Compile on Windows from Source Code¶
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+/3.6/3.7/3.8(64bit)
pip version 20.2.2+(64bit)
Visual Studio 2015 Update3
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
There is one compilation methods in Windows system:
Direct native source code compilation(NCCL, distributed and other related functions are not supported temporarily)
Direct native source code compilation¶
Please strictly follow the following instructions step by step
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 and added to the environment variable.
Python requires version 2.7 and above, which can be downloaded from the official website.
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, wheelare 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 and added to the environment variable.
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
Switch to a more stable release branch for compilation:
git checkout [name of the branch]
git checkout release/1.8
Note: python3.6、python3.7 version started supporting from release/1.2, python3.8 version started supporting from release/1.8
Create a directory called build and enter it:
For details on the compilation options, see the compilation options list.
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、3.8)
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"
Use Blend for Visual Studio 2015 to open
paddle.slnfile, select the platform
x64, configure with
Release, then begin to compile
After compilation successfully, go to the
\paddle\build\python\distdirectory and find the generated
Install the generated
pip install -U (whl package name)
Congratulations, you have completed the process of compiling PaddlePaddle successfully!
After the compilation and installation is completed, you can use
python to enter the Python interface, input
import paddle.fluid as fluid
to verify that the installation was successful.
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