[tf.data] Add documentation for checkpointing V2 dataset iterators.

PiperOrigin-RevId: 305898485
Change-Id: Idbee38df6b2216ac53f212a2f3fe66cb21389ebe

tensorflow/python/data/experimental/ops/iterator_ops.py

@@ -25,6 +25,7 @@ from tensorflow.python.training import basic_session_run_hooks
 from tensorflow.python.training import checkpoint_management
 from tensorflow.python.training import saver as saver_lib
 from tensorflow.python.training import session_run_hook
+from tensorflow.python.util import deprecation
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -42,6 +43,9 @@ def _convert_external_state_policy_to_enum(external_state_policy):
 
 
 @tf_export("data.experimental.make_saveable_from_iterator")
+@deprecation.deprecated(
+    None, "`make_saveable_from_iterator` is intended for use in TF1 with "
+    "`tf.compat.v1.Saver`. In TF2, use `tf.train.Checkpoint` instead.")
 def make_saveable_from_iterator(iterator, external_state_policy="fail"):
   """Returns a SaveableObject for saving/restoring iterator state using Saver.
 

tensorflow/python/training/tracking/util.py

@@ -1723,9 +1723,9 @@ class Checkpoint(tracking.AutoTrackable):
 
   `Checkpoint`'s constructor accepts keyword arguments whose values are types
   that contain trackable state, such as `tf.keras.optimizers.Optimizer`
-  implementations, `tf.Variable`, `tf.keras.Layer` implementations, or
-  `tf.keras.Model` implementations. It saves these values with a checkpoint, and
-  maintains a `save_counter` for numbering checkpoints.
+  implementations, `tf.Variable`s, `tf.data.Dataset` iterators, `tf.keras.Layer`
+  implementations, or `tf.keras.Model` implementations. It saves these values
+  with a checkpoint, and maintains a `save_counter` for numbering checkpoints.
 
   Example usage: