PySINGA (the Python binding) has additional dependencies
Users are encouraged to install the cuda and cudnn for running SINGA on GPUs to get better performance. Most of the dependent libraries could be installed from source or via package mangers like apt-get, homebrew, pip and anaconda. 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 llibopencv-dev ibgoogle-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/library:$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
pip and anaconda could be used to install python packages, e.g. numpy. To use pip with virtual environment,
# install virtualenv $ pip install virtualenv $ virtualenv pysinga $ source pysinga/bin/activate $ pip install numpy
To use anaconda with virtual environment,
$ conda create --name pysinga python=2 $ source activate pysinga $ conda install numpy
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
After installing the dependencies for SINGA and PySINGA, please download the correct binary:
# Ubuntu/Linux 64-bit, CPU only, Python 2.7, Protobuf 2.5 $ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.5/singa-1.0.0-cp27-none-linux_x86_64.whl # Ubuntu/Linux 64-bit, CPU only, Python 2.7, Protobuf 2.6 $ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6/singa-1.0.0-cp27-none-linux_x86_64.whl # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7, Protobuf 2.5, CUDA toolkit 7.5 and CuDNN v5 $ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.5-cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7, Protobuf 2.6, CUDA toolkit 7.5 and CuDNN v5 $ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6-cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl
Then, run the following command
$ sudo pip install --upgrade $SINGA_WHEEL_URL
If you do not have sudo right, you can run pip install in a python virtual environment. 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.
Please compile SINGA from source (see the next section) with the ‘USE_PYTHON’ option on, and then run the following commands,
# under the build directory $ cd python $ sudo pip install .
If you are using a virtual environment, you can ignore the sudo keyword.
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. To build cnmem into the wheel file, please change CMakeLists.txt by replacing ‘SHARED’ with ‘STATIC’.
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/ # If you use CUDA, then CNMeM is necessary $ git submodule init $ git submodule update
GCC (>=4.8.1) is required to compile SINGA on Linux. For Mac OS users, you can use either GCC or Clang.
In SINGA_ROOT, execute the following commands for compiling SINGA,
$ mkdir build && cd build $ cmake .. $ make $ make install
Note that if you are using CUDNN and it is not installed under system default folder, you need to let cmake know the paths to CUDNN,
$ export CMAKE_INCLUDE_PATH=<path to cudnn>/include:$CMAKE_INCLUDE_PATH $ export CMAKE_LIBRARY_PATH=<path to cudnn>/lib64:$CMAKE_LIBRARY_PATH
You can use ccmake .. to configure the compilation options including using generating python binding and changing the installation folder. Alternatively, the options could be switched on by
$ cmake -DUSE_CUDA=ON -DUSE_PYTHON=ON ..
If the dependent libraries are not in the system default paths, you need to export the following environment variables
export CMAKE_INCLUDE_PATH=<path to your header file folder> export CMAKE_LIBRARY_PATH=<path to your lib file folder>
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!
Install opencl-headers and libviennacl-dev (Ubuntu 16) or viennacl (Fedora).
Additionally, you will need the OpenCL Installable Client Driver (ICD) for the platforms that you want to run OpenCL on.
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
To be added.
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.
A9: 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