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Building
========

The TensorRT Inference Server is built using Docker and the TensorFlow
and PyTorch containers from `NVIDIA GPU Cloud (NGC)
<https://ngc.nvidia.com>`_. Before building you must install Docker
and nvidia-docker and login to the NGC registry by following the
instructions in :ref:`section-installing-prebuilt-containers`.

.. _section-building-the-server:

Building the Server
-------------------

To build a release version of the TensorRT Inference Server container,
change directory to the root of the repo and checkout the release
version of the branch that you want to build (or the master branch if
you want to build the under-development version)::

  $ git checkout r19.05

Then use docker to build::

  $ docker build --pull -t tensorrtserver .

Incremental Builds
^^^^^^^^^^^^^^^^^^

For typical development you will want to run the *build* container
with your local repo’s source files mounted so that your local changes
can be incrementally built. This is done by first building the
*tensorrtserver_build* container::

  $ docker build --pull -t tensorrtserver_build --target trtserver_build .

By mounting /path/to/tensorrtserver/src into the container at
/workspace/src, changes to your local repo will be reflected in the
container::

  $ nvidia-docker run -it --rm -v/path/to/tensorrtserver/src:/workspace/src tensorrtserver_build

Within the container you can perform an incremental server build
with::

  # cd /workspace
  # bazel build -c opt src/servers/trtserver
  # cp /workspace/bazel-bin/src/servers/trtserver /opt/tensorrtserver/bin/.
  # cp /workspace/bazel-bin/src/core/libtrtserver.so /opt/tensorrtserver/lib/.

Some source changes seem to cause bazel to get confused and not
correctly rebuild all required sources. You can force bazel to rebuild
all of the inference server source without requiring a complete
rebuild of the TensorFlow and Caffe2 components by doing the following
before issuing the above build command::

  # rm -fr bazel-bin/src

Building the Client Libraries and Examples
------------------------------------------

The provided Makefile.client and Dockerfile.client can be used to
build the client libraries and examples.

.. include:: client.rst
   :start-after: build-client-begin-marker-do-not-remove
   :end-before: build-client-end-marker-do-not-remove

Building the Documentation
--------------------------

The inference server documentation is found in the docs/ directory and
is based on `Sphinx <http://www.sphinx-doc.org>`_. `Doxygen
<http://www.doxygen.org/>`_ integrated with `Exhale
<https://github.com/svenevs/exhale>`_ is used for C++ API
docuementation.

To build the docs install the required dependencies::

  $ apt-get update
  $ apt-get install -y --no-install-recommends doxygen
  $ pip install --upgrade sphinx sphinx-rtd-theme nbsphinx exhale

To get the Python client library API docs the TensorRT Inference
Server Python package must be installed::

  $ pip install --upgrade tensorrtserver-*.whl

Then use Sphinx to build the documentation into the build/html
directory::

  $ cd docs
  $ make clean html