This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

1.  Using tools and libraries installed directly on your system.

    Refer to the
    [CPU-only developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-cpu.Dockerfile)
    and

# (e.g. _pywrap_tensorflow_internal.so for Python, libtensorflow.so for the C
# API) is responsible for registering ops with libtensorflow_framework.so. In
# addition to this core set of ops, user libraries which are loaded (via
# TF_LoadLibrary/tf.load_op_library) register their ops and kernels with this
# shared object directly.
#
# For example, from Python tf.load_op_library loads a custom op library (via

# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#
# TODO: Remove the following two lines once TF doesn't depend on Bazel wrapping

### Major Features and Improvements