JulianSlzr commented on a change in pull request #9353: added mac gpu install; refactored windows install URL: https://github.com/apache/incubator-mxnet/pull/9353#discussion_r160804449
########## File path: docs/install/index.md ########## @@ -938,15 +977,97 @@ Follow the installation instructions [in this guide](./osx_setup.md) to set up M </div> <div class="windows"> - <div class="python scala julia perl"> - <div class="gpu"> + <div class="python"> + <div class="cpu"> + <div class="pip"> +<br/> + +**Step 1** Install Python. + +[Anaconda](https://www.anaconda.com/download/) is recommended. + +**Step 2** Install *MXNet*. + +```bash +$ pip install mxnet +``` + +</div> +</div> + + <div class="gpu"> + +<div class="pip"> +<br/> + +**Step 1** Install Python. + +[Anaconda](https://www.anaconda.com/download/) is recommended. + +**Step 2** Install *MXNet* with GPU support using CUDA 9.0. + +```bash +$ pip install mxnet-cu90 +``` + +Refer to [#8671](https://github.com/apache/incubator-mxnet/issues/8671) for status on CUDA 9.1 support. + +</div> +<div class="build-from-source"> +<br/> +To build and install MXNet yourself, you need the following dependencies. Install the required dependencies: + +1. If [Microsoft Visual Studio 2015](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/) 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 [CUDA](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64) and [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/apache/incubator-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. +These commands produce a library called ```mxnet.dll``` in the ```./build/Release/``` or ```./build/Debug``` folder. + + + + +Next, we install ```graphviz``` library that we use for visualizing network graphs you build on MXNet. We will also install [Jupyter Notebook](http://jupyter.readthedocs.io/) used for running MXNet tutorials and examples. +- Install ```graphviz``` by downloading MSI installer from [Graphviz Download Page](https://graphviz.gitlab.io/_pages/Download/Download_windows.html). +**Note** Make sure to add graphviz executable path to PATH environment variable. Refer [here for more details](http://stackoverflow.com/questions/35064304/runtimeerror-make-sure-the-graphviz-executables-are-on-your-systems-path-aft) + Review comment: Definite articles! E.g., _the_ ```graphviz``` library, ... _the_ MSI installer, ... _the_ `graphviz` executable, ... _the_ `PATH` environment ---------------------------------------------------------------- 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: [email protected] With regards, Apache Git Services
