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Using TensorRT in TensorFlow
============================
This module provides necessary bindings and introduces TRT_engine_op
operator that wraps a subgraph in TensorRT. This is still a work in progress
but should be useable with most common graphs.
Compilation
-----------
In order to compile the module, you need to have a local TensorRT
installation (libnvinfer.so and respective include files). During the
configuration step, TensorRT should be enabled and installation path
should be set. If installed through package managers (deb,rpm),
configure script should find the necessary components from the system
automatically. If installed from tar packages, user has to set path to
location where the library is installed during configuration.
```shell
bazel build --config=cuda --config=opt //tensorflow/tools/pip_package:build_pip_package
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/
```
After the installation of tensorflow package, TensorRT transformation
will be available. An example use can be found in test/test_tftrt.py directory
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