-
-

Build and Install

-
-

Requirement

-
-

Dependents

+
+

Installing from Sources

+
+

Download and Setup

+

You can download PaddlePaddle from the github source.

+
git clone https://github.com/baidu/Paddle paddle
+
+
-
-

Optional

-

PaddlePaddle also support some build options, you have to install related libraries.

+
+

Requirements

+

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

+
+

Dependencies

    -
  • WITH_GPU: Compile with gpu mode
      -
    • The GPU version works best with Cuda Toolkit 7.5 and cuDNN v5
    • -
    • Other versions Cuda Toolkit 6.5, 7.0 and cuDNN v2, v3, v4 are also supported
    • -
    • Note: to utilize cuDNN v5, Cuda Toolkit 7.5 is prerequisite and vice versa
    • +
    • 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
    -
  • -
  • WITH_DOUBLE: Compile with double precision, otherwise use single precision
  • -
  • WITH_GLOG: Compile with glog, otherwise use a log implement internally
  • -
  • WITH_GFLAGS: Compile with gflags, otherwise use a flag implement internally
  • -
  • WITH_TESTING: Compile with gtest and run unittest for PaddlePaddle
  • -
  • WITH_DOC: Compile with documentation
  • -
  • WITH_SWIG_PY: Compile with python predict api
  • -
  • WITH_STYLE_CHECK: Style check for source code
  • +
+
+

Options

+

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

+
Optional            | Description
+------------        | :-----------
+**WITH_GPU**        | Compile with GPU mode.
+**WITH_DOUBLE**     | Compile with double precision floating-point, default: single precision. |
+**WITH_GLOG**       | Compile with glog. If not found, default: an internal log implementation.
+**WITH_GFLAGS**     | Compile with gflags. If not found, default: an internal flag implementation.
+**WITH_TESTING**    | Compile with gtest for PaddlePaddle's unit testing. 
+**WITH_DOC**        | Compile to generate PaddlePaddle's docs, default: disabled (OFF).
+**WITH_SWIG_PY**    | Compile with python predict API, default: disabled (OFF).
+**WITH_STYLE_CHECK**| Compile with code style check, default: enabled (ON).
+
+
+

|

+

Note:

+
    +
  • 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. +
  3. 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`
    +
    +
    +
  4. +
-
-

Building on Ubuntu14.04

+
+

Build on Ubuntu 14.04

Install Dependencies

-
    -
  • CPU 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
    @@ -123,17 +169,19 @@ sudo cp *.a /usr/lib
     popd
     
    -
      -
    • GPU Dependencies(optional)
    • -
    -

    If you need to build GPU version, the first thing you need is a machine that has GPU and CUDA installed. -And you also need to install cuDNN.

    -

    You can download CUDA toolkit and cuDNN from nvidia website:

    -
    https://developer.nvidia.com/cuda-downloads
    -https://developer.nvidia.com/cudnn
    +
  • +
  • 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 http://developer.nvidia.com/cuda-downloads)
    +  4. NVIDIA cuDNN Library (availabel at https://developer.nvidia.com/cudnn)
     
    -

    You can copy cuDNN files into the CUDA toolkit directory, such as:

    +

    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*
     
    @@ -144,56 +192,170 @@ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* export PATH=/usr/local/cuda/bin:$PATH
-
    -
  • Python Dependencies(optional)
  • +
-

If you want to compile PaddlePaddle with python predict api, you need to add -DWITH_SWIG_PY=ON in cmake command and install these first:

-
sudo apt-get install swig
-
-
    -
  • Doc Dependencies(optional)
  • -
-

If you want to compile PaddlePaddle with doc, you need to add -DWITH_DOC=ON in cmake command and install these first:

-
pip install 'sphinx>=1.4.0'
-pip install sphinx_rtd_theme breathe recommonmark
-sudo apt-get install doxygen 
+
+

Build and Install

+

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

+
mkdir build && cd build
+cmake ..
 
-
-
-

Build and Install

-

CMake will find dependent libraries in system default paths first. After installing some optional libraries, corresponding build option will automatically be on(such as glog, gtest and gflags). And if libraries are not found, you have to set following variables manually in cmake command(CUDNN_ROOT, ATLAS_ROOT, MKL_ROOT, OPENBLAS_ROOT).

-

Here are some examples of cmake command with different options:

-

only cpu

-
cmake -DWITH_GPU=OFF -DWITH_DOC=OFF
+

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 -DWITH_DOC=OFF
     
    -

    gpu

    -
    cmake -DWITH_GPU=ON -DWITH_DOC=OFF
    +
  • +
  • GPU

    +
    cmake .. -DWITH_GPU=ON -DWITH_DOC=OFF
     
    -

    gpu with doc and swig

    -
    cmake -DWITH_GPU=ON -DWITH_DOC=ON -DWITH_SWIG_PY=ON
    +
  • +
  • GPU with doc and swig

    +
    cmake .. -DWITH_GPU=ON -DWITH_DOC=ON -DWITH_SWIG_PY=ON
     
    +
  • +

Finally, you can download source code and build:

-
git clone https://github.com/baidu/Paddle paddle
-cd paddle
-mkdir build
-cd build
-# you can add build option here, such as:    
-cmake -DWITH_GPU=ON -DWITH_DOC=OFF -DCMAKE_INSTALL_PREFIX=<path to install> ..
+
# you can add build option here, such as:    
+cmake .. -DWITH_GPU=ON -DWITH_DOC=OFF -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
-# PaddlePaddle installation path
+# set PaddlePaddle installation path in ~/.bashrc
 export PATH=<path to install>/bin:$PATH
 
-

Note

-

And if you set WITH_SWIG_PY=ON, you have to install related python predict api at the same time:

-
pip install <path to install>/opt/paddle/share/wheels/*.whl
+

Note:

+

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
+
+
+
+
+
+

Building on Mac OS X

+
+

Prerequisites

+

This guide is based on Mac OS X 10.11 (El Capitan). Note that if you are running an up to date version of OS X, +you will already have Python 2.7.10 and Numpy 1.8 installed.

+

The best option is to use the package manager homebrew to handle installations and upgrades for you. +To install homebrew, first open a terminal window (you can find Terminal in the Utilities folder in Applications), and issue the command:

+
# install brew
+/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
+# install pip
+easy_install pip
+
+
+
+
+

Install Dependencies

+
    +
  • CPU Dependencies

    +
    # Install fundamental dependents 
    +brew install glog gflags cmake protobuf openblas
    +
    +# Install google test on Mac OS X
    +# Download gtest 1.7.0
    +wget https://github.com/google/googletest/archive/release-1.7.0.tar.gz
    +tar -xvf googletest-release-1.7.0.tar.gz && cd googletest-release-1.7.0
    +# Build gtest
    +mkdir build && cmake ..
    +make
    +# Install gtest library
    +sudo cp -r ../include/gtest /usr/local/include/
    +sudo cp lib*.a /usr/local/lib
    +
    +
    +
  • +
  • GPU Dependencies(optional)

    +

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

    +
      1. a CUDA-capable GPU
    +  2. Mac OS X 10.11 or later
    +  2. the Clang compiler and toolchain installed using Xcode
    +  3. NVIDIA CUDA Toolkit (available at http://developer.nvidia.com/cuda-downloads)
    +  4. NVIDIA cuDNN Library (availabel at https://developer.nvidia.com/cudnn)
    +
    +
    +

    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.

    +
      +
    1. After downloading cuDNN library, issue the following commands:

      +
      sudo tar -xzf cudnn-7.5-osx-x64-v5.0-ga.tgz -C /usr/local
      +sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
      +
      +
      +
    2. +
    3. Then you need to set DYLD_LIBRARY_PATH, CUDA_HOME and PATH environment variables in ~/.bashrc.

      +
      export DYLD_LIBRARY_PATH=/usr/local/cuda/lib:$DYLD_LIBRARY_PATH
      +export PATH=/usr/local/cuda/bin:$PATH
      +
      +
      +
    4. +
    +
  • +
+
+
+

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 -DWITH_DOC=OFF
    +
    +
    +
  • +
  • GPU

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

    +
    cmake .. -DWITH_GPU=ON -DWITH_DOC=ON -DWITH_SWIG_PY=ON
    +
    +
    +
  • +
+

Finally, you can build PaddlePaddle:

+
# you can add build option here, such as:    
+cmake .. -DWITH_GPU=ON -DWITH_DOC=OFF -DCMAKE_INSTALL_PREFIX=<installation path>
+# 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=<installation path>/bin:$PATH
+
+
+

Note:

+

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
 
@@ -208,13 +370,20 @@ make -j `nproc`

Table Of Contents

    -
  • Build and Install
      -
    • Requirement
        -
      • Dependents
      • -
      • Optional
      • +
      • Installing from Sources
          +
        • Download and Setup
        • +
        • Requirements +
        • +
        • Build on Ubuntu 14.04
        • -
        • Building on Ubuntu14.04
            +
          • Building on Mac OS X diff --git a/doc/build/contribute_to_paddle.html b/doc/build/contribute_to_paddle.html index 0e13740646387c979aa7e2d8ed54b638814b4b30..5dc93d431c3e9442d96c495e3184e888df538a62 100644 --- a/doc/build/contribute_to_paddle.html +++ b/doc/build/contribute_to_paddle.html @@ -29,7 +29,7 @@ - + - +