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Installation

Install PySINGA

PySINGA has been tested on Linux (Ubunu 14.04 and 16.04) and Mac OS (10.11).

Install dependent libraries

Python 2.7 is required to run PySINGA.

# For Ubuntu
$ sudo apt-get install python2.7-dev python-pip

# For Mac
$ brew tap homebrew/python
$ brew install python

Virtual environment

Users are recommended to use PySINGA in python virtual environment.

To use pip with virtual environment,

# install virtualenv
$ pip install virtualenv
$ virtualenv pysinga
$ source pysinga/bin/activate

To use anaconda with virtual environment,

$ conda create --name pysinga python=2
$ source activate pysinga

Note that in python virtual environment, you may need to reset the PYTHONPATH to empty to avoid the conflicts of system path and virtual environment path.

From wheel

Currently, we have three versions of wheel files,

# Ubuntu 14.04 64-bit, CPU only, Python 2.7
$ pip install --upgrade http://comp.nus.edu.sg/~dbsystem/singa/assets/file/ubuntu1404/singa-1.0.0-cp27-none-linux_x86_64.whl

# Ubuntu 14.04 64-bit, GPU enabled, Python 2.7, CUDA toolkit 7.5 and CuDNN v5
$ pip install --upgrade http://comp.nus.edu.sg/~dbsystem/singa/assets/file/ubuntu1404/cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl

# Mac OSX (10.11), CPU only, Python 2.7
$ pip install --upgrade http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6/singa-1.0.0-cp27-none-macosx_10_11_intel.whl

If you have sudo right, you can run the above commands using sudo pip install without python virtual environment. You can also download the .whl file and run pip install <the whl file directly>. The option --upgrade may cause errors sometimes, in which case you can ignore it.

From source

To build the PySINGA from source, the following dependent libraries are required,

  • swig(>=3.0.10)
  • numpy(>=1.11.0)

They can be installed by

$ Ubuntu 14.04 and 16.04
$ sudo apt-get install python-numpy
# Ubuntu 16.04
$ sudo apt-get install swig

Note that swig has to be installed from source on Ubuntu 14.04. After installing numpy, please export the header path of numpy.i as

$ export CPLUS_INCLUDE_PATH=`python -c "import numpy; print numpy.get_include()"`:$CPLUS_INCLUDE_PATH

Please compile SINGA from source (see the next section) with cmake -DUSE_PYTHON=ON -DUSE_MODULES=ON .., and then run the following commands,

# under the build directory
$ cd python
$ pip install .

Developers can build the wheel file via

# under the build directory
$ cd python
$ python setup.py bdist_wheel

The generated wheel file is under "dist" directory.

Build SINGA on Linux and Mac OS

The source files could be downloaded either as a tar.gz file, or as a git repo

$ git clone https://github.com/apache/incubator-singa.git
$ cd incubator-singa/

cmake (>=2.8) is used for compile SINGA, which can be installed by

# For Ubuntu 14.04 and 16.04
$ sudo apt-get install cmake

GCC (>=4.8.1) is required to compile SINGA on Linux. For Mac OS users, you can use either GCC or Clang.

Compile SINGA together with dependent libraries

SINGA code uses CBLAS and Protobuf (>=2.5, <3). If they are not installed in your OS, you can compile SINGA together with them

$ In SINGA ROOT folder
$ mkdir build
$ cd build
$ cmake -DUSE_MODULES=ON ..
$ make

cmake would download OpenBlas and Protobuf (2.6.1) and compile them together with SINGA.

Install dependent libraries and compile SINGA

Users can also install the dependent libraries and link SINGA with them.

The following libraries are required

  • google protobuf (>=2.5,<3)
  • blas (tested with openblas >=0.2.10)

The following libraries are optional

  • opencv (tested with 2.4.8)
  • lmdb (tested with 0.9)
  • glog

Most of the dependent libraries could be installed from source or via package mangers like apt-get, yum, and homebrew. Please refer to FAQ for problems caused by the path setting of the dependent libraries.

The following instructions are tested on Ubuntu 14.04 for installing dependent libraries.

# required libraries
$ sudo apt-get install libprotobuf-dev libopenblas-dev protobuf-compiler

# optional libraries
$ sudo apt-get install python2.7-dev python-pip python-numpy
$ sudo apt-get install libopencv-dev libgoogle-glog-dev liblmdb-dev

Please note that PySINGA requires swig >=3.0, which could be installed via apt-get on Ubuntu 16.04; but it has to be installed from source for other Ubuntu versions including 14.04.

The following instructions are tested on Mac OS X Yosemite (10.10.5) for installing dependent libraries.

# required libraries
$ brew tap homebrew/science
$ brew install openblas
$ brew install protobuf260

# optional libraries
$ brew tap homebrew/python
$ brew install python
$ brew install opencv
$ brew install -vd glog lmdb

By default, openblas is installed into /usr/local/opt/openblas. To let the compiler (and cmake) know the openblas path, please export

$ export CMAKE_INCLUDE_PATH=/usr/local/opt/openblas/include:$CMAKE_INCLUDE_PATH
$ export CMAKE_LIBRARY_PATH=/usr/local/opt/openblas/lib:$CMAKE_LIBRARY_PATH

To let the runtime know the openblas path, please export

$ export LD_LIBRARY_PATH=/usr/local/opt/openblas/library:$LD_LIBRARY_PATH

With the dependent libraries installed, SINGA can be compiled via

$ mkdir build
$ cd build
$ cmake ..
$ make
$ make install

After compiling SINGA, you can run the unit tests by

$ ./bin/test_singa

You can see all the testing cases with testing results. If SINGA passes all tests, then you have successfully installed SINGA. Please proceed to try the examples!

You can use ccmake .. to configure the compilation options. If some dependent libraries are not in the system default paths, you need to export the following environment variables

export CMAKE_INCLUDE_PATH=<path to the header file folder>
export CMAKE_LIBRARY_PATH=<path to the lib file folder>

Compile SINGA with CUDA and CUDNN

Users are encouraged to install the cuda and cudnn for running SINGA on GPUs to get better performance.

SINGA has been tested over CUDA (7 and 7.5), and CUDNN (4-5.1). If CUDNN is decompressed into non-system folder, e.g. /home/bob/local/cudnn/, the following commands should be executed for cmake and the runtime to find it

$ export CMAKE_INCLUDE_PATH=/home/bob/local/cudnn/include:$CMAKE_INCLUDE_PATH
$ export CMAKE_LIBRARY_PATH=/home/bob/local/cudnn/lib64:$CMAKE_LIBRARY_PATH
$ export LD_LIBRARY_PATH=/home/bob/local/cudnn/lib64:$LD_LIBRARY_PATH

The cmake options for CUDA and CUDNN should be switched on

# Dependent libs are install already
$ cmake -DUSE_CUDA=ON ..

# Compile dependent libs together with SINGA
$ cmake -DUSE_CUDA=ON -DUSE_MODULES=ON ..

Compile SINGA with OpenCL support (Linux)

SINGA uses opencl-headers and viennacl (version 1.7.1 or newer) for OpenCL support, which can be installed using via

# On Ubuntu 16.04
$ sudo apt-get install opencl-headers, libviennacl-dev
# On Fedora
$ sudo yum install opencl-headers, viennacl

Additionally, you will need the OpenCL Installable Client Driver (ICD) for the platforms that you want to run OpenCL on.

  • For AMD and nVidia GPUs, the driver package should also install the correct OpenCL ICD.
  • For Intel CPUs and/or GPUs, get the driver from the Intel website. Note that the drivers provided on that website only supports recent CPUs and Iris GPUs.
  • For older Intel CPUs, you can use the beignet-opencl-icd package.

Note that running OpenCL on CPUs is not currently recommended because it is slow. Memory transfer is on the order of whole seconds (1000's of ms on CPUs as compared to 1's of ms on GPUs).

More information on setting up a working OpenCL environment may be found here.

If the package version of ViennaCL is not at least 1.7.1, you will need to build it from source:

Clone the repository from here, checkout the release-1.7.1 tag and build it. Remember to add its directory to PATH and the built libraries to LD_LIBRARY_PATH.

To build SINGA with OpenCL support, you need to pass the flag during cmake:

cmake -DUSE_OPENCL=ON ..

Build SINGA on Windows

For the dependent library installation, please refer to Dependencies. After all the dependencies are successfully installed, just run the following commands to generate the VS solution in cmd under singa folder:

$ md build && cd build
$ cmake -G "Visual Studio 14" -DUSE_CUDA=OFF -DUSE_PYTHON=OFF ..

The default project generated by the command is 32-bit version. You can also specify a 64-bit version project by:

$ md build && cd build
$ cmake -G "Visual Studio 14 Win64" -DUSE_CUDA=OFF -DUSE_PYTHON=OFF ..

If you get error outputs like "Could NOT find xxxxx" indicating a dependent library missing, please configure your library file and include path for cmake or the system. For example, you get an error "Could NOT find CBLAS" and suppose you installed openblas header files at "d:\include" and openblas library at "d:\lib". You should run the following command to specify your cblas parameters in cmake:

$ cmake -G "Visual Studio 14" -DUSE_CUDA=OFF -DUSE_PYTHON=OFF -DCBLAS_INCLUDE_DIR="d:\include" -DCBLAS_LIBRARIES="d:\lib\libopenblas.lib" -DProtobuf_INCLUDE_DIR=<include dir of protobuf> -DProtobuf_LIBRARIES=<path to libprotobuf.lib> -DProtobuf_PROTOC_EXECUTABLE=<path to protoc.exe> -DGLOG_INCLUDE_DIR=<include dir of glog> -DGLOG_LIBRARIES=<path to libglog.lib> ..

To find out the parameters you need to specify for some special libraries, you can run the following command:

$ cmake -LAH

If you use cmake GUI tool in windows, please make sure you configure the right parameters for the singa solution by select "Advanced" box. After generating the VS project, please open the "singa.sln" project file under the "build" folder and compile it as a normal VS solution. You will find the unit tests file named "test_singa" in the project binary folder. If you get errors when running test_singa.exe due to libglog.dll/libopenblas.dll missing, please just copy the dll files into the same folder as test_singa.exe

FAQ

  • Q: Error from 'import singa' using PySINGA installed from wheel.

    A: Please check the detailed error from python -c "from singa import _singa_wrap". Sometimes it is caused by the dependent libraries, e.g. there are multiple versions of protobuf or missing of cudnn. Following steps show the solutions for different cases

    1. Check the cudnn and cuda and gcc versions, cudnn5 and cuda7.5 and gcc4.8/4.9 are preferred. if gcc is 5.0, then downgrade it. If cudnn is missing or not match with the wheel version, you can download the correct version of cudnn into ~/local/cudnn/ and 
      echo "export LD_LIBRARY_PATH=/home/<yourname>/local/cudnn/lib64:$LD_LIBRARY_PATH" >> ~/.bashrc
    2. If it is the problem related to protobuf, then please download the newest whl files which have compiled protobuf and openblas into the whl file of PySINGA. Or you can install protobuf from source into a local folder, say ~/local/; Decompress the tar file, and then 
      ./configure --prefix=/home/<yourname>local
make && make install
echo "export LD_LIBRARY_PATH=/home/<yourname>/local/lib:$LD_LIBRARY_PATH" >> ~/.bashrc
source ~/.bashrc
    3. If it cannot find other libs including python, then please create virtual env using pip or conda; and then install SINGA via 
      pip install --upgrade <url of singa wheel>

  • Q: Error from running cmake .., which cannot find the dependent libraries.

    A: If you haven't installed the libraries, please install them. If you installed the libraries in a folder that is outside of the system folder, e.g. /usr/local, please export the following variables

      export CMAKE_INCLUDE_PATH=<path to your header file folder>
  export CMAKE_LIBRARY_PATH=<path to your lib file folder>

  • Q: Error from make, e.g. the linking phase

    A: If your libraries are in other folders than system default paths, you need to export the following varaibles

    $ export LIBRARY_PATH= $ export LD_LIBRARY_PATH=

  • Q: Error from header files, e.g. 'cblas.h no such file or directory exists'

    A: You need to include the folder of the cblas.h into CPLUS_INCLUDE_PATH, e.g.,

      $ export CPLUS_INCLUDE_PATH=/opt/OpenBLAS/include:$CPLUS_INCLUDE_PATH

  • Q:While compiling SINGA, I get error SSE2 instruction set not enabled

    A:You can try following command:

      $ make CFLAGS='-msse2' CXXFLAGS='-msse2'

  • Q:I get ImportError: cannot import name enum_type_wrapper from google.protobuf.internal when I try to import .py files.

    A: You need to install the python binding of protobuf, which could be installed via

      $ sudo apt-get install protobuf

    or from source

      $ cd /PROTOBUF/SOURCE/FOLDER
  $ cd python
  $ python setup.py build
  $ python setup.py install

  • Q: When I build OpenBLAS from source, I am told that I need a Fortran compiler.

    A: You can compile OpenBLAS by

      $ make ONLY_CBLAS=1

    or install it using

      $ sudo apt-get install libopenblas-dev

  • Q: When I build protocol buffer, it reports that GLIBC++_3.4.20 not found in /usr/lib64/libstdc++.so.6.

    A: This means the linker found libstdc++.so.6 but that library belongs to an older version of GCC than was used to compile and link the program. The program depends on code defined in the newer libstdc++ that belongs to the newer version of GCC, so the linker must be told how to find the newer libstdc++ shared library. The simplest way to fix this is to find the correct libstdc++ and export it to LD_LIBRARY_PATH. For example, if GLIBC++_3.4.20 is listed in the output of the following command,

      $ strings /usr/local/lib64/libstdc++.so.6|grep GLIBC++

    then you just set your environment variable as

      $ export LD_LIBRARY_PATH=/usr/local/lib64:$LD_LIBRARY_PATH

  • Q: When I build glog, it reports that "src/logging_unittest.cc:83:20: error: ‘gflags’ is not a namespace-name"

    A: It maybe that you have installed gflags with a different namespace such as "google". so glog can't find 'gflags' namespace. Because it is not necessary to have gflags to build glog. So you can change the configure.ac file to ignore gflags.

      1. cd to glog src directory
  2. change line 125 of configure.ac  to "AC_CHECK_LIB(gflags, main, ac_cv_have_libgflags=0, ac_cv_have_libgflags=0)"
  3. autoreconf

    After this, you can build glog again.

  • Q: When using virtual environment, everytime I run pip install, it would reinstall numpy. However, the numpy would not be used when I import numpy

    A: It could be caused by the PYTHONPATH which should be set to empty when you are using virtual environment to avoid the conflicts with the path of the virtual environment.

  • Q: When compiling PySINGA from source, there is a compilation error due to the missing of <numpy/objectarray.h>

    A: Please install numpy and export the path of numpy header files as

      $ export CPLUS_INCLUDE_PATH=`python -c "import numpy; print numpy.get_include()"`:$CPLUS_INCLUDE_PATH