aaronmarkham commented on a change in pull request #12504: [WIP] replacing windows setup with newer instructions URL: https://github.com/apache/incubator-mxnet/pull/12504#discussion_r217131383
########## File path: docs/install/windows_setup.md ########## @@ -1,64 +1,94 @@ # Installing MXNet in Windows -On Windows, you can download and install the prebuilt MXNet package, or download, build, and install MXNet yourself. +We provide two options to build and install MXNet yourself using [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/) or [Microsoft Visual Studio 2015](https://www.visualstudio.com/vs/older-downloads/). -## Build the Shared Library -You can either use a prebuilt binary package or build from source to build the MXNet shared library - ```libmxnet.dll```. +You can also install MXNet with the following programming language support: +- [Python](#install-the-mxnet-package-for-python) +- [R](#install-mxnet-package-for-r) +- [Julia](#install-the-mxnet-package-for-julia) -### Installing the Prebuilt Package on Windows -MXNet provides a prebuilt package for Windows. The prebuilt package includes the MXNet library, all of the dependent third-party libraries, a sample C++ solution for Visual Studio, and the Python installation script. To install the prebuilt package: -1. Download the latest prebuilt package from the [Releases](https://github.com/dmlc/mxnet/releases) tab of MXNet. -2. Unpack the package into a folder, with an appropriate name, such as ```D:\MXNet```. -3. Open the folder, and install the package by double-clicking ```setupenv.cmd```. This sets up all of the environment variables required by MXNet. -4. Test the installation by opening the provided sample C++ Visual Studio solution and building it. +**Option 1: Build with Visual Studio 2017** +To build and install MXNet yourself using [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/), you need the following dependencies. Install the required dependencies: - -This produces a library called ```libmxnet.dll```. +1. If [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/) is not already installed, download and install it. You can download and install the free community edition. +2. Download and install [CMake](https://cmake.org/files/v3.11/cmake-3.11.0-rc4-win64-x64.msi) if it is not already installed. +3. Download and install [OpenCV](https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.4.1/opencv-3.4.1-vc14_vc15.exe/download). +4. Unzip the OpenCV package. +5. Set the environment variable ```OpenCV_DIR``` to point to the ```OpenCV build directory``` (e.g., ```OpenCV_DIR = C:\utils\opencv\build```). +6. If you don’t have the Intel Math Kernel Library (MKL) installed, download and install [OpenBlas](https://sourceforge.net/projects/openblas/files/v0.2.20/OpenBLAS%200.2.20%20version.zip/download). +7. Set the environment variable ```OpenBLAS_HOME``` to point to the ```OpenBLAS``` directory that contains the ```include``` and ```lib``` directories (e.g., ```OpenBLAS_HOME = C:\utils\OpenBLAS```). +8. Download and install CUDA: Install [CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal), and Download the base installer (e.g., ```cuda_9.1.85_win10.exe```). +9. Download and install cuDNN. To get access to the download link, register as an NVIDIA community user. Then Follow the [link](http://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows) to install the cuDNN. +10. Download and install [git](https://git-for-windows.github.io/). -### Building and Installing Packages on Windows +After you have installed all of the required dependencies, build the MXNet source code: -To build and install MXNet yourself, you need the following dependencies. Install the required dependencies: +1. Start ```cmd``` in windows. +2. Download the MXNet source code from GitHub by using following command: -1. If [Microsoft Visual Studio 2015](https://www.visualstudio.com/vs/older-downloads/) is not already installed, download and install it. You can download and install the free community edition. -2. Download and Install [CMake](https://cmake.org/) if it is not already installed. -3. Download and install [OpenCV](http://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.0.0/opencv-3.0.0.exe/download). -4. Unzip the OpenCV package. -5. Set the environment variable ```OpenCV_DIR``` to point to the ```OpenCV build directory``` (```C:\opencv\build\x64\vc14``` for example). Also, you need to add the OpenCV bin directory (```C:\opencv\build\x64\vc14\bin``` for example) to the ``PATH`` variable. -6. If you have Intel Math Kernel Library (MKL) installed, set ```MKL_ROOT``` to point to ```MKL``` directory that contains the ```include``` and ```lib```. Typically, you can find the directory in -```C:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2018\windows\mkl```. -7. If you don't have the Intel Math Kernel Library (MKL) installed, download and install [OpenBlas](http://sourceforge.net/projects/openblas/files/v0.2.14/). -8. Set the environment variable ```OpenBLAS_HOME``` to point to the ```OpenBLAS``` directory that contains the ```include``` and ```lib``` directories. Typically, you can find the directory in ```C:\Program files (x86)\OpenBLAS\```. -9. Download and install [CuDNN](https://developer.nvidia.com/cudnn). To get access to the download link, register as an NVIDIA community user. +``` +cd C:\ +git clone https://github.com/apache/incubator-mxnet.git --recursive +``` -After you have installed all of the required dependencies, build the MXNet source code: +3. Follow [this link](https://docs.microsoft.com/en-us/visualstudio/install/modify-visual-studio) to modify ```Individual components```, and check ```VC++ 2017 version 15.4 v14.11 toolset```, and click ```Modify```. +4. 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): Review comment: This should be changed to setting on the command prompt after vs install. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
