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id: installation title: Installation

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

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

$ conda install -c nusdbsystem -c conda-forge singa-gpu

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                      2.1.0.dev        cpu_py36  nusdbsystem
singa                      2.1.0.dev        cpu_py37  nusdbsystem

The following command installs a specific version of SINGA,

$ conda install -c nusdbsystem -c conda-forge singa=X.Y.Z.dev=cpu_py37

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:X.Y.Z-cpu-ubuntu16.04 /bin/bash

2. With GPU enabled. Install Nvidia-Docker after install Docker.

$ nvidia-docker run -it apache/singa:X.Y.Z-cuda9.0-cudnn7.4.2-ubuntu16.04 /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

version-(cpu|gpu)[-devel]

Tag	Description	Example value
version	SINGA version	‘2.0.0-rc0’, ‘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’
OS	indicate OS version number	‘ubuntu16.04’, ‘ubuntu18.04’

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.

FAQ

• 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 _singa_wrap.so
  ldd path to _singa_wrap.so
  python
  >> import importlib
  >> importlib.import_module('_singa_wrap')
  

  The folder of _singa_wrap.so 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 _singa_wrap.so>. This problem should be resolved if SINGA is installation via conda.