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Update and modify Windows docs #12620

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Update and modify Windows docs #12620

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5 changes: 3 additions & 2 deletions docs/install/windows_setup.md
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Expand Up @@ -77,6 +77,7 @@ When using supported NVIDIA GPU hardware, inference and training can be vastly f
The following steps will setup MXNet with CUDA. cuDNN can be enabled only when building from source.
1. Install [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/) or [Microsoft Visual Studio 2015](https://www.visualstudio.com/vs/older-downloads/).
1. Download and install [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal). CUDA versions 9.2 or 9.0 are recommended. Some [issues with CUDA 9.1](https://github.com/apache/incubator-mxnet/labels/CUDA) have been identified in the past.
1. Download and install [NVIDIA_CUDA_DNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows)
1. Install MXNet with CUDA support with pip:

```bash
Expand All @@ -93,6 +94,7 @@ The following steps will setup MXNet with CUDA and MKL.
1. Install [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/) or [Microsoft Visual Studio 2015](https://www.visualstudio.com/vs/older-downloads/).
1. Download and install [Intel MKL](https://software.intel.com/en-us/mkl/choose-download/windows) (registration required).
1. Download and install [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal).
1. Download and install [NVIDIA_CUDA_DNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows)
1. Install MXNet with MKL support with pip:

```bash
Expand Down Expand Up @@ -163,7 +165,6 @@ cd C:\build
```
cmake -G "Visual Studio 15 2017 Win64" -T cuda=9.2,host=x64 -DUSE_CUDA=1 -DUSE_CUDNN=1 -DUSE_NVRTC=1 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_BLAS=open -DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_LIST=Common -DCUDA_TOOLSET=9.2 -DCUDNN_INCLUDE=C:\cuda\include -DCUDNN_LIBRARY=C:\cuda\lib\x64\cudnn.lib "C:\incubator-mxnet"
```
**Note**: you may add to the cmake compilation options the compiler version to use with: `-T version=14.11`
6. After the CMake successfully completed, compile the the MXNet source code by using following command:
```
msbuild mxnet.sln /p:Configuration=Release;Platform=x64 /maxcpucount
Expand Down Expand Up @@ -216,7 +217,7 @@ These steps are required after building from source. If you already installed MX
```bash
# Assuming you are in root mxnet source code folder
cd python
sudo python setup.py install
python setup.py install
```

Done! We have installed MXNet with Python interface.
Expand Down