Compile on Linux from Source Code

Environment preparation

  • Linux version (64 bit)

    • CentOS 6 (not recommended, no official support for compilation problems)

    • CentOS 7 (GPU version supports CUDA 10.1/10.2/11.0/11.1/11.2

    • Ubuntu 14.04 (not recommended, no official support for compilation problems)

    • Ubuntu 16.04 (GPU version supports CUDA 10.1/10.2/11.0/11.1/11.2)

    • Ubuntu 18.04 (GPU version supports CUDA 10.1/10.2/11.0/11.1/11.2)

  • Python version 3.6/3.7/3.8/3.9 (64 bit)

  • pip or pip3 version 20.2.2 or above (64 bit)

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 10.1/10.2 with cuDNN 7 (cuDNN version>=7.6.5, for multi card support, NCCL2.7 or higher)

    • CUDA toolkit 11.0 with cuDNN v8.0.4(for multi card support, NCCL2.7 or higher)

    • CUDA toolkit 11.1 with cuDNN v8.1.1(for multi card support, NCCL2.7 or higher)

    • CUDA toolkit 11.2 with cuDNN v8.1.1(for multi card support, NCCL2.7 or higher)

    • Hardware devices with GPU computing power over 3.5

      You can refer to NVIDIA official documents for installation process and configuration method of CUDA and cudnn. Please refer toCUDAcuDNN

    • If you need to use multi card environment, please make sure that you have installed nccl2 correctly, or install nccl2 according to the following instructions (here is the installation instructions of nccl2 under CUDA10.2 and cuDNN7. For more version of installation information, please refer to NVIDIAofficial website):

      • Centos system can refer to the following commands

        wget http://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
        
        rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
        
        yum update -y
        
        yum install -y libnccl-2.7.8-1+cuda10.2 libnccl-devel-2.7.8-1+cuda10.2 libnccl-static-2.7.8-1+cuda10.2
        
      • Ubuntu system can refer to the following commands

        wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb
        
        dpkg -i nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb
        
        sudo apt install -y libnccl2=2.7.8-1+cuda10.2 libnccl-dev=2.7.8-1+cuda10.2
        

Installation steps

There are two compilation methods under Linux system:

Compile with Docker

Docker is an open source application container engine. Using docker, you can not only isolate the installation and use of paddlepaddle from the system environment, but also share GPU, network and other resources with the host

Compiling PaddlePaddle with Docker,you need:

Please follow the steps below to install:

1. First select the path where you want to store PaddlePaddle, then use the following command to clone PaddlePaddle’s source code from github to a folder named Paddle in the local current directory:

git clone https://github.com/PaddlePaddle/Paddle.git

2. Go to the Paddle directory:

cd Paddle

3. Pull PaddlePaddle image:

For domestic users, when downloading docker is slow due to network problems, you can use the mirror provided by Baidu:

  • CPU version of PaddlePaddle:

    docker pull registry.baidubce.com/paddlepaddle/paddle:latest-dev
    
  • GPU version of PaddlePaddle:

    docker pull registry.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda10.2-cudnn7-dev
    

If your machine is not in mainland China, you can pull the image directly from DockerHub:

  • CPU version of PaddlePaddle:

    docker pull paddlepaddle/paddle:latest-dev
    
  • GPU version of PaddlePaddle:

    docker pull paddlepaddle/paddle:latest-gpu-cuda10.2-cudnn7-dev
    

In the above example, latest-gpu-cuda10.2-cudnn7-dev is only for illustration, indicating that the GPU version of the image is installed. If you want to install another cuda/cudnn version of the image, you can replace it with latest-dev-cuda11.2-cudnn8-gcc82, latest-gpu-cuda10.1-cudnn7-gcc82-dev, latest-gpu-cuda10.1-cudnn7-gcc54-dev etc.

You can see DockerHub to get the image that matches your machine.

4. Create and enter a Docker container that meets the compilation environment:

  • Compile CPU version of PaddlePaddle:

    docker run --name paddle-test -v $PWD:/paddle --network=host -it registry.baidubce.com/paddlepaddle/paddle:latest-dev /bin/bash
    
    • --name paddle-test: names the Docker container you created as paddle-test;

    • -v $PWD:/paddle: mount the current directory to the /paddle directory in the docker container (PWD variable in Linux will be expanded to absolute path of the current path);

    • -it: keeps interaction with the host;

    • registry.baidubce.com/paddlepaddle/paddle:latest-dev: use the image named registry.baidubce.com/paddlepaddle/paddle:latest-dev to create Docker container, /bin/bash start the /bin/bash command after entering the container.

  • Compile GPU version of PaddlePaddle:

    nvidia-docker run --name paddle-test -v $PWD:/paddle --network=host -it registry.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda10.2-cudnn7-dev /bin/bash
    
    • --name paddle-test: names the Docker container you created as paddle-test;

    • -v $PWD:/paddle: mount the current directory to the /paddle directory in the docker container (PWD variable in Linux will be expanded to absolute path of the current path);

    • -it: keeps interaction with the host;

    • registry.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda10.2-cudnn7-dev: use the image named registry.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda10.2-cudnn7-dev to create Docker container, /bin/bash start the /bin/bash command after entering the container.

5. After entering Docker, go to the paddle directory:

cd /paddle

6. Switch to a more stable version to compile:

git checkout [name of the branch]

For example:

git checkout release/2.2

Note: python3.6、python3.7 version started supporting from release/1.2 branch, python3.8 version started supporting from release/1.8 branch, python3.9 version started supporting from release/2.1 branch

7. Create and enter the /paddle/build path:

mkdir -p /paddle/build && cd /paddle/build

8. Use the following command to install the dependencies:

  • Install protobuf 3.1.0

pip3.7 install protobuf

Note: We used Python3.7 command as an example above, if the version of your Python is 3.6/3.8/3.9, please change pip3.7 in the commands to pip3.6/pip3.8/pip3.9

  • Installing patchelf, PatchELF is a small and useful program for modifying the dynamic linker and RPATH of ELF executables.

apt install patchelf

9. Execute cmake:

  • For users who need to compile the CPU version PaddlePaddle:

    cmake .. -DPY_VERSION=3.7 -DWITH_GPU=OFF -DWITH_TESTING=OFF -DCMAKE_BUILD_TYPE=Release
    
  • For users who need to compile the GPU version PaddlePaddle:

    cmake .. -DPY_VERSION=3.7 -DWITH_GPU=ON -DWITH_TESTING=OFF -DCMAKE_BUILD_TYPE=Release
    
  • For details on the compilation options, see the compilation options table.

  • Please attention to modify parameters -DPY_VERSION for the version of Python you want to compile with, for example -DPY_VERSION=3.7 means the version of python is 3.7

  • We currently do not support the compilation of the GPU version PaddlePaddle under CentOS 6.

10. Execute compilation:

Use multicore compilation

make -j$(nproc)

11. After compiling successfully, go to the /paddle/build/python/dist directory and find the generated .whl package:

cd /paddle/build/python/dist

12. Install the compiled .whl package on the current machine or target machine:

For Python3:

pip3.7 install -U [whl package name]

Note: We used Python3.7 command as an example above, if the version of your Python is 3.6/3.8/3.9, please change pip3.7 in the commands to pip3.6/pip3.8/pip3.9

Congratulations, now that you have successfully installed PaddlePaddle using Docker, you only need to run PaddlePaddle after entering the Docker container. For more Docker usage, please refer to the official Docker documentation.

Local compilation

1. Check that your computer and operating system meet the compilation standards we support:

uname -m && cat /etc/*release

2. Update the system source

  • Centos system

    Update the source of yum: yum update, and add the necessary yum source:

    yum install -y epel-release
    
  • Ubuntu system

    Update the source of apt:

    apt update
    

3. Install the necessary tools

  • Centos system

    bzip2 and make:

    yum install -y bzip2
    
    yum install -y make
    

    cmake requires version 3.15, we recommend that you use 3.16.0 version:

    wget -q https://cmake.org/files/v3.16/cmake-3.16.0-Linux-x86_64.tar.gz
    
    tar -zxvf cmake-3.16.0-Linux-x86_64.tar.gz
    
    rm cmake-3.16.0-Linux-x86_64.tar.gz
    
    PATH=/home/cmake-3.16.0-Linux-x86_64/bin:$PATH
    

    gcc requires version 4.8.2, we recommend that you use 8.2.0 version:

    wget -q https://paddle-docker-tar.bj.bcebos.com/home/users/tianshuo/bce-python-sdk-0.8.27/gcc-8.2.0.tar.xz && \
    tar -xvf gcc-8.2.0.tar.xz && \
    cd gcc-8.2.0 && \
    sed -i 's#ftp://gcc.gnu.org/pub/gcc/infrastructure/#https://paddle-ci.gz.bcebos.com/#g' ./contrib/download_prerequisites && \
    unset LIBRARY_PATH CPATH C_INCLUDE_PATH PKG_CONFIG_PATH CPLUS_INCLUDE_PATH INCLUDE && \
    ./contrib/download_prerequisites && \
    cd .. && mkdir temp_gcc82 && cd temp_gcc82 && \
    ../gcc-8.2.0/configure --prefix=/usr/local/gcc-8.2 --enable-threads=posix --disable-checking --disable-multilib && \
    make -j8 && make install
    
  • Ubuntu system

    bzip2 and make:

    apt install -y bzip2
    
    apt install -y make
    

    cmake requires version 3.15, we recommend that you use 3.16.0 version:

    wget -q https://cmake.org/files/v3.16/cmake-3.16.0-Linux-x86_64.tar.gz
    
    tar -zxvf cmake-3.16.0-Linux-x86_64.tar.gz
    
    rm cmake-3.16.0-Linux-x86_64.tar.gz
    
    PATH=/home/cmake-3.16.0-Linux-x86_64/bin:$PATH
    

    gcc requires version 4.8.2, we recommend that you use 8.2.0 version:

    wget -q https://paddle-docker-tar.bj.bcebos.com/home/users/tianshuo/bce-python-sdk-0.8.27/gcc-8.2.0.tar.xz && \
    tar -xvf gcc-8.2.0.tar.xz && \
    cd gcc-8.2.0 && \
    sed -i 's#ftp://gcc.gnu.org/pub/gcc/infrastructure/#https://paddle-ci.gz.bcebos.com/#g' ./contrib/download_prerequisites && \
    unset LIBRARY_PATH CPATH C_INCLUDE_PATH PKG_CONFIG_PATH CPLUS_INCLUDE_PATH INCLUDE && \
    ./contrib/download_prerequisites && \
    cd .. && mkdir temp_gcc82 && cd temp_gcc82 && \
    ../gcc-8.2.0/configure --prefix=/usr/local/gcc-8.2 --enable-threads=posix --disable-checking --disable-multilib && \
    make -j8 && make install
    

4. We support compiling and installing with virtualenv. First, create a virtual environment called paddle-venv with the following command:

  • a. Install Python-dev:

    (Please refer to the official Python installation process)

  • b. Install pip:

    (Please refer to the official Python installation process, and ensure that the pip3 version 20.2.2 and above, please note that in python3.6 and above, pip3 does not necessarily correspond to the python version, such as python3.7 default only Pip3.7)

  • c. (Only For Python3) set Python3 related environment variables, here is python3.7 version example, please replace with the version you use (3.6, 3.8, 3.9):

    1. First find the path to the Python lib using

      find `dirname $(dirname $(which python3))` -name "libpython3.so"
      

      If it is 3.6,3.7,3.8,3.9, change python3 to python3.6,python3.7, python3.8, python3.9, then replace [python-lib-path] in the following steps with the file path found.

    2. Set PYTHON_LIBRARIES:

      export PYTHON_LIBRARY=[python-lib-path]
      
    3. Secondly, use

      find `dirname $(dirname $(which python3))`/include -name "python3.7m"
      

      to find the path to Python Include, please pay attention to the python version, then replace the following [python-include-path] to the file path found.

    4. Set PYTHON_INCLUDE_DIR:

      export PYTHON_INCLUDE_DIRS=[python-include-path]
      
    5. Set the system environment variable path:

      export PATH=[python-lib-path]:$PATH
      

      (here replace the last two levels content of [python-lib-path] with /bin/)

  • d. Install the virtual environment virtualenv and virtualenvwrapper and create a virtual environment called paddle-venv: (please note the pip3 commands corresponding to the python version, such as pip3.6, pip3.7, pip3.8, pip3.9)

    1. Install virtualenv:

      pip install virtualenv
      

      or

      pip3 install virtualenv
      
    2. Install virtualenvwrapper

      Pip install virtualenvwrapper
      

      or

      pip3 install virtualenvwrapper
      
    3. Find virtualenvwrapper.sh:

      find / -name virtualenvwrapper.sh
      

      (please find the corresponding Python version of virtualenvwrapper.sh)

    4. See the installation method in virtualenvwrapper.sh:

      cat vitualenvwrapper.sh
      

      this shell file describes the steps and commands

    5. Install virtualwrapper as described in virtualenvwrapper.sh

    6. Set VIRTUALENVWRAPPER_PYTHON:

      export VIRTUALENVWRAPPER_PYTHON=[python-lib-path]:$PATH
      

      (here replace the last two levels content of [python-lib-path] with /bin/)

    7. Create virtual environment named paddle-venv:

      mkvirtualenv paddle-venv
      

5. Enter the virtual environment:

workon paddle-venv

7. Put the PaddlePaddle source cloned in the Paddle folder in the current directory and go to the Paddle directory:

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

8. Switch to a more stable release branch for compilation (support for Python 3.6 and 3.7 is added from the 1.2 branch, support for Python 3.8 is added from the 1.8 branch, support for Python 3.9 is added from the 2.1 branch,):

git checkout [name of target branch]

For example:

git checkout release/2.2

9. And please create and enter a directory called build:

mkdir build && cd build

10. Execute cmake:

For details on the compilation options, see the compilation options table.

  • For users who need to compile the CPU version PaddlePaddle:

    cmake .. -DPY_VERSION=3.7 -DPYTHON_INCLUDE_DIR=${PYTHON_INCLUDE_DIRS} \
    -DPYTHON_LIBRARY=${PYTHON_LIBRARY} -DWITH_GPU=OFF -DWITH_TESTING=OFF -DCMAKE_BUILD_TYPE=Release
    

    If you encounter Could NOT find PROTOBUF (missing: PROTOBUF_LIBRARY PROTOBUF_INCLUDE_DIR), you can re-execute the cmake command. Please note that the PY_VERSION parameter is replaced with the python version you need.

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

    1. Please make sure that you have installed nccl2 correctly, or install nccl2 according to the following instructions (here is ubuntu 16.04, CUDA10.2, cuDNN7 nccl2 installation instructions, for more information on the installation information please refer to the NVIDIA official website):

      wget http://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
      
      rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
      
      yum install -y libnccl-2.7.8-1+cuda10.2 libnccl-devel-2.7.8-1+cuda10.2 libnccl-static-2.7.8-1+cuda10.2
      
    2. If you have already installed nccl2 correctly, you can start cmake: (For Python3: Please configure the correct python version for the PY_VERSION parameter)

      cmake .. -DPYTHON_EXECUTABLE:FILEPATH=[您可执行的Python3的路径] -DPYTHON_INCLUDE_DIR:PATH=[之前的PYTHON_INCLUDE_DIRS] -DPYTHON_LIBRARY:FILEPATH=[之前的PYTHON_LIBRARY] -DWITH_GPU=ON -DWITH_TESTING=OFF -DCMAKE_BUILD_TYPE=Release
      

Note: For the command involving Python 3, we use Python 3.7 as an example above, if the version of your Python is 3.6/3.8/3.9, please change Python3.7 in the commands to Python3.6/Python3.8/Python3.9

11. Compile with the following command:

make -j$(nproc)

Use multicore compilation

If “Too many open files” error is displayed during compilation, please use the instruction ulimit -n 8192 to increase the number of files allowed to be opened by the current process. Generally speaking, 8192 can ensure the completion of compilation.

12. After compiling successfully, go to the /paddle/build/python/dist directory and find the generated .whl package:

cd /paddle/build/python/dist

13. Install the compiled .whl package on the current machine or target machine:

Pip install -U (whl package name)

or

pip3 install -U (whl package name)

Congratulations, now you have completed the process of compiling PaddlePaddle natively.



Verify installation

After the installation is complete, you can use python or python3 to enter the Python interpreter and then use

import paddle

and then

paddle.utils.run_check()

to verify that the installation was successful.

If PaddlePaddle is installed successfully! appears, it means the installation was successful.



How to uninstall

Please use the following command to uninstall PaddlePaddle (users who use Docker to install PaddlePaddle should use the following command in the container containing PaddlePaddle. Please use the corresponding version of pip):

  • CPU version of PaddlePaddle:

    pip uninstall paddlepaddle
    

    or

    pip3 uninstall paddlepaddle
    
  • GPU version of PaddlePaddle:

    pip uninstall paddlepaddle-gpu
    

    or

    pip3 uninstall paddlepaddle-gpu
    

Users installing PaddlePaddle with Docker, please use above commands in the container involved PaddlePaddle and attention to use the corresponding version of Pip