message: Update save_options.function_aliases docstring.
diff: @@ -126,26 +126,22 @@ class SaveOptions(object):
  by a single tf.function you can use the `function_aliases` argument to
  store a map from the alias name to all concrete function names.
  E.g.
  - ```python
  - class MyModel:
  - @tf.function
  - def func():
  - ...
  -
  - @tf.function
  - def serve():
  - ...
  - func()
  -
  - model = MyModel()
  - signatures = {
  - 'serving_default': model.serve.get_concrete_function(),
  - }
  - options = tf.saved_model.SaveOptions(function_aliases={
  - 'my_func': func,
  - })
  - tf.saved_model.save(model, export_dir, signatures, options)
  - ```
  +
  + >>> class Adder(tf.Module):
  + ... @tf.function
  + ... def double(self, x):
  + ... return x + x
  +
  + >>> model = Adder()
  + >>> model.double.get_concrete_function(
  + ... tf.TensorSpec(shape=[], dtype=tf.float32, name="float_input"))
  + >>> model.double.get_concrete_function(
  + ... tf.TensorSpec(shape=[], dtype=tf.string, name="string_input"))
  +
  + >>> options = tf.saved_model.SaveOptions(
  + ... function_aliases={'double': model.double})
  + >>> tf.saved_model.save(model, '/tmp/adder', options=options)
  +
  experimental_io_device: string. Applies in a distributed setting.
  Tensorflow device to use to access the filesystem. If `None` (default)
  then for each variable the filesystem is accessed from the CPU:0 device
  