[GitHub] piiswrong closed pull request #8519: More details to the windows build process

[GitBox <gi...@apache.org>]

piiswrong closed pull request #8519: More details to the windows build process
URL: https://github.com/apache/incubator-mxnet/pull/8519
 
 
   

This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:

As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):

diff --git a/docs/install/windows_setup.md b/docs/install/windows_setup.md
index bf1673ac87..e5e92a7303 100755
--- a/docs/install/windows_setup.md
+++ b/docs/install/windows_setup.md
@@ -25,16 +25,28 @@ To build and install MXNet yourself, you need the following dependencies. Instal
 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```.
-6. 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/).
-7. 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\```.
-8. Download and install [CuDNN](https://developer.nvidia.com/cudnn). To get access to the download link, register as an NVIDIA community user.
+5. Set the environment variable ```OpenCV_DIR``` to point to the ```OpenCV build directory``` (```c:\utils\opencv\build``` for example).
+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.
 
 After you have installed all of the required dependencies, build the MXNet source code:
 
-1. Download the MXNet source code from [GitHub](https://github.com/dmlc/mxnet).
-2. Use [CMake](https://cmake.org/) to create a Visual Studio solution in ```./build```.
-3. In Visual Studio, open the solution file,```.sln```, and compile it.
+1. Download the MXNet source code from [GitHub](https://github.com/dmlc/mxnet). Don't forget to pull the submodules:
+```
+    git clone https://github.com/apache/incubator-mxnet.git ~/mxnet --recursive
+```
+2. Start a Visual Studio command prompt.
+3. Use [CMake](https://cmake.org/) to create a Visual Studio solution in ```./build``` or some other directory. Make sure to specify the architecture in the 
+[CMake](https://cmake.org/) command:
+```
+    mkdir build
+    cd build
+    cmake -G "Visual Studio 14 Win64" ..
+```
+4. In Visual Studio, open the solution file,```.sln```, and compile it.
 These commands produce a library called ```mxnet.dll``` in the ```./build/Release/``` or ```./build/Debug``` folder.
 
 


 

----------------------------------------------------------------
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:
users@infra.apache.org


With regards,
Apache Git Services