# **Compile on Windows from Source Code**

## Environment preparation

* **Windows 7/8/10 Pro/Enterprise(64bit)**
    * **GPU Version support CUDA 9.0/9.1/9.2/10.0/10.1, and only support single GPU**
* **Python version 2.7.15+/3.5.1+/3.6/3.7(64bit)**
* **pip version 9.0.1+(64bit)**
* **Visual Studio 2015 Update3**

## Choose CPU/GPU

* If your computer doesn't have NVIDIA® GPU, please install CPU version of PaddlePaddle

* If your computer has NVIDIA® GPU, and the following conditions are met，GPU version of PaddlePaddle is recommended.
    * **CUDA toolkit 9.0/9.1/9.2/10.0/10.1 with cuDNN v7.3+**
    * **GPU's computing capability exceeds 1.0**

## Installation steps

There is one compilation methods in Windows system:

* Direct native source code compilation(NCCL, distributed and other related functions are not supported temporarily)

<a name="win_source"></a>
### ***Direct native source code compilation***

**Please strictly follow the following instructions step by step**

1. Install the necessary tools i.e. cmake, git and python:

    > Cmake requires version 3.5 and above, which can be downloaded from the [official website](https://cmake.org/download/) and added to the environment variable. 

    > Python requires version 2.7 and above,  which can be downloaded from the [official website](https://www.python.org/download/releases/2.7/).

        * After installing python, please check whether the python version is the expected version by `python-version`, because you may have more than one python installed on your computer. You can handle conflicts of multiple pythons by changing the order of the environment variables.

    > `numpy, protobuf, wheel` are needed to be installed. Use the 'pip' command.

        * To Install numpy package you can use command `pip install numpy`

        * To Install protobuf package you can use command `pip install protobuf`

        * To Install Wheel package you can use command `pip install wheel`

    > Git can be downloaded on the [official website](https://gitforwindows.org/) and added to the environment variable. 

2. Clone the PaddlePaddle source code to the Paddle subdirectories of the current directory and go to the Paddle subdirectories:

    - `git clone https://github.com/PaddlePaddle/Paddle.git`
    - `cd Paddle`

3. Switch to a more stable release branch for compilation:

    `git checkout [name of the branch]`

    For example：

    `git checkout release/1.7`

    Note: python3.6、python3.7 version started supporting from release/1.2

4. Create a directory called build and enter it:

    - `mkdir build`
    - `cd build`

5. Execute cmake:

    > For details on the compilation options, see [the compilation options list](../Tables.html/#Compile).
    * For users who need to compile **the CPU version PaddlePaddle**:

    `cmake .. -G "Visual Studio 14 2015 Win64" -DWITH_GPU=OFF -DWITH_TESTING=OFF -DCMAKE_BUILD_TYPE=Release`

    * For users who need to compile **the GPU version PaddlePaddle**:

    `cmake .. -G "Visual Studio 14 2015 Win64" -DWITH_GPU=ON -DWITH_TESTING=OFF -DCMAKE_BUILD_TYPE=Release`

    Python2 by default，Python3 please add：

    > -DPY_VERSION=3 (or 3.5、3.6、3.7)

    If your device information contains multiple Python or CUDA, you can also specify a specific version of Python or CUDA by setting the corresponding compile options:

    > -DPYTHON_EXECUTABLE: the installation path of python

    > -DCUDA_TOOLKIT_ROOT_DIR: the installation path of CUDA

    For example: (for instance only, please set it according to your actual installation path)

    `cmake .. -G "Visual Studio 14 2015 Win64" -DCMAKE_BUILD_TYPE=Release -DWITH_GPU=ON -DWITH_TESTING=OFF -DPYTHON_EXECUTABLE=C:\\Python36\\python.exe -DCUDA_TOOLKIT_ROOT_DIR="C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\v10.0"`

6. Use Blend for Visual Studio 2015 to open `paddle.sln` file, select the platform `x64`, configure with `Release`, then begin to compile

7. After compilation successfully, go to the `\paddle\build\python\dist` directory and find the generated `.whl` package:

    `cd \paddle\build\python\dist`

8. Install the generated `.whl` package:

     `pip install -U (whl package name)`

Congratulations, you have completed the process of compiling PaddlePaddle successfully!

### ***Verify installation***

After the compilation and installation is completed, you can use `python` to enter the Python interface, input `import paddle.fluid as fluid` and then `fluid.install_check.run_check()` to verify that the installation was successful.

If `Your Paddle Fluid is installed succesfully!` appears, it means the compilation and installation was successful.


### ***How to uninstall***

Please use the following command to uninstall PaddlePaddle:

* ***CPU version of PaddlePaddle*** : `pip uninstall paddlepaddle`

* ***GPU version of PaddlePaddle*** : `pip uninstall paddlepaddle-gpu`