What does tf.gfile do in TensorFlow?

For anyone landing here, the following answer was provided (by a googler) on: Why use tensorflow gfile? (for file I/O)

The main roles of the tf.gfile module are:

1. To provide an API that is close to Python’s file objects, and

2. To provide an implementation based on TensorFlow’s C++ FileSystem API.

The C++ FileSystem API supports multiple file system implementations,
including local files, Google Cloud Storage (using a gs:// prefix),
and HDFS (using an hdfs:// prefix). TensorFlow exports these as
tf.gfile, so that you can use these implementations for saving and
loading checkpoints, writing TensorBoard logs, and accessing training
data (among other uses). However, if all of your files are local, you
can use the regular Python file API without any problem.