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2daa05c0
编写于
9月 20, 2016
作者:
L
liaogang
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add build on MAC OSX docs
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doc/build/build_from_source.md
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2daa05c0
Build and Install
Build and Install
=================
=================
## Requirement
*
[
1. Requirement
](
#Requirement
)
*
[
2. Build on Ubuntu
](
#ubuntu
)
*
[
3. Build on Mac OS X
](
#mac
)
## <span id="Requirement">Requirement</span>
### Dependents
### Dependents
...
@@ -28,7 +32,7 @@ PaddlePaddle also support some build options, you have to install related librar
...
@@ -28,7 +32,7 @@ PaddlePaddle also support some build options, you have to install related librar
-
**WITH_STYLE_CHECK**
: Style check for source code
-
**WITH_STYLE_CHECK**
: Style check for source code
##
Building on Ubuntu14.04
##
<span id="ubuntu">Building on Ubuntu14.04</span>
### Install Dependencies
### Install Dependencies
...
@@ -44,7 +48,7 @@ sudo apt-get install libgflags-dev
...
@@ -44,7 +48,7 @@ sudo apt-get install libgflags-dev
sudo
apt-get
install
libgtest-dev
sudo
apt-get
install
libgtest-dev
sudo
pip
install
wheel
sudo
pip
install
wheel
pushd
/usr/src/gtest
pushd
/usr/src/gtest
cmake
.
cmake .
.
make
make
sudo cp
*
.a /usr/lib
sudo cp
*
.a /usr/lib
popd
popd
...
@@ -102,19 +106,19 @@ Here are some examples of cmake command with different options:
...
@@ -102,19 +106,19 @@ Here are some examples of cmake command with different options:
**only cpu**
**only cpu**
```
bash
```
bash
cmake
-DWITH_GPU
=
OFF
-DWITH_DOC
=
OFF
cmake
-DWITH_GPU
=
OFF
-DWITH_DOC
=
OFF
..
```
```
**gpu**
**gpu**
```
bash
```
bash
cmake
-DWITH_GPU
=
ON
-DWITH_DOC
=
OFF
cmake
-DWITH_GPU
=
ON
-DWITH_DOC
=
OFF
..
```
```
**gpu with doc and swig**
**gpu with doc and swig**
```
bash
```
bash
cmake
-DWITH_GPU
=
ON
-DWITH_DOC
=
ON
-DWITH_SWIG_PY
=
ON
cmake
-DWITH_GPU
=
ON
-DWITH_DOC
=
ON
-DWITH_SWIG_PY
=
ON
..
```
```
Finally, you can download source code and build:
Finally, you can download source code and build:
...
@@ -139,3 +143,129 @@ And if you set WITH_SWIG_PY=ON, you have to install related python predict api a
...
@@ -139,3 +143,129 @@ And if you set WITH_SWIG_PY=ON, you have to install related python predict api a
```
bash
```
bash
pip
install
<path to
install
>
/opt/paddle/share/wheels/
*
.whl
pip
install
<path to
install
>
/opt/paddle/share/wheels/
*
.whl
```
```
## <span id="mac">Building on Mac OS X</span>
### 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:
```
bash
# 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**
```
bash
# 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)**
If you need to build GPU version, the first thing you need is a machine that has NVIDIA GPU and CUDA installed.
And you also need to install cuDNN.
You can download CUDA toolkit and cuDNN from nvidia website:
```
bash
https://developer.nvidia.com/cuda-downloads
https://developer.nvidia.com/cudnn
```
You can copy cuDNN files into the CUDA toolkit directory, for instance:
```
bash
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
*
```
Then you need to set DYLD
\_
LIBRARY
\_
PATH, CUDA
\_
HOME and PATH environment variables in ~/.bashrc.
```
bash
export
DYLD_LIBRARY_PATH
=
/usr/local/cuda/lib:
$DYLD_LIBRARY_PATH
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:
```
bash
brew
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:
```
bash
pip
install
'sphinx>=1.4.0'
pip
install
sphinx_rtd_theme breathe recommonmark
brew
install
doxygen
```
### Build and Install
CMake can find dependent libraries in system default paths firstly.
After installing some optional libraries, corresponding build option will be on automatically (for instance, glog, gtest and gflags).
If not found, you have to set following variables manually via CMake command (CUDNN_ROOT, ATLAS_ROOT, MKL_ROOT, OPENBLAS_ROOT).
Here are some examples of CMake command with different options:
**only cpu**
```
bash
cmake
-DWITH_GPU
=
OFF
-DWITH_DOC
=
OFF ..
```
**gpu**
```
bash
cmake
-DWITH_GPU
=
ON
-DWITH_DOC
=
OFF ..
```
**gpu with doc and swig**
```
bash
cmake
-DWITH_GPU
=
ON
-DWITH_DOC
=
ON
-DWITH_SWIG_PY
=
ON ..
```
Finally, you can download source code and build:
```
bash
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
>
..
# please use sudo make install, if you want
# to install PaddlePaddle into the system
make
-j
`
nproc
`
&&
make
install
# PaddlePaddle installation path
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:
```
bash
sudo
pip
install
<path to
install
>
/opt/paddle/share/wheels/
*
.whl
```
\ No newline at end of file
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