Installing from Sources

Download and Setup

You can download PaddlePaddle from the github source.

git clone paddle
cd paddle


To compile the source code, your computer must be equipped with GCC >=4.6 or Clang compiler.


  • CMake: version >= 2.8
  • BLAS: MKL, OpenBlas or ATLAS
  • protobuf: version >= 2.4, Note: 3.x is not supported
  • python: only python 2.7 is supported currently


PaddlePaddle supports some build options. To enable it, first you need to install the related libraries.

Optional Description
WITH_GPUCompile with GPU mode.
WITH_DOUBLECompile with double precision floating-point, default: single precision.
WITH_GLOGCompile with glog. If not found, default: an internal log implementation.
WITH_GFLAGSCompile with gflags. If not found, default: an internal flag implementation.
WITH_TESTINGCompile with gtest for PaddlePaddle's unit testing.
WITH_DOC Compile to generate PaddlePaddle's docs, default: disabled (OFF).
WITH_SWIG_PYCompile with python predict API, default: disabled (OFF).
WITH_STYLE_CHECKCompile with code style check, default: enabled (ON).


  • The GPU version works best with Cuda Toolkit 7.5 and cuDNN v5.
  • Other versions like Cuda Toolkit 6.5, 7.0, 8.0 and cuDNN v2, v3, v4 are also supported.
  • To utilize cuDNN v5, Cuda Toolkit 7.5 is prerequisite and vice versa.

As a simple example, consider the following:

  1. Python Dependencies(optional)

    To compile PaddlePaddle with python predict API, make sure swig installed and set -DWITH_SWIG_PY=ON as follows:

    # install swig on ubuntu
    sudo apt-get install swig
    # install swig on Mac OS X
    brew install swig
    # active swig in cmake
    cmake .. -DWITH_SWIG_PY=ON
  2. Doc Dependencies(optional)

    To generate PaddlePaddle’s documentation, install dependencies and set -DWITH_DOC=ON as follows:

    pip install 'sphinx>=1.4.0'
    pip install sphinx_rtd_theme breathe recommonmark
    # install doxygen on Ubuntu
    sudo apt-get install doxygen 
    # install doxygen on Mac OS X
    brew install doxygen
    # active docs in cmake
    cmake .. -DWITH_DOC=ON`

Build on Ubuntu 14.04

Install Dependencies

  • CPU Dependencies

    # necessary
    sudo apt-get update
    sudo apt-get install -y g++ make cmake build-essential libatlas-base-dev python python-pip libpython-dev m4 libprotobuf-dev protobuf-compiler python-protobuf python-numpy git
    # optional
    sudo apt-get install libgoogle-glog-dev
    sudo apt-get install libgflags-dev
    sudo apt-get install libgtest-dev
    sudo pip install wheel
    pushd /usr/src/gtest
    cmake .
    sudo cp *.a /usr/lib
  • GPU Dependencies (optional)

    To build GPU version, you will need the following installed:

      1. a CUDA-capable GPU
      2. A supported version of Linux with a gcc compiler and toolchain
      3. NVIDIA CUDA Toolkit (available at
      4. NVIDIA cuDNN Library (availabel at

    The CUDA development environment relies on tight integration with the host development environment, including the host compiler and C runtime libraries, and is therefore only supported on distribution versions that have been qualified for this CUDA Toolkit release.

    After downloading cuDNN library, issue the following commands:

    sudo tar -xzf cudnn-7.5-linux-x64-v5.1.tgz -C /usr/local
    sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

    Then you need to set LD_LIBRARY_PATH, PATH environment variables in ~/.bashrc.

    export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
    export PATH=/usr/local/cuda/bin:$PATH

Build and Install

As usual, the best option is to create build folder under paddle project directory.

mkdir build && cd build
cmake ..

CMake first check PaddlePaddle’s dependencies in system default path. After installing some optional libraries, corresponding build option will be set automatically (for instance, glog, gtest and gflags). If still not found, you can manually set it based on CMake error information from your screen.

As a simple example, consider the following:

  • Only CPU

    cmake  .. -DWITH_GPU=OFF
  • GPU

    cmake .. -DWITH_GPU=ON
  • GPU with doc and swig


Finally, you can build PaddlePaddle:

# you can add build option here, such as:    
cmake .. -DWITH_GPU=ON -DCMAKE_INSTALL_PREFIX=<path to install>
# please use sudo make install, if you want to install PaddlePaddle into the system
make -j `nproc` && make install
# set PaddlePaddle installation path in ~/.bashrc
export PATH=<path to install>/bin:$PATH


If you set WITH_SWIG_PY=ON, related python dependencies also need to be installed. Otherwise, PaddlePaddle will automatically install python dependencies at first time when user run paddle commands, such as paddle version, paddle train. It may require sudo privileges:

# you can run
sudo pip install <path to install>/opt/paddle/share/wheels/*.whl
# or just run 
sudo paddle version