diff --git a/RELEASE.md b/RELEASE.md
index 666a7dbc8bb..5e06d0d473e 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -58,6 +58,9 @@
 * A new module named `tf.experimental.numpy` is added, which is a NumPy-compatible API for writing TF programs. This module provides class `ndarray`, which mimics the `ndarray` class in NumPy, and wraps an immutable `tf.Tensor` under the hood. A subset of NumPy functions (e.g. `numpy.add`) are provided. Their inter-operation with TF facilities is seamless in most cases. See [tensorflow/python/ops/numpy_ops/README.md](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/numpy_ops/README.md) for details of what operations are supported and what are the differences from NumPy.
 * A major refactoring of the internals of the Keras Functional API has been completed, that should improve the reliability, stability, and performance of constructing Functional models.
 
+* `tf.distribute`:
+  * Deprecated `experimental_distribute_datasets_from_function` method and renamed it to `distribute_datasets_from_function` as it is no longer experimental.
+
 ## Bug Fixes and Other Changes
 
 * <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
diff --git a/tensorflow/python/distribute/central_storage_strategy.py b/tensorflow/python/distribute/central_storage_strategy.py
index 6e2c441c468..e61570dd6bd 100644
--- a/tensorflow/python/distribute/central_storage_strategy.py
+++ b/tensorflow/python/distribute/central_storage_strategy.py
@@ -105,52 +105,6 @@ class CentralStorageStrategy(distribute_lib.Strategy):
     return super(CentralStorageStrategy, self).experimental_distribute_dataset(
         dataset, options)
 
-  def experimental_distribute_datasets_from_function(self, dataset_fn,  # pylint: disable=useless-super-delegation
-                                                     options=None):
-    """Distributes `tf.data.Dataset` instances created by calls to `dataset_fn`.
-
-    `dataset_fn` will be called once for each worker in the strategy. In this
-    case, we only have one worker so `dataset_fn` is called once. Each replica
-    on this worker will then dequeue a batch of elements from this local
-    dataset.
-
-    The `dataset_fn` should take an `tf.distribute.InputContext` instance where
-    information about batching and input replication can be accessed.
-
-    For Example:
-    ```
-    def dataset_fn(input_context):
-      batch_size = input_context.get_per_replica_batch_size(global_batch_size)
-      d = tf.data.Dataset.from_tensors([[1.]]).repeat().batch(batch_size)
-      return d.shard(
-          input_context.num_input_pipelines, input_context.input_pipeline_id)
-
-    inputs = strategy.experimental_distribute_datasets_from_function(dataset_fn)
-
-    for batch in inputs:
-      replica_results = strategy.run(replica_fn, args=(batch,))
-    ```
-
-    IMPORTANT: The `tf.data.Dataset` returned by `dataset_fn` should have a
-    per-replica batch size, unlike `experimental_distribute_dataset`, which uses
-    the global batch size.  This may be computed using
-    `input_context.get_per_replica_batch_size`.
-
-    Args:
-      dataset_fn: A function taking a `tf.distribute.InputContext` instance and
-        returning a `tf.data.Dataset`.
-      options: `tf.distribute.InputOptions` used to control options on how this
-        dataset is distributed.
-
-    Returns:
-      A "distributed `Dataset`", which the caller can iterate over like regular
-      datasets.
-    """
-    return super(
-        CentralStorageStrategy,
-        self).experimental_distribute_datasets_from_function(dataset_fn,
-                                                             options)
-
   def experimental_local_results(self, value):  # pylint: disable=useless-super-delegation
     """Returns the list of all local per-replica values contained in `value`.
 
diff --git a/tensorflow/python/distribute/collective_all_reduce_strategy.py b/tensorflow/python/distribute/collective_all_reduce_strategy.py
index e41fda63fd5..a3e63e8a6f1 100644
--- a/tensorflow/python/distribute/collective_all_reduce_strategy.py
+++ b/tensorflow/python/distribute/collective_all_reduce_strategy.py
@@ -479,8 +479,7 @@ class CollectiveAllReduceExtended(mirrored_strategy.MirroredExtended):
         split_batch_by=self._num_replicas_in_sync,
         input_context=input_context)
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     input_context = self._make_input_context()
     return input_lib.get_distributed_datasets_from_function(
         dataset_fn=dataset_fn,
diff --git a/tensorflow/python/distribute/custom_training_loop_input_test.py b/tensorflow/python/distribute/custom_training_loop_input_test.py
index a835f5e5ac9..7debd850486 100644
--- a/tensorflow/python/distribute/custom_training_loop_input_test.py
+++ b/tensorflow/python/distribute/custom_training_loop_input_test.py
@@ -386,7 +386,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
   def testDistributeDatasetIteratorWithoutFunction(self, distribution):
     data = [5., 6., 7., 8.]
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(
+        distribution.distribute_datasets_from_function(
             lambda _: get_dataset_from_tensor_slices(data)))
 
     self.assertAllEqual(
@@ -401,7 +401,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
   def testDistributeDatasetIteratorWithFunction(self, distribution):
     data = [5., 6., 7., 8.]
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(
+        distribution.distribute_datasets_from_function(
             lambda _: get_dataset_from_tensor_slices(data)))
 
     @def_function.function
@@ -439,7 +439,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
   def testDistributeDatasetFunctionPrefetch(self, distribution):
     data = [5., 6., 7., 8.]
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(
+        distribution.distribute_datasets_from_function(
             lambda _: get_dataset_from_tensor_slices(data)))
 
     local_results = distribution.experimental_local_results(
@@ -476,10 +476,9 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
   def testDistributeDatasetFunctionHostPrefetch(self, distribution):
     data = [5., 6., 7., 8.]
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(
+        distribution.distribute_datasets_from_function(
             lambda _: get_dataset_from_tensor_slices(data),
-            distribute_lib.InputOptions(
-                experimental_prefetch_to_device=False)))
+            distribute_lib.InputOptions(experimental_prefetch_to_device=False)))
 
     local_results = distribution.experimental_local_results(
         input_iterator.get_next())
@@ -645,7 +644,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
       return dataset
 
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(dataset_fn))
+        distribution.distribute_datasets_from_function(dataset_fn))
 
     @def_function.function
     def step_fn(example):
@@ -673,7 +672,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
       return dataset
 
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(dataset_fn))
+        distribution.distribute_datasets_from_function(dataset_fn))
 
     @def_function.function
     def step_fn(example):
@@ -724,7 +723,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
       return dataset
 
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(dataset_fn))
+        distribution.distribute_datasets_from_function(dataset_fn))
 
     @def_function.function
     def run(inputs):
@@ -750,7 +749,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
       return dataset
 
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(dataset_fn))
+        distribution.distribute_datasets_from_function(dataset_fn))
 
     def embedding_lookup(inputs):
       embedding_weights = array_ops.zeros((1, 128))
@@ -935,7 +934,7 @@ class InputIterationTest(test.TestCase, parameterized.TestCase,
     inputs = constant_op.constant([2., 3.])
     dataset = lambda _: dataset_ops.Dataset.from_tensor_slices(inputs).repeat(5)
     input_iterator = iter(
-        distribution.experimental_distribute_datasets_from_function(dataset))
+        distribution.distribute_datasets_from_function(dataset))
     with distribution.scope():
       var = variables.Variable(1.0)
 
diff --git a/tensorflow/python/distribute/distribute_lib.py b/tensorflow/python/distribute/distribute_lib.py
index 944fc9c6ed7..14e2b6f3f02 100644
--- a/tensorflow/python/distribute/distribute_lib.py
+++ b/tensorflow/python/distribute/distribute_lib.py
@@ -114,7 +114,7 @@ the same way with eager and graph execution.
   devices, with a different value for each replica. They are produced by
   iterating through a distributed dataset returned by
   `tf.distribute.Strategy.experimental_distribute_dataset` and
-  `tf.distribute.Strategy.experimental_distribute_datasets_from_function`. They
+  `tf.distribute.Strategy.distribute_datasets_from_function`. They
   are also the typical result returned by
   `tf.distribute.Strategy.run`.
 
@@ -688,7 +688,7 @@ class StrategyBase(object):
         a `tf.data.Dataset` to something that produces "per-replica" values.
         If you want to manually specify how the dataset should be partitioned
         across replicas, use
-        `tf.distribute.Strategy.experimental_distribute_datasets_from_function`
+        `tf.distribute.Strategy.distribute_datasets_from_function`
         instead.
       * Use `tf.distribute.Strategy.run` to run a function
         once per replica, taking values that may be "per-replica" (e.g.
@@ -1030,13 +1030,13 @@ class StrategyBase(object):
 
     If the above batch splitting and dataset sharding logic is undesirable,
     please use
-    `tf.distribute.Strategy.experimental_distribute_datasets_from_function`
+    `tf.distribute.Strategy.distribute_datasets_from_function`
     instead, which does not do any automatic batching or sharding for you.
 
     Note: If you are using TPUStrategy, the order in which the data is processed
     by the workers when using
     `tf.distribute.Strategy.experimental_distribute_dataset` or
-    `tf.distribute.Strategy.experimental_distribute_datasets_from_function` is
+    `tf.distribute.Strategy.distribute_datasets_from_function` is
     not guaranteed. This is typically required if you are using
     `tf.distribute` to scale prediction. You can however insert an index for
     each element in the batch and order outputs accordingly. Refer to [this
@@ -1045,7 +1045,7 @@ class StrategyBase(object):
 
     Note: Stateful dataset transformations are currently not supported with
     `tf.distribute.experimental_distribute_dataset` or
-    `tf.distribute.experimental_distribute_datasets_from_function`. Any stateful
+    `tf.distribute.distribute_datasets_from_function`. Any stateful
     ops that the dataset may have are currently ignored. For example, if your
     dataset has a `map_fn` that uses `tf.random.uniform` to rotate an image,
     then you have a dataset graph that depends on state (i.e the random seed) on
@@ -1067,8 +1067,7 @@ class StrategyBase(object):
     # pylint: enable=line-too-long
     return self._extended._experimental_distribute_dataset(dataset, options)  # pylint: disable=protected-access
 
-  def experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                     options=None):
+  def distribute_datasets_from_function(self, dataset_fn, options=None):
     # pylint: disable=line-too-long
     """Distributes `tf.data.Dataset` instances created by calls to `dataset_fn`.
 
@@ -1077,7 +1076,7 @@ class StrategyBase(object):
     instance. It is expected that the returned dataset from `dataset_fn` is
     already batched by per-replica batch size (i.e. global batch size divided by
     the number of replicas in sync) and sharded.
-    `tf.distribute.Strategy.experimental_distribute_datasets_from_function` does
+    `tf.distribute.Strategy.distribute_datasets_from_function` does
     not batch or shard the `tf.data.Dataset` instance
     returned from the input function. `dataset_fn` will be called on the CPU
     device of each of the workers and each generates a dataset where every
@@ -1112,7 +1111,7 @@ class StrategyBase(object):
     Note: If you are using TPUStrategy, the order in which the data is processed
     by the workers when using
     `tf.distribute.Strategy.experimental_distribute_dataset` or
-    `tf.distribute.Strategy.experimental_distribute_datasets_from_function` is
+    `tf.distribute.Strategy.distribute_datasets_from_function` is
     not guaranteed. This is typically required if you are using
     `tf.distribute` to scale prediction. You can however insert an index for
     each element in the batch and order outputs accordingly. Refer to [this
@@ -1121,14 +1120,14 @@ class StrategyBase(object):
 
     Note: Stateful dataset transformations are currently not supported with
     `tf.distribute.experimental_distribute_dataset` or
-    `tf.distribute.experimental_distribute_datasets_from_function`. Any stateful
+    `tf.distribute.distribute_datasets_from_function`. Any stateful
     ops that the dataset may have are currently ignored. For example, if your
     dataset has a `map_fn` that uses `tf.random.uniform` to rotate an image,
     then you have a dataset graph that depends on state (i.e the random seed) on
     the local machine where the python process is being executed.
 
     For a tutorial on more usage and properties of this method, refer to the
-    [tutorial on distributed input](https://www.tensorflow.org/tutorials/distribute/input#tfdistributestrategyexperimental_distribute_datasets_from_function).
+    [tutorial on distributed input](https://www.tensorflow.org/tutorials/distribute/input#tfdistributestrategyexperimental_distribute_datasets_from_function)).
     If you are interested in last partial batch handling, read [this section](https://www.tensorflow.org/tutorials/distribute/input#partial_batches).
 
     Args:
@@ -1141,9 +1140,17 @@ class StrategyBase(object):
       A `tf.distribute.DistributedDataset`.
     """
     # pylint: enable=line-too-long
-    return self._extended._experimental_distribute_datasets_from_function(  # pylint: disable=protected-access
+    return self._extended._distribute_datasets_from_function(  # pylint: disable=protected-access
         dataset_fn, options)
 
+  # TODO(b/162776748): Remove deprecated symbol.
+  @doc_controls.do_not_doc_inheritable
+  @deprecation.deprecated(None, "rename to distribute_datasets_from_function")
+  def experimental_distribute_datasets_from_function(self,
+                                                     dataset_fn,
+                                                     options=None):
+    return self.distribute_datasets_from_function(dataset_fn, options)
+
   def run(self, fn, args=(), kwargs=None, options=None):
     """Invokes `fn` on each replica, with the given arguments.
 
@@ -1152,7 +1159,7 @@ class StrategyBase(object):
     have `tf.distribute.DistributedValues`, such as those produced by a
     `tf.distribute.DistributedDataset` from
     `tf.distribute.Strategy.experimental_distribute_dataset` or
-    `tf.distribute.Strategy.experimental_distribute_datasets_from_function`,
+    `tf.distribute.Strategy.distribute_datasets_from_function`,
     when `fn` is executed on a particular replica, it will be executed with the
     component of `tf.distribute.DistributedValues` that correspond to that
     replica.
@@ -2196,8 +2203,7 @@ class StrategyExtendedV2(object):
   def _experimental_distribute_dataset(self, dataset, options):
     raise NotImplementedError("must be implemented in descendants")
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     raise NotImplementedError("must be implemented in descendants")
 
   def _experimental_distribute_values_from_function(self, value_fn):
@@ -3298,8 +3304,7 @@ class _DefaultDistributionExtended(StrategyExtendedV1):
   def _experimental_distribute_dataset(self, dataset, options):
     return dataset
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     return dataset_fn(InputContext())
 
   def _experimental_distribute_values_from_function(self, value_fn):
diff --git a/tensorflow/python/distribute/distribute_lib_test.py b/tensorflow/python/distribute/distribute_lib_test.py
index 816ff0ce465..0fe05b52d6f 100644
--- a/tensorflow/python/distribute/distribute_lib_test.py
+++ b/tensorflow/python/distribute/distribute_lib_test.py
@@ -89,8 +89,7 @@ class _TestExtended(distribute_lib.StrategyExtendedV1):
                                            [distribute_lib.InputContext()],
                                            self._container_strategy())
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     return dataset_fn(distribute_lib.InputContext())
 
   def _local_results(self, value):
@@ -546,14 +545,14 @@ class DefaultDistributionStrategyTest(test.TestCase, parameterized.TestCase):
     if context.executing_eagerly():
       dataset_fn = lambda _: dataset_ops.DatasetV2.range(10).batch(2)
       dist_dataset_from_func = \
-          default_strategy.experimental_distribute_datasets_from_function(
+          default_strategy.distribute_datasets_from_function(
               dataset_fn)
       next_val = next(iter(dist_dataset_from_func))
       self.assertAllEqual([0, 1], self.evaluate(next_val))
     else:
       dataset_fn = lambda _: dataset_ops.DatasetV2.range(10).batch(2)
       dist_dataset_from_func = \
-        default_strategy.experimental_distribute_datasets_from_function(
+        default_strategy.distribute_datasets_from_function(
             dataset_fn)
       dataset_ops.make_initializable_iterator(dist_dataset_from_func)
 
diff --git a/tensorflow/python/distribute/input_lib.py b/tensorflow/python/distribute/input_lib.py
index d689346870e..dbefff9cf66 100644
--- a/tensorflow/python/distribute/input_lib.py
+++ b/tensorflow/python/distribute/input_lib.py
@@ -274,7 +274,7 @@ class DistributedDatasetInterface(collections_abc.Iterable,
 
   There are two APIs to create a `tf.distribute.DistributedDataset` object:
   `tf.distribute.Strategy.experimental_distribute_dataset(dataset)`and
-  `tf.distribute.Strategy.experimental_distribute_datasets_from_function(dataset_fn)`.
+  `tf.distribute.Strategy.distribute_datasets_from_function(dataset_fn)`.
   *When to use which?* When you have a `tf.data.Dataset` instance, and the
   regular batch splitting (i.e. re-batch the input `tf.data.Dataset` instance
   with a new batch size that is equal to the global batch size divided by the
diff --git a/tensorflow/python/distribute/input_lib_test.py b/tensorflow/python/distribute/input_lib_test.py
index b43dc961d27..ec0b591d710 100644
--- a/tensorflow/python/distribute/input_lib_test.py
+++ b/tensorflow/python/distribute/input_lib_test.py
@@ -120,7 +120,7 @@ class DistributedIteratorTestBase(test.TestCase):
             split_batch_by=split_batch_by,
             input_context=input_context)
     else:
-      return strategy.experimental_distribute_datasets_from_function(dataset)
+      return strategy.distribute_datasets_from_function(dataset)
 
   def _assert_iterator_values(self,
                               iterator,
@@ -1158,8 +1158,7 @@ class DistributedIteratorTensorTypeTest(DistributedIteratorTestBase,
       ds = distribution.experimental_distribute_dataset(
           dataset_fn(distribute_lib.InputContext()))
     else:
-      ds = distribution.experimental_distribute_datasets_from_function(
-          dataset_fn)
+      ds = distribution.distribute_datasets_from_function(dataset_fn)
     iterator = iter(ds)
 
     self.assertEqual(iterator._enable_get_next_as_optional,
@@ -1208,8 +1207,7 @@ class DistributedIteratorTensorTypeTest(DistributedIteratorTestBase,
       ds = distribution.experimental_distribute_dataset(
           dataset_fn(distribute_lib.InputContext()))
     else:
-      ds = distribution.experimental_distribute_datasets_from_function(
-          dataset_fn)
+      ds = distribution.distribute_datasets_from_function(dataset_fn)
 
     # Iterate through all the batches and sum them up.
     def sum_batch(per_replica_features):
diff --git a/tensorflow/python/distribute/input_lib_type_spec_test.py b/tensorflow/python/distribute/input_lib_type_spec_test.py
index 691b29202e1..bc6ac811bbb 100644
--- a/tensorflow/python/distribute/input_lib_type_spec_test.py
+++ b/tensorflow/python/distribute/input_lib_type_spec_test.py
@@ -176,8 +176,7 @@ class InputTypeSpecTest(test.TestCase, parameterized.TestCase):
           dataset_fn(distribute_lib.InputContext()))
       type_spec = ds.element_spec
     else:
-      ds = distribution.experimental_distribute_datasets_from_function(
-          dataset_fn)
+      ds = distribution.distribute_datasets_from_function(dataset_fn)
       iterator = iter(ds)
       _check_type_spec_structure(iterator)
       type_spec = iterator.element_spec
diff --git a/tensorflow/python/distribute/mirrored_strategy.py b/tensorflow/python/distribute/mirrored_strategy.py
index 79a563680ea..523c71c4fb5 100644
--- a/tensorflow/python/distribute/mirrored_strategy.py
+++ b/tensorflow/python/distribute/mirrored_strategy.py
@@ -507,8 +507,7 @@ class MirroredExtended(distribute_lib.StrategyExtendedV1):
     return numpy_dataset.one_host_numpy_dataset(
         numpy_input, self._host_input_device, session)
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     input_contexts = []
     input_workers = self._input_workers_with_options(options)
     num_workers = input_workers.num_workers
diff --git a/tensorflow/python/distribute/one_device_strategy.py b/tensorflow/python/distribute/one_device_strategy.py
index 8f40a5f7991..c256c2df78f 100644
--- a/tensorflow/python/distribute/one_device_strategy.py
+++ b/tensorflow/python/distribute/one_device_strategy.py
@@ -109,8 +109,10 @@ class OneDeviceStrategy(distribute_lib.Strategy):
     return super(OneDeviceStrategy, self).experimental_distribute_dataset(
         dataset, options)
 
-  def experimental_distribute_datasets_from_function(self, dataset_fn,  # pylint: disable=useless-super-delegation
-                                                     options=None):
+  def distribute_datasets_from_function(
+      self,
+      dataset_fn,  # pylint: disable=useless-super-delegation
+      options=None):
     """Distributes `tf.data.Dataset` instances created by calls to `dataset_fn`.
 
     `dataset_fn` will be called once for each worker in the strategy. In this
@@ -127,7 +129,7 @@ class OneDeviceStrategy(distribute_lib.Strategy):
       return d.shard(
           input_context.num_input_pipelines, input_context.input_pipeline_id)
 
-    inputs = strategy.experimental_distribute_datasets_from_function(dataset_fn)
+    inputs = strategy.distribute_datasets_from_function(dataset_fn)
 
     for batch in inputs:
       replica_results = strategy.run(replica_fn, args=(batch,))
@@ -148,9 +150,8 @@ class OneDeviceStrategy(distribute_lib.Strategy):
       A "distributed `Dataset`", which the caller can iterate over like regular
       datasets.
     """
-    return super(
-        OneDeviceStrategy, self).experimental_distribute_datasets_from_function(
-            dataset_fn, options)
+    return super(OneDeviceStrategy,
+                 self).distribute_datasets_from_function(dataset_fn, options)
 
   def experimental_local_results(self, value):  # pylint: disable=useless-super-delegation
     """Returns the list of all local per-replica values contained in `value`.
@@ -316,8 +317,7 @@ class OneDeviceExtended(distribute_lib.StrategyExtendedV1):
         self._input_workers_with_options(options),
         self._container_strategy())
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     return input_lib.get_distributed_datasets_from_function(
         dataset_fn,
         self._input_workers_with_options(options),
diff --git a/tensorflow/python/distribute/parameter_server_strategy.py b/tensorflow/python/distribute/parameter_server_strategy.py
index 1d4c593d48b..b60ea74dd04 100644
--- a/tensorflow/python/distribute/parameter_server_strategy.py
+++ b/tensorflow/python/distribute/parameter_server_strategy.py
@@ -128,12 +128,10 @@ class ParameterServerStrategy(distribute_lib.Strategy):
           self).experimental_distribute_dataset(dataset=dataset,
                                                 options=options)
 
-  def experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                     options=None):
+  def distribute_datasets_from_function(self, dataset_fn, options=None):
     self._raise_pss_error_if_eager()
-    super(ParameterServerStrategy,
-          self).experimental_distribute_datasets_from_function(
-              dataset_fn=dataset_fn, options=options)
+    super(ParameterServerStrategy, self).distribute_datasets_from_function(
+        dataset_fn=dataset_fn, options=options)
 
   def run(self, fn, args=(), kwargs=None, options=None):
     self._raise_pss_error_if_eager()
@@ -387,8 +385,7 @@ class ParameterServerStrategyExtended(distribute_lib.StrategyExtendedV1):
     return numpy_dataset.one_host_numpy_dataset(
         numpy_input, self._input_host_device, session)
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     if self._cluster_spec:
       input_pipeline_id = multi_worker_util.id_in_cluster(
           self._cluster_spec, self._task_type, self._task_id)
diff --git a/tensorflow/python/distribute/parameter_server_strategy_test.py b/tensorflow/python/distribute/parameter_server_strategy_test.py
index a68183adbaa..1b4cd21c249 100644
--- a/tensorflow/python/distribute/parameter_server_strategy_test.py
+++ b/tensorflow/python/distribute/parameter_server_strategy_test.py
@@ -759,10 +759,9 @@ class ParameterServerStrategyTest(
                            strategy.experimental_distribute_dataset,
                            dataset.batch(2))
 
-    self.assertRaisesRegex(
-        NotImplementedError, 'ParameterServerStrategy*',
-        strategy.experimental_distribute_datasets_from_function,
-        lambda _: dataset)
+    self.assertRaisesRegex(NotImplementedError, 'ParameterServerStrategy*',
+                           strategy.distribute_datasets_from_function,
+                           lambda _: dataset)
 
     self.assertRaisesRegex(NotImplementedError, 'ParameterServerStrategy*',
                            strategy.scope)
diff --git a/tensorflow/python/distribute/strategy_common_test.py b/tensorflow/python/distribute/strategy_common_test.py
index 0c9fbe0d660..5eeeb11fa8f 100644
--- a/tensorflow/python/distribute/strategy_common_test.py
+++ b/tensorflow/python/distribute/strategy_common_test.py
@@ -605,7 +605,7 @@ class DistributedCollectiveAllReduceStrategyTest(
 
     expected_sum_on_workers = {'chief': 10, 'worker': 35}
     input_iterator = iter(
-        strategy.experimental_distribute_datasets_from_function(dataset_fn))
+        strategy.distribute_datasets_from_function(dataset_fn))
 
     @def_function.function
     def run(iterator):
@@ -648,7 +648,7 @@ class DistributedCollectiveAllReduceStrategyTest(
                            input_context.input_pipeline_id)
 
     input_iterator = iter(
-        strategy.experimental_distribute_datasets_from_function(dataset_fn))
+        strategy.distribute_datasets_from_function(dataset_fn))
 
     @def_function.function
     def run(input_iterator):
diff --git a/tensorflow/python/distribute/strategy_test_lib.py b/tensorflow/python/distribute/strategy_test_lib.py
index 0bc4c6fca68..f660e3ab9f8 100644
--- a/tensorflow/python/distribute/strategy_test_lib.py
+++ b/tensorflow/python/distribute/strategy_test_lib.py
@@ -340,7 +340,7 @@ class DistributionTestBase(test.TestCase):
       self, strategy, input_fn, expected_values, ignore_order=False):
     assert_same = self.assertCountEqual if ignore_order else self.assertEqual
 
-    iterable = strategy.experimental_distribute_datasets_from_function(input_fn)
+    iterable = strategy.distribute_datasets_from_function(input_fn)
     if context.executing_eagerly():
       iterator = iter(iterable)
 
diff --git a/tensorflow/python/distribute/tpu_strategy.py b/tensorflow/python/distribute/tpu_strategy.py
index 0d5ab9d01cd..1a3d49a2032 100644
--- a/tensorflow/python/distribute/tpu_strategy.py
+++ b/tensorflow/python/distribute/tpu_strategy.py
@@ -125,7 +125,7 @@ class TPUStrategyV2(distribute_lib.Strategy):
   `strategy.run` is called inside a `tf.function` if eager
   behavior is enabled. See more details in https://www.tensorflow.org/guide/tpu.
 
-  `experimental_distribute_datasets_from_function` and
+  `distribute_datasets_from_function` and
   `experimental_distribute_dataset` APIs can be used to distribute the dataset
   across the TPU workers when writing your own training loop. If you are using
   `fit` and `compile` methods available in `tf.keras.Model`, then Keras will
@@ -144,7 +144,7 @@ class TPUStrategyV2(distribute_lib.Strategy):
   ...   y = np.random.randint(2, size=(2, 1))
   ...   dataset = tf.data.Dataset.from_tensor_slices((x, y))
   ...   return dataset.repeat().batch(1, drop_remainder=True)
-  >>> dist_dataset = strategy.experimental_distribute_datasets_from_function(
+  >>> dist_dataset = strategy.distribute_datasets_from_function(
   ...     dataset_fn)
   >>> iterator = iter(dist_dataset)
 
@@ -190,7 +190,7 @@ class TPUStrategyV2(distribute_lib.Strategy):
   ...   # Add operation will be executed on logical device 0.
   ...   output = strategy.experimental_assign_to_logical_device(output, 0)
   ...   return output
-  >>> dist_dataset = strategy.experimental_distribute_datasets_from_function(
+  >>> dist_dataset = strategy.distribute_datasets_from_function(
   ...     dataset_fn)
   >>> iterator = iter(dist_dataset)
   >>> strategy.run(step_fn, args=(next(iterator),))
@@ -229,7 +229,7 @@ class TPUStrategyV2(distribute_lib.Strategy):
     `tf.distribute.DistributedValues`, such as those produced by a
     `tf.distribute.DistributedDataset` from
     `tf.distribute.Strategy.experimental_distribute_dataset` or
-    `tf.distribute.Strategy.experimental_distribute_datasets_from_function`,
+    `tf.distribute.Strategy.distribute_datasets_from_function`,
     when `fn` is executed on a particular replica, it will be executed with the
     component of `tf.distribute.DistributedValues` that correspond to that
     replica.
@@ -811,8 +811,7 @@ class TPUExtended(distribute_lib.StrategyExtendedV1):
         self._container_strategy(),
         split_batch_by=self._num_replicas_in_sync)
 
-  def _experimental_distribute_datasets_from_function(self, dataset_fn,
-                                                      options):
+  def _distribute_datasets_from_function(self, dataset_fn, options):
     input_workers = self._get_input_workers(options)
     input_contexts = []
     num_workers = input_workers.num_workers
diff --git a/tensorflow/python/distribute/tpu_strategy_test.py b/tensorflow/python/distribute/tpu_strategy_test.py
index c2aa68a0785..70f05a3bb9c 100644
--- a/tensorflow/python/distribute/tpu_strategy_test.py
+++ b/tensorflow/python/distribute/tpu_strategy_test.py
@@ -509,10 +509,9 @@ class TPUStrategyTest(test.TestCase, parameterized.TestCase):
       return dataset.map(make_sparse)
 
     dataset = iter(
-        strategy.experimental_distribute_datasets_from_function(
+        strategy.distribute_datasets_from_function(
             dataset_fn,
-            distribute_lib.InputOptions(
-                experimental_prefetch_to_device=False)))
+            distribute_lib.InputOptions(experimental_prefetch_to_device=False)))
 
     sparse, result = sparse_lookup(dataset)
 
@@ -560,10 +559,9 @@ class TPUStrategyTest(test.TestCase, parameterized.TestCase):
       return dataset.map(make_sparse)
 
     dataset = iter(
-        strategy.experimental_distribute_datasets_from_function(
+        strategy.distribute_datasets_from_function(
             dataset_fn,
-            distribute_lib.InputOptions(
-                experimental_prefetch_to_device=False)))
+            distribute_lib.InputOptions(experimental_prefetch_to_device=False)))
 
     output = sparse_lookup(dataset)
 
@@ -616,7 +614,7 @@ class TPUStrategyTest(test.TestCase, parameterized.TestCase):
       return dataset.map(make_sparse)
 
     dataset = iter(
-        strategy.experimental_distribute_datasets_from_function(
+        strategy.distribute_datasets_from_function(
             dataset_fn,
             options=distribute_lib.InputOptions(
                 experimental_prefetch_to_device=False)))
@@ -730,7 +728,7 @@ class TPUStrategyDataPrefetchTest(test.TestCase):
       return dataset.batch(strategy.num_replicas_in_sync)
 
     with self.assertRaisesRegex(ValueError, "TPUStrategy does not support"):
-      iter(strategy.experimental_distribute_datasets_from_function(dataset_fn))
+      iter(strategy.distribute_datasets_from_function(dataset_fn))
 
   def test_prefetch_to_device_ragged_dataset_fn(self):
     strategy = get_tpu_strategy()
@@ -745,7 +743,7 @@ class TPUStrategyDataPrefetchTest(test.TestCase):
       return dataset.batch(strategy.num_replicas_in_sync)
 
     with self.assertRaisesRegex(ValueError, "TPUStrategy does not support"):
-      iter(strategy.experimental_distribute_datasets_from_function(dataset_fn))
+      iter(strategy.distribute_datasets_from_function(dataset_fn))
 
 
 class TPUStrategyDistributionTest(
diff --git a/tensorflow/python/keras/distribute/distribute_strategy_test.py b/tensorflow/python/keras/distribute/distribute_strategy_test.py
index 7825c732356..18485749b18 100644
--- a/tensorflow/python/keras/distribute/distribute_strategy_test.py
+++ b/tensorflow/python/keras/distribute/distribute_strategy_test.py
@@ -1732,10 +1732,8 @@ class TestDistributionStrategyWithKerasModels(test.TestCase,
         ds = ds.batch(5).repeat()
         return ds
 
-      ds = distribution.experimental_distribute_datasets_from_function(
-          make_dataset)
-      val_ds = distribution.experimental_distribute_datasets_from_function(
-          make_dataset)
+      ds = distribution.distribute_datasets_from_function(make_dataset)
+      val_ds = distribution.distribute_datasets_from_function(make_dataset)
 
       model.fit(
           ds,
diff --git a/tensorflow/python/tpu/tpu_embedding_v2.py b/tensorflow/python/tpu/tpu_embedding_v2.py
index ededc63e860..1417824e53c 100644
--- a/tensorflow/python/tpu/tpu_embedding_v2.py
+++ b/tensorflow/python/tpu/tpu_embedding_v2.py
@@ -152,7 +152,7 @@ class TPUEmbedding(tracking.AutoTrackable):
 
   ```python
   distributed_dataset = (
-      strategy.experimental_distribute_datasets_from_function(
+      strategy.distribute_datasets_from_function(
           dataset_fn=...,
           options=tf.distribute.InputOptions(
               experimental_prefetch_to_device=False))
@@ -583,7 +583,7 @@ class TPUEmbedding(tracking.AutoTrackable):
       embedding = tf.tpu.experimental.embedding.TPUEmbedding(...)
 
     distributed_dataset = (
-        strategy.experimental_distribute_datasets_from_function(
+        strategy.distribute_datasets_from_function(
             dataset_fn=...,
             options=tf.distribute.InputOptions(
                 experimental_prefetch_to_device=False))
@@ -680,7 +680,7 @@ class TPUEmbedding(tracking.AutoTrackable):
       embedding = tf.tpu.experimental.embedding.TPUEmbedding(...)
 
     distributed_dataset = (
-        strategy.experimental_distribute_datasets_from_function(
+        strategy.distribute_datasets_from_function(
             dataset_fn=...,
             options=tf.distribute.InputOptions(
                 experimental_prefetch_to_device=False))
@@ -1125,7 +1125,7 @@ class TPUEmbedding(tracking.AutoTrackable):
     features matches the per core batch size. This will automatically happen if
     your input dataset is batched to the global batch size and you use
     `tf.distribute.TPUStrategy`'s `experimental_distribute_dataset`
-    or if you use `experimental_distribute_datasets_from_function` and batch
+    or if you use `distribute_datasets_from_function` and batch
     to the per core batch size computed by the context passed to your input
     function.
 
@@ -1135,7 +1135,7 @@ class TPUEmbedding(tracking.AutoTrackable):
       embedding = tf.tpu.experimental.embedding.TPUEmbedding(...)
 
     distributed_dataset = (
-        strategy.experimental_distribute_datasets_from_function(
+        strategy.distribute_datasets_from_function(
             dataset_fn=...,
             options=tf.distribute.InputOptions(
                 experimental_prefetch_to_device=False))
diff --git a/tensorflow/python/tpu/tpu_embedding_v2_correctness_test.py b/tensorflow/python/tpu/tpu_embedding_v2_correctness_test.py
index 7a9a727d956..8960d907be7 100644
--- a/tensorflow/python/tpu/tpu_embedding_v2_correctness_test.py
+++ b/tensorflow/python/tpu/tpu_embedding_v2_correctness_test.py
@@ -427,7 +427,7 @@ class TPUEmbeddingCorrectness(parameterized.TestCase, test.TestCase):
     strategy, mid_level_api, _ = self._create_strategy_and_mid_level('sgd')
 
     input_fn = self._create_dense_input_fn(strategy)
-    dist = strategy.experimental_distribute_datasets_from_function(
+    dist = strategy.distribute_datasets_from_function(
         input_fn,
         options=distribute_lib.InputOptions(
             experimental_prefetch_to_device=False))
diff --git a/tensorflow/python/tpu/tpu_embedding_v2_test.py b/tensorflow/python/tpu/tpu_embedding_v2_test.py
index 5e081d6f9ef..4ad26ce5742 100644
--- a/tensorflow/python/tpu/tpu_embedding_v2_test.py
+++ b/tensorflow/python/tpu/tpu_embedding_v2_test.py
@@ -556,7 +556,7 @@ class TPUEmbeddingTest(parameterized.TestCase, test.TestCase):
     strategy, mid_level_api, _ = self._create_strategy_and_mid_level('sgd')
 
     input_fn = self._create_dense_input_fn(strategy, include_weights=True)
-    dist = strategy.experimental_distribute_datasets_from_function(
+    dist = strategy.distribute_datasets_from_function(
         input_fn,
         options=distribute_lib.InputOptions(
             experimental_prefetch_to_device=False))
@@ -744,8 +744,7 @@ class TPUEmbeddingTest(parameterized.TestCase, test.TestCase):
     strategy, mid_level_api, _ = self._create_strategy_and_mid_level('sgd')
 
     input_fn = self._create_dense_input_fn(strategy)
-    sparse_iter = iter(strategy.experimental_distribute_datasets_from_function(
-        input_fn))
+    sparse_iter = iter(strategy.distribute_datasets_from_function(input_fn))
 
     @def_function.function
     def test_fn():
@@ -768,8 +767,7 @@ class TPUEmbeddingTest(parameterized.TestCase, test.TestCase):
     strategy, mid_level_api, _ = self._create_strategy_and_mid_level('sgd')
 
     input_fn = self._create_dense_input_fn(strategy)
-    sparse_iter = iter(strategy.experimental_distribute_datasets_from_function(
-        input_fn))
+    sparse_iter = iter(strategy.distribute_datasets_from_function(input_fn))
 
     @def_function.function
     def test_fn():
@@ -1127,7 +1125,8 @@ class TPUEmbeddingTest(parameterized.TestCase, test.TestCase):
     def input_fn(ctx):
       del ctx
       return dataset_ops.DatasetV2.from_tensors(feature).repeat()
-    dist = strategy.experimental_distribute_datasets_from_function(
+
+    dist = strategy.distribute_datasets_from_function(
         input_fn,
         options=distribute_lib.InputOptions(
             experimental_prefetch_to_device=False))
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.distribute.-mirrored-strategy.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.distribute.-mirrored-strategy.pbtxt
index 85dd7f5eaa6..009e612f94f 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.distribute.-mirrored-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.distribute.-mirrored-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.distribute.-one-device-strategy.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.distribute.-one-device-strategy.pbtxt
index 23e03ceab02..e6729e82004 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.distribute.-one-device-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.distribute.-one-device-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.distribute.-strategy.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.distribute.-strategy.pbtxt
index 7fbd9dded22..00964c7cbb0 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.distribute.-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.distribute.-strategy.pbtxt
@@ -27,6 +27,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt
index 2f7ba2db15c..b360ed1f628 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt
index dac5652c7fd..598a9dbc15b 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt
index f63c16dec5a..0e78cb93209 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt
index 53d5b756568..4cbcab923c6 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt
@@ -32,6 +32,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-mirrored-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-mirrored-strategy.pbtxt
index 5e17d5c8752..598c01c6da0 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-mirrored-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-mirrored-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-one-device-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-one-device-strategy.pbtxt
index aa23fddab08..5b044576d14 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-one-device-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-one-device-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-strategy.pbtxt
index 611247e3ab9..a8ebaa87590 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-strategy.pbtxt
@@ -27,6 +27,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-t-p-u-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-t-p-u-strategy.pbtxt
index 505c77be2e2..3a94e8b9fa4 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.-t-p-u-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.-t-p-u-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_assign_to_logical_device"
     argspec: "args=[\'self\', \'tensor\', \'logical_device_id\'], varargs=None, keywords=None, defaults=None"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt
index 7fd7878c45c..290d834305a 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-central-storage-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt
index 66e1fb34bb5..2245eb4b122 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-multi-worker-mirrored-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt
index 3d8265ee720..707d7281a5c 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-parameter-server-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt
index 8956d528b3a..a2adcea87e6 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.distribute.experimental.-t-p-u-strategy.pbtxt
@@ -28,6 +28,10 @@ tf_class {
     name: "configure"
     argspec: "args=[\'self\', \'session_config\', \'cluster_spec\', \'task_type\', \'task_id\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
   }
+  member_method {
+    name: "distribute_datasets_from_function"
+    argspec: "args=[\'self\', \'dataset_fn\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "experimental_distribute_dataset"
     argspec: "args=[\'self\', \'dataset\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "