Install DGL¶

At this stage, we recommend installing DGL from conda or pip.

System requirements¶

Currently DGL is tested on

Ubuntu 16.04
macOS X
Windows 10

DGL is expected to work on all Linux distributions later than Ubuntu 16.04, macOS X, and Windows 10.

DGL also requires the Python version to be 3.5 or later. Python 3.4 or less is not tested, and Python 2 support is coming.

DGL supports multiple tensor libraries (e.g. PyTorch, MXNet) as backends; refer Working with different backends for requirements on backends and how to select a backend.

Install from conda¶

One can either grab miniconda or the full anaconda if conda has not been installed.

Once the conda environment is activated, run

conda install -c dglteam dgl

Install from pip¶

One can simply run the following command to install via pip:

pip install dgl

Working with different backends¶

Currently DGL supports PyTorch and MXNet.

Switching backend¶

The backend is controlled by DGLBACKEND environment variable, which defaults to pytorch. Currently it supports the following values:

Value	Backend	Memo
pytorch	PyTorch	Requires 0.4.1 or later; see official website
mxnet	MXNet	Requires nightly build; run the following command to install (TODO): pip install --pre mxnet
numpy	NumPy	Does not support gradient computation

Install from source¶

First, download the source files from GitHub:

git clone --recursive https://github.com/dmlc/dgl.git

One can also clone the repository first and run the following:

git submodule init
git submodule update

Linux¶

Install the system packages for building the shared library, for Debian/Ubuntu users, run:

sudo apt-get update
sudo apt-get install -y build-essential build-dep python3-dev make cmake

For Fedora/RHEL/CentOS users, run:

sudo yum install -y gcc-c++ python3-devel make cmake

Build the shared library and install the Python binding afterwards:

mkdir build
cd build
cmake ..
make -j4
cd ../python
python setup.py install

macOS¶

Installation on macOS is similar to Linux. But macOS users need to install building tools like clang, GNU Make, cmake first.

Tools like clang and GNU Make are packaged in Command Line Tools for macOS. To install:

xcode-select --install

To install other needed packages like cmake, we recommend first installing Homebrew, which is a popular package manager for macOS. Detailed instructions can be found on its homepage.

After installation of Homebrew, install cmake by:

brew install cmake

Then go to root directory of DGL repository, build shared library and install Python binding for DGL:

mkdir build
cd build
cmake ..
make -j4
cd ../python
python setup.py install

We tested installation on macOS X with clang 10.0.0, GNU Make 3.81, and cmake 3.13.1.

Windows¶

Currently Windows source build is tested with CMake and MinGW/GCC. We highly recommend using CMake and GCC from conda installations. To do so, run

conda install cmake m2w64-gcc m2w64-make

Then build the shared library and install the Python binding:

md build
cd build
cmake -DCMAKE_CXX_FLAGS="-DDMLC_LOG_STACK_TRACE=0 -DDGL_EXPORTS" -DCMAKE_MAKE_PROGRAM=mingw32-make .. -G "MSYS Makefiles"
mingw32-make
cd ..\python
python setup.py install