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

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PiperOrigin-RevId: 305898485
Change-Id: Idbee38df6b2216ac53f212a2f3fe66cb21389ebe
This commit is contained in:
Andrew Audibert 2020-04-10 10:22:29 -07:00 committed by TensorFlower Gardener
parent fbfb7e412c
commit cf5d6e2d24
2 changed files with 7 additions and 3 deletions
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4
tensorflow/python/data/experimental/ops/iterator_ops.py
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@ -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 checkpoint_management
from tensorflow.python.training import saver as saver_lib from tensorflow.python.training import saver as saver_lib
from tensorflow.python.training import session_run_hook from tensorflow.python.training import session_run_hook
from tensorflow.python.util import deprecation
from tensorflow.python.util.tf_export import tf_export 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") @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"): def make_saveable_from_iterator(iterator, external_state_policy="fail"):
"""Returns a SaveableObject for saving/restoring iterator state using Saver. """Returns a SaveableObject for saving/restoring iterator state using Saver.

6
tensorflow/python/training/tracking/util.py
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@ -1723,9 +1723,9 @@ class Checkpoint(tracking.AutoTrackable):
`Checkpoint`'s constructor accepts keyword arguments whose values are types `Checkpoint`'s constructor accepts keyword arguments whose values are types
that contain trackable state, such as `tf.keras.optimizers.Optimizer` that contain trackable state, such as `tf.keras.optimizers.Optimizer`
implementations, `tf.Variable`, `tf.keras.Layer` implementations, or implementations, `tf.Variable`s, `tf.data.Dataset` iterators, `tf.keras.Layer`
`tf.keras.Model` implementations. It saves these values with a checkpoint, and implementations, or `tf.keras.Model` implementations. It saves these values
maintains a `save_counter` for numbering checkpoints. with a checkpoint, and maintains a `save_counter` for numbering checkpoints.
Example usage: Example usage: