message: Expanded the description of tf.gfile.
diff: @@ -41,11 +41,23 @@ from tensorflow.python.util.tf_export import tf_export
  class GFile(_FileIO):
  """File I/O wrappers without thread locking.
  - Note, that this is somewhat like builtin Python file I/O, but
  - there are semantic differences to make it more efficient for
  - some backing filesystems. For example, a write mode file will
  - not be opened until the first write call (to minimize RPC
  - invocations in network filesystems).
  + The main roles of the `tf.gfile` module are:
  +
  + 1. To provide an API that is close to Python's file I/O 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 to TensorBoard logs, and accessing training data (among other uses).
  + However, if all your files are local, you can use the regular Python file
  + API without any problem.
  +
  + *Note*: though similar to Python's I/O implementation, there are semantic
  + differences to make `tf.gfile` more efficient for backing filesystems. For
  + example, a write mode file will not be opened until the first write call, to
  + minimize RPC invocations in network filesystems.
  """
  def __init__(self, name, mode='r'):
  