.. install.rst: ######## Install ######## Build Environments ================== The |release| version of |project| supports Linux\*-based systems with the following packages and prerequisites: .. csv-table:: :header: "Operating System", "Compiler", "Build System", "Status", "Additional Packages" :widths: 25, 15, 25, 20, 25 :escape: ~ CentOS 7.4 64-bit, GCC 4.8, CMake 3.2, supported, ``patch diffutils zlib1g-dev libtinfo-dev`` Ubuntu 16.04 (LTS) 64-bit, Clang 3.9, CMake 3.5.1 + GNU Make, supported, ``build-essential cmake clang-3.9 git curl zlib1g zlib1g-dev libtinfo-dev`` Clear Linux\* OS for Intel Architecture, Clang 5.0.1, CMake 3.10.2, experimental, bundles ``machine-learning-basic dev-utils python3-basic python-basic-dev`` Other configurations may work, but should be considered experimental with limited support. On Ubuntu 16.04 with ``gcc-5.4.0`` or ``clang-3.9``, for example, we recommend adding ``-DNGRAPH_USE_PREBUILT_LLVM=TRUE`` to the :command:`cmake` command in step 4 below. This fetches a pre-built tarball of LLVM+Clang from `llvm.org`_, and will substantially reduce build time. If using ``gcc`` version 4.8, it may be necessary to add symlinks from ``gcc`` to ``gcc-4.8``, and from ``g++`` to ``g++-4.8``, in your :envvar:`PATH`, even if you explicitly specify the ``CMAKE_C_COMPILER`` and ``CMAKE_CXX_COMPILER`` flags when building. (**Do NOT** supply the ``-DNGRAPH_USE_PREBUILT_LLVM`` flag in this case, because the prebuilt tarball supplied on llvm.org is not compatible with a gcc 4.8-based build.) Installation Steps ================== The CMake procedure installs ``ngraph_dist`` to the installing user's ``$HOME`` directory as the default location. See the :file:`CMakeLists.txt` file for details about how to change or customize the install location. The process documented here will work on Ubuntu\* 16.04 (LTS) #. (Optional) Create something like ``/opt/libraries`` and (with sudo), give ownership of that directory to your user. Creating such a placeholder can be useful if you'd like to have a local reference for APIs and documentation, or if you are a developer who wants to experiment with how to :doc:`../howto/execute` using resources available through the code base. .. code-block:: console $ sudo mkdir -p /opt/libraries $ sudo chown -R username:username /opt/libraries $ cd /opt/libraries #. Clone the `NervanaSystems` ``ngraph`` repo: .. code-block:: console $ git clone git@github.com:NervanaSystems/ngraph.git $ cd ngraph #. Create a build directory outside of the ``ngraph/src`` directory tree; somewhere like ``ngraph/build``, for example: .. code-block:: console $ mkdir build && cd build #. Generate the GNUMakefiles in the customary manner (from within the ``build`` directory). If running ``gcc-5.4.0`` or ``clang-3.9``, remember that you can also append ``cmake`` with the prebuilt LLVM option to speed-up the build: .. code-block:: console $ cmake ../ [-DNGRAPH_USE_PREBUILT_LLVM=TRUE] #. Run ``$ make`` and ``make install`` to install ``libngraph.so`` and the header files to ``$HOME/ngraph_dist``: .. code-block:: console $ make # note: make -j <N> may work, but sometimes results in out-of-memory # errors if too many compilation processes are used $ make install #. (Optional, requires `doxygen`_, `Sphinx`_, and `breathe`_). Run ``make html`` inside the ``doc/sphinx`` directory of the cloned source to build a copy of the `website docs`_ locally. The low-level API docs with inheritance and collaboration diagrams can be found inside the ``/docs/doxygen/`` directory. macOS\* development -------------------- .. note:: Although we do not offer support for the macOS platform; some configurations and features may work. The repository includes two scripts (``maint/check-code-format.sh`` and ``maint/apply-code-format.sh``) that are used respectively to check adherence to ``libngraph`` code formatting conventions, and to automatically reformat code according to those conventions. These scripts require the command ``clang-format-3.9`` to be in your ``PATH``. Run the following commands (you will need to adjust them if you are not using bash): .. code-block:: bash $ brew install llvm@3.9 $ mkdir -p $HOME/bin $ ln -s /usr/local/opt/llvm@3.9/bin/clang-format $HOME/bin/clang-format-3.9 $ echo 'export PATH=$HOME/bin:$PATH' >> $HOME/.bash_profile Test ==== The |InG| library code base uses GoogleTest's\* `googletest framework`_ for unit tests. The ``cmake`` command from the :doc:`install` guide automatically downloaded a copy of the needed ``gtest`` files when it configured the build directory. To perform unit tests on the install: #. Create and configure the build directory as described in our :doc:`install` guide. #. Enter the build directory and run ``make check``: .. code-block:: console $ cd build/ $ make check Compile a framework with ``libngraph`` ====================================== After building and installing nGraph on your system, there are two likely paths for what you'll want to do next: either compile a framework to run a DL training model, or load an import of an "already-trained" model for inference on an Intel nGraph-enabled backend. For the former case, this early |version|, :doc:`framework-integration-guides`, can help you get started with a training a model on a supported framework. * :doc:`neon<framework-integration-guides>` framework, * :doc:`MXNet<framework-integration-guides>` framework, * :doc:`TensorFlow<framework-integration-guides>` framework, and For the latter case, if you've followed a tutorial from `ONNX`_, and you have an exported, serialized model, you can skip the section on frameworks and go directly to our :doc:`../howto/import` documentation. Please keep in mind that both of these are under continuous development, and will be updated frequently in the coming months. Stay tuned! .. _doxygen: https://www.stack.nl/~dimitri/doxygen/ .. _Sphinx: http://www.sphinx-doc.org/en/stable/ .. _breathe: https://breathe.readthedocs.io/en/latest/ .. _llvm.org: https://www.llvm.org .. _NervanaSystems: https://github.com/NervanaSystems/ngraph/blob/master/README.md .. _googletest framework: https://github.com/google/googletest.git .. _ONNX: http://onnx.ai .. _website docs: http://ngraph.nervanasys.com/docs/latest/