From Conda

Conda is a package manager for Python, CPP and other packages.

Currently, SINGA has conda packages for Linux and MacOSX. Miniconda3 is recommended to use with SINGA. After installing miniconda, execute the one of the following commands to install SINGA.

  1. CPU only

     conda install -c nusdbsystem -c conda-forge singa-cpu
 In Colab

  2. GPU with CUDA and cuDNN (CUDA driver >=384.81 is required)

     conda install -c nusdbsystem -c conda-forge singa-gpu
 In Colab

  3. Install a specific version of SINGA. The following command lists all the available SINGA packages.

     conda search -c nusdbsystem singa
     Loading channels: done
     # Name                       Version           Build  Channel             
     singa                    cpu_py36  nusdbsystem         
     singa                    cpu_py37  nusdbsystem   

    The following command install a specific version of SINGA,

     conda install -c nusdbsystem -c conda-forge

If there is no error message from

python -c "from singa import tensor"

then SINGA is installed successfully.

Using Docker

Install Docker on your local host machine following the instructions. Add your user into the docker group to run docker commands without sudo.

  1. CPU-only.

    docker run -it apache/singa:2.0.0-cpu /bin/bash
  2. With GPU enabled. Install Nvidia-Docker after install Docker.

     nvidia-docker run -it apache/singa:2.0.0-gpu /bin/bash
  3. For the complete list of SINGA Docker images (tags), visit the docker hub site. For each docker image, the tag is named as


    | Tag | Description| Example value| | — | — | — | | version| SINGA version | ‘nightly‘, ‘2.0.0‘, ‘1.2.0‘| | cpu | the image cannot run on GPUs | ‘cpu‘ | | gpu | the image can run on Nvidia GPUs| ‘gpu‘, or ‘cudax.x-cudnnx.x‘ e.g., ‘cuda10.0-cudnn7.3‘| | devel| indicator for development|if absent SINGA Python package is installed for runtime only; if present, the building environment is also created, you can recompile SINGA from source at ‘/root/singa‘

  • Please note that using the nightly built images is not recommended excpet for SINGA development and testing. Using an official release is recommended. Official releases have version numbers such as ‘2.0.0‘ and ‘1.2.0‘.

From source

You can build and install SINGA from the source code using native building tools or conda-build, on local host OS or in a Docker container.


  • Q: Error from from singa import tensor

    A: Check the detailed error from

    python -c  "from singa import _singa_wrap"
    # go to the folder of
    ldd path to
    >> import importlib
    >> importlib.import_module('_singa_wrap')

    The folder of is like ‘ ~/miniconda3/lib/python3.7/site-packages/singa‘. Normally, the error is caused by the mismatch or missing of dependent libraries, e.g. cuDNN or protobuf. The solution is to create a new virtual environment and install SINGA in that environment, e.g.,

      conda create -n singa
      conda activate singa
      conda install -c nusdbsystem -c conda-forge singa-cpu
  • Q: When using virtual environment, every time I install SINGA, numpy would be reinstalled. However, the numpy is not used when I run import numpy

    A: It could be caused by the PYTHONPATH environment variable 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 I run SINGA in Mac OS X, I got the error “Fatal Python error: PyThreadState_Get: no current thread Abort trap: 6“

    A: This error happens typically when you have multiple versions of Python in your system, e.g, the one comes with the OS and the one installed by Homebrew. The Python linked by SINGA must be the same as the Python interpreter. You can check your interpreter by which python and check the Python linked by SINGA via otool -L <path to>. This problem should be resolved if SINGA is installation via conda.