ build tools

Download "Build Tools for Visual Studio 2017" from https://www.visualstudio.com/downloads/#build-tools-for-visual-studio-2017 and run it.

Clone ml-cpp

The github repository contains a script to download the remaining dependencies, therefore it is best to clone ml-cpp to your preferred location. Afterwards execute the powershell script from: dev-tools\download_windows_deps.ps1.

Environment

Create a .bashrc similar to that recommended in windows.md, but with a couple of extra environment variables. The build system lets you define VCBASE and WINSDKBASE to point it to the right compiler and SDK. In addition you have to put the directories into PATH as well. This is how it could look:

export VCBASE=PROGRA~2/MICROS~2/2017/BUILDT~1
export WINSDKBASE=PROGRA~2/WI3CF2~1

export CPP_SRC_HOME=$HOME/ml-cpp
VCVER=`/bin/ls -1 /c/$VCBASE/VC/Tools/MSVC | tail -1`
VCBINDIR=/c/$VCBASE/VC/Tools/MSVC/$VCVER/bin/HostX64/x64:/c/$VCBASE/Common7/IDE:/c/$WINSDKBASE/8.0/bin/x64:/c/$WINSDKBASE/8.0/bin/x86:/c/$VCBASE/TEAMTO~1/PERFOR~1/x64:/c/$VCBASE/TEAMTO~1/PERFOR~1
export JAVA_HOME=/c/PROGRA~1/Java/jdk1.8.0_121
export PATH="$CPP_SRC_HOME/build/distribution/platform/windows-x86_64/bin:$VCBINDIR:/mingw64/bin:$JAVA_HOME/bin:/c/usr/local/bin:/c/usr/local/lib:/bin:/c/Windows/System32:/c/Windows"
alias make=gnumake