dmlc--dgl
Da Zheng
257 行
7.6 KiB
ReStructuredText
257 行
7.6 KiB
ReStructuredText
Install DGL
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============
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At this stage, we recommend installing DGL from ``conda`` or ``pip``.
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System requirements
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-------------------
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Currently DGL is tested on
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* Ubuntu 16.04
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* macOS X
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* Windows 10
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DGL is expected to work on all Linux distributions later than Ubuntu 16.04, macOS X, and
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Windows 10.
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DGL also requires the Python version to be 3.5 or later. Python 3.4 or less is not
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tested, and Python 2 support is coming.
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DGL supports multiple tensor libraries (e.g. PyTorch, MXNet) as backends; refer
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`Working with different backends`_ for requirements on backends and how to select a
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backend.
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Starting from 0.3 DGL is separated into CPU and CUDA builds. The builds share the
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same Python package name, so installing DGL with CUDA 9 build after installing the
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CPU build will overwrite the latter.
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Install from conda
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----------------------
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One can either grab `miniconda <https://conda.io/miniconda.html>`_ or
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the full `anaconda <https://www.anaconda.com/download/>`_ if ``conda``
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has not been installed.
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Once the conda environment is activated, run
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.. code:: bash
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conda install -c dglteam dgl # For CPU Build
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conda install -c dglteam dgl-cuda9.0 # For CUDA 9.0 Build
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conda install -c dglteam dgl-cuda10.0 # For CUDA 10.0 Build
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Install from pip
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----------------
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For CPU builds, one can simply run the following command to install via ``pip``:
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.. code:: bash
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pip install dgl
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For CUDA builds, one needs to specify the URL:
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.. code:: bash
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pip install https://s3.us-east-2.amazonaws.com/dgl.ai/<BUILD-DIR>/dgl-0.3-<PYTHON-ABI>-<PLATFORM>.whl
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where ``<BUILD-DIR>``, ``<PYTHON-ABI>`` and ``<PLATFORM>`` can take either of the following values:
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+------------+---------------------+
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| Build Type | ``<BUILD>`` |
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+============+=====================+
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| CUDA 9.0 | ``wheels/cuda9.0`` |
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+------------+---------------------+
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| CUDA 10.0 | ``wheels/cuda10.0`` |
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+------------+---------------------+
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+------------------+------------------+
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| Python Version | ``<PYTHON-ABI>`` |
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+==================+==================+
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| Python 3.5 | ``cp35-cp35m`` |
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+------------------+------------------+
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| Python 3.6 | ``cp36-cp36m`` |
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+------------------+------------------+
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| Python 3.7 | ``cp37-cp37m`` |
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+------------------+------------------+
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+-------------+-----------------------+
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| OS/Arch | ``<PLATFORM>`` |
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+=============+=======================+
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| Linux x64 | ``manylinux1_x86_64`` |
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+-------------+-----------------------+
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| Windows x64 | ``win_amd64`` |
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+-------------+-----------------------+
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For instance, if one wants to install the CUDA 9.0 build on Linux, Python 3.5, then the command is
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.. code:: bash
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pip install https://s3.us-east-2.amazonaws.com/dgl.ai/wheels/cuda9.0/dgl-0.3-cp35-cp35m-manylinux1_x86_64.whl
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Working with different backends
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-------------------------------
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Currently DGL supports PyTorch and MXNet.
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Switching backend
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`````````````````
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The backend is controlled by ``DGLBACKEND`` environment variable, which defaults to
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``pytorch``. Currently it supports the following values:
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+---------+---------+--------------------------------------------------+
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| Value | Backend | Memo |
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+=========+=========+==================================================+
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| pytorch | PyTorch | Requires 0.4.1 or later; see |
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| | | `official website <https://pytorch.org>`_ |
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+---------+---------+--------------------------------------------------+
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| mxnet | MXNet | Requires MXNet 1.5 |
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| | | |
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| | | .. code:: bash |
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| | | pip install mxnet |
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| | | |
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| | | or cuda version (e.g. for cuda 9.0) |
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| | | |
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| | | .. code:: bash |
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| | | pip install mxnet-cu90 |
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+---------+---------+--------------------------------------------------+
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| numpy | NumPy | Does not support gradient computation |
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+---------+---------+--------------------------------------------------+
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.. _install-from-source:
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Install from source
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-------------------
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First, download the source files from GitHub:
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.. code:: bash
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git clone --recursive https://github.com/dmlc/dgl.git
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One can also clone the repository first and run the following:
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.. code:: bash
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git submodule init
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git submodule update
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Linux
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`````
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Install the system packages for building the shared library, for Debian/Ubuntu
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users, run:
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.. code:: bash
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sudo apt-get update
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sudo apt-get install -y build-essential build-dep python3-dev make cmake
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For Fedora/RHEL/CentOS users, run:
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.. code:: bash
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sudo yum install -y gcc-c++ python3-devel make cmake
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Build the shared library. Use the configuration template ``cmake/config.cmake``.
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Copy it to either the project directory or the build directory and change the
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configuration as you wish. For example, change ``USE_CUDA`` to ``ON`` will
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enable cuda build. You could also pass ``-DKEY=VALUE`` to the cmake command
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for the same purpose.
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- CPU-only build:
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.. code:: bash
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mkdir build
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cd build
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cmake ..
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make -j4
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- Cuda build:
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.. code:: bash
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mkdir build
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cd build
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cmake -DUSE_CUDA=ON ..
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make -j4
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Finally, install the Python binding.
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.. code:: bash
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cd ../python
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python setup.py install
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macOS
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`````
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Installation on macOS is similar to Linux. But macOS users need to install
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building tools like clang, GNU Make, cmake first.
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Tools like clang and GNU Make are packaged in **Command Line Tools** for macOS. To
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install:
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.. code:: bash
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xcode-select --install
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To install other needed packages like cmake, we recommend first installing
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**Homebrew**, which is a popular package manager for macOS. Detailed
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instructions can be found on its `homepage <https://brew.sh/>`_.
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After installation of Homebrew, install cmake by:
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.. code:: bash
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brew install cmake
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Then go to root directory of DGL repository, build shared library and
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install Python binding for DGL:
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.. code:: bash
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mkdir build
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cd build
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cmake ..
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make -j4
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cd ../python
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python setup.py install
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We tested installation on macOS X with clang 10.0.0, GNU Make 3.81, and cmake
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3.13.1.
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Windows
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```````
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Currently Windows source build is tested with CMake and MinGW/GCC. We highly recommend
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using CMake and GCC from `conda installations <https://conda.io/miniconda.html>`_. To
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do so, run
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.. code:: bash
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conda install cmake m2w64-gcc m2w64-make
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Then build the shared library and install the Python binding:
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.. code::
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md build
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cd build
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cmake -DCMAKE_CXX_FLAGS="-DDMLC_LOG_STACK_TRACE=0 -DDGL_EXPORTS" -DCMAKE_MAKE_PROGRAM=mingw32-make .. -G "MSYS Makefiles"
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mingw32-make
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cd ..\python
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python setup.py install
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We also support building DGL with MSBuild. With `MS Build Tools <https://go.microsoft.com/fwlink/?linkid=840931>`_
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and `CMake on Windows <https://cmake.org/download/>`_ installed, run the following
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in VS2017 x64 Native tools command prompt:
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.. code::
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MD build
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CD build
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cmake -DCMAKE_CXX_FLAGS="/DDGL_EXPORTS" -DCMAKE_CONFIGURATION_TYPES="Release" .. -G "Visual Studio 15 2017 Win64"
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msbuild dgl.sln
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cd ..\python
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python setup.py install
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