diff --git a/RELEASE.md b/RELEASE.md
index c716a7f36de..876ef314f1a 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -141,6 +141,10 @@ This release contains contributions from many people at Google, as well as:
         file is a protobuf containing the "fingerprint" of the SavedModel. See
         the [RFC](https://github.com/tensorflow/community/pull/415) for more
         details regarding its design and properties.
+  
+*   `tf.data`:
+    *   Graduated experimental APIs:
+        * [`tf.data.Dataset.ragged_batch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#ragged_batch), which batches elements of `tf.data.Dataset`s into `tf.RaggedTensor`s.
 
 ## Bug Fixes and Other Changes
 
diff --git a/tensorflow/python/data/experimental/kernel_tests/BUILD b/tensorflow/python/data/experimental/kernel_tests/BUILD
index a254ae26f5f..a86a682ece1 100644
--- a/tensorflow/python/data/experimental/kernel_tests/BUILD
+++ b/tensorflow/python/data/experimental/kernel_tests/BUILD
@@ -147,22 +147,6 @@ tf_py_test(
     ],
 )
 
-tf_py_test(
-    name = "dense_to_ragged_batch_test",
-    size = "small",
-    srcs = ["dense_to_ragged_batch_test.py"],
-    shard_count = 4,
-    deps = [
-        "//tensorflow/python:array_ops",
-        "//tensorflow/python:client_testlib",
-        "//tensorflow/python:dtypes",
-        "//tensorflow/python:errors",
-        "//tensorflow/python/data/kernel_tests:test_base",
-        "//tensorflow/python/data/ops:dataset_ops",
-        "//third_party/py/numpy",
-    ],
-)
-
 tf_py_test(
     name = "dense_to_sparse_batch_test",
     size = "medium",
diff --git a/tensorflow/python/data/experimental/ops/batching.py b/tensorflow/python/data/experimental/ops/batching.py
index da58ff1f8dc..1bc965d88fb 100644
--- a/tensorflow/python/data/experimental/ops/batching.py
+++ b/tensorflow/python/data/experimental/ops/batching.py
@@ -13,7 +13,6 @@
 # limitations under the License.
 # ==============================================================================
 """Batching dataset transformations."""
-from tensorflow.python.data.ops import batch_op
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.ops import structured_function
 from tensorflow.python.data.util import convert
@@ -22,15 +21,14 @@ from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import sparse_tensor
 from tensorflow.python.framework import tensor_shape
-from tensorflow.python.framework import tensor_spec
 from tensorflow.python.framework import tensor_util
 from tensorflow.python.ops import gen_experimental_dataset_ops as ged_ops
-from tensorflow.python.ops.ragged import ragged_tensor
 from tensorflow.python.util import deprecation
 from tensorflow.python.util.tf_export import tf_export
 
 
 @tf_export("data.experimental.dense_to_ragged_batch")
+@deprecation.deprecated(None, "Use `tf.data.Dataset.ragged_batch` instead.")
 def dense_to_ragged_batch(batch_size,
                           drop_remainder=False,
                           row_splits_dtype=dtypes.int64):
@@ -87,11 +85,8 @@ def dense_to_ragged_batch(batch_size,
   Returns:
     Dataset: A `Dataset`.
   """
-
   def _apply_fn(dataset):
-    ragged_dataset = _DenseToRaggedDataset(dataset, row_splits_dtype)
-    return batch_op.BatchDataset(
-        ragged_dataset, batch_size=batch_size, drop_remainder=drop_remainder)
+    return dataset.ragged_batch(batch_size, drop_remainder, row_splits_dtype)
 
   return _apply_fn
 
@@ -381,78 +376,3 @@ class _MapAndBatchDataset(dataset_ops.UnaryDataset):
   @property
   def element_spec(self):
     return self._element_spec
-
-
-class _DenseToRaggedDataset(dataset_ops.UnaryDataset):
-  """A `Dataset` that encodes dense inputs as ragged (w/ ragged_rank=0).
-
-  In particular:
-
-  * Any tf.Tensor elements with rank>0 are encoded as ragged tensors with
-    ragged_rank=0.  This allows tensors with varying shape to be batched
-    together.
-  * Any other elements are left as-is.
-  """
-
-  def __init__(self, input_dataset, row_splits_dtype):
-    """Constructs a new _DenseToRaggedDataset.
-
-    Args:
-      input_dataset: The dataset whose tf.Tensor elements should be made ragged.
-      row_splits_dtype: The dtype that should be used for the `row_splits` of
-        any new ragged tensors.  Existing `tf.RaggedTensor` elements do *not*
-        have their row_splits dtype changed.
-    """
-    # Replace each TensorSpec in the input dataset's structure with a
-    # corresponding RaggedTensorSpec.
-    def to_ragged_spec(spec):
-      """Returns the new spec based on RaggedTensors."""
-      if (not isinstance(spec, tensor_spec.TensorSpec) or
-          spec.shape.rank is None or
-          spec.shape.is_fully_defined()):
-        return spec
-      else:
-        ragged_rank = max([
-            axis for (axis, size) in enumerate(spec.shape.as_list())
-            if size is None
-        ])
-        return ragged_tensor.RaggedTensorSpec(
-            shape=spec.shape,
-            dtype=spec.dtype,
-            ragged_rank=ragged_rank,
-            row_splits_dtype=row_splits_dtype)
-
-    self._structure = nest.map_structure(to_ragged_spec,
-                                         input_dataset.element_spec)
-
-    # Replace each tf.Tensor value in the input dataset with a variant-encoded
-    # RaggedTensor. Since we're updating the corresponding structure to be
-    # a RaggedTensorSpec, this variant-encoded tensor will be decoded with
-    # RaggedTensorSpec._from_tensor_list.
-    def to_ragged_variant(value):
-      """Re-encode Tensors as RaggedTensors."""
-      if (not isinstance(value, ops.Tensor) or
-          value.shape.rank is None or
-          value.shape.is_fully_defined()):
-        return value
-      else:
-        spec = to_ragged_spec(tensor_spec.TensorSpec.from_tensor(value))
-        if spec._ragged_rank > 0:  # pylint: disable=protected-access
-          value = ragged_tensor.RaggedTensor.from_tensor(
-              value, ragged_rank=spec._ragged_rank)  # pylint: disable=protected-access
-        return spec._to_tensor_list(value)[0]  # pylint: disable=protected-access
-
-    # Tuples are automatically unpacked by `dataset.map` so we repack them.
-    if structured_function._should_unpack(input_dataset.element_spec):  # pylint: disable=protected-access
-      map_fn = lambda *value: nest.map_structure(to_ragged_variant, value)
-    else:
-      map_fn = lambda value: nest.map_structure(to_ragged_variant, value)
-
-    self._mapped_dataset = input_dataset.map(map_fn)
-
-    variant = self._mapped_dataset._variant_tensor  # pylint: disable=protected-access
-    super(_DenseToRaggedDataset, self).__init__(input_dataset, variant)
-
-  @property
-  def element_spec(self):
-    return self._structure
diff --git a/tensorflow/python/data/kernel_tests/BUILD b/tensorflow/python/data/kernel_tests/BUILD
index 607bcd5680c..33dac535c12 100644
--- a/tensorflow/python/data/kernel_tests/BUILD
+++ b/tensorflow/python/data/kernel_tests/BUILD
@@ -754,6 +754,22 @@ tf_py_test(
     ],
 )
 
+tf_py_test(
+    name = "ragged_batch_test",
+    size = "small",
+    srcs = ["ragged_batch_test.py"],
+    shard_count = 4,
+    deps = [
+        "//tensorflow/python:array_ops",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:dtypes",
+        "//tensorflow/python:errors",
+        "//tensorflow/python/data/kernel_tests:test_base",
+        "//tensorflow/python/data/ops:dataset_ops",
+        "//third_party/py/numpy",
+    ],
+)
+
 tf_py_test(
     name = "random_test",
     size = "small",
diff --git a/tensorflow/python/data/experimental/kernel_tests/dense_to_ragged_batch_test.py b/tensorflow/python/data/kernel_tests/ragged_batch_test.py
similarity index 95%
rename from tensorflow/python/data/experimental/kernel_tests/dense_to_ragged_batch_test.py
rename to tensorflow/python/data/kernel_tests/ragged_batch_test.py
index d2ada96b086..7791cc0da55 100644
--- a/tensorflow/python/data/experimental/kernel_tests/dense_to_ragged_batch_test.py
+++ b/tensorflow/python/data/kernel_tests/ragged_batch_test.py
@@ -12,11 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-"""Tests for `tf.data.experimental.dense_to_ragged_batch`."""
+"""Tests for `tf.data.Dataset.ragged_batch`."""
 from absl.testing import parameterized
 import numpy as np
 
-from tensorflow.python.data.experimental.ops import batching
 from tensorflow.python.data.kernel_tests import test_base
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
@@ -118,8 +117,7 @@ class RaggedBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
             for _ in range(nrows)]
 
     # Batch the dataset, and check that batches match slices from `rows`.
-    batched_dataset = dataset.apply(
-        batching.dense_to_ragged_batch(batch_size, drop_remainder))
+    batched_dataset = dataset.ragged_batch(batch_size, drop_remainder)
     get_next = self.getNext(batched_dataset)
     for start_row in range(0, nrows, batch_size):
       end_row = start_row + batch_size
@@ -155,7 +153,7 @@ class RaggedBatchTest(test_base.DatasetTestBase, parameterized.TestCase):
 
     dataset = dataset_ops.Dataset.from_tensor_slices(np.arange(nrows))
     dataset = dataset.map(make_structure)
-    dataset = dataset.apply(batching.dense_to_ragged_batch(batch_size))
+    dataset = dataset.ragged_batch(batch_size)
     get_next = self.getNext(dataset)
 
     for i in range(0, nrows, batch_size):
diff --git a/tensorflow/python/data/ops/BUILD b/tensorflow/python/data/ops/BUILD
index d135909cc27..c3980e0b727 100644
--- a/tensorflow/python/data/ops/BUILD
+++ b/tensorflow/python/data/ops/BUILD
@@ -53,6 +53,7 @@ py_library(
         ":iterator_ops",
         ":load_ops",
         ":options",
+        ":ragged_batch_op",
         ":rebatch_op",
         ":save_ops",
         ":structured_function",
@@ -137,6 +138,23 @@ py_library(
     ],
 )
 
+py_library(
+    name = "ragged_batch_op",
+    srcs = ["ragged_batch_op.py"],
+    srcs_version = "PY3",
+    deps = [
+        "//tensorflow/python:dtypes",
+        "//tensorflow/python:experimental_dataset_ops_gen",
+        "//tensorflow/python:framework_ops",
+        "//tensorflow/python:tensor_shape",
+        "//tensorflow/python:tensor_util",
+        "//tensorflow/python:util",
+        "//tensorflow/python/data/util:convert",
+        "//tensorflow/python/data/util:nest",
+        "//tensorflow/python/data/util:structure",
+    ],
+)
+
 py_library(
     name = "save_ops",
     srcs = ["save_op.py"],
diff --git a/tensorflow/python/data/ops/dataset_ops.py b/tensorflow/python/data/ops/dataset_ops.py
index d81d0027871..fcc742010c7 100644
--- a/tensorflow/python/data/ops/dataset_ops.py
+++ b/tensorflow/python/data/ops/dataset_ops.py
@@ -2126,6 +2126,67 @@ class DatasetV2(
         drop_remainder,
         name=name)
 
+  def ragged_batch(self,
+                   batch_size,
+                   drop_remainder=False,
+                   row_splits_dtype=dtypes.int64,
+                   name=None):
+    """Combines consecutive elements of this dataset into `tf.RaggedTensor`s.
+
+    Like `tf.data.Dataset.batch`, the components of the resulting element will
+    have an additional outer dimension, which will be `batch_size` (or
+    `N % batch_size` for the last element if `batch_size` does not divide the
+    number of input elements `N` evenly and `drop_remainder` is `False`). If
+    your program depends on the batches having the same outer dimension, you
+    should set the `drop_remainder` argument to `True` to prevent the smaller
+    batch from being produced.
+
+    Unlike `tf.data.Dataset.batch`, the input elements to be batched may have
+    different shapes:
+
+    *  If an input element is a `tf.Tensor` whose static `tf.TensorShape` is
+    fully defined, then it is batched as normal.
+    *  If an input element is a `tf.Tensor` whose static `tf.TensorShape`
+    contains one or more axes with unknown size (i.e., `shape[i]=None`), then
+    the output will contain a `tf.RaggedTensor` that is ragged up to any of such
+    dimensions.
+    *  If an input element is a `tf.RaggedTensor` or any other type, then it is
+    batched as normal.
+
+    Example:
+
+    >>> dataset = tf.data.Dataset.range(6)
+    >>> dataset = dataset.map(lambda x: tf.range(x))
+    >>> dataset.element_spec.shape
+    TensorShape([None])
+    >>> dataset = dataset.ragged_batch(2)
+    >>> for batch in dataset:
+    ...   print(batch)
+    <tf.RaggedTensor [[], [0]]>
+    <tf.RaggedTensor [[0, 1], [0, 1, 2]]>
+    <tf.RaggedTensor [[0, 1, 2, 3], [0, 1, 2, 3, 4]]>
+
+    Args:
+      batch_size: A `tf.int64` scalar `tf.Tensor`, representing the number of
+        consecutive elements of this dataset to combine in a single batch.
+      drop_remainder: (Optional.) A `tf.bool` scalar `tf.Tensor`, representing
+        whether the last batch should be dropped in the case it has fewer than
+        `batch_size` elements; the default behavior is not to drop the smaller
+        batch.
+      row_splits_dtype: The dtype that should be used for the `row_splits` of
+        any new ragged tensors.  Existing `tf.RaggedTensor` elements do not have
+        their row_splits dtype changed.
+      name: (Optional.) A string indicating a name for the `tf.data` operation.
+
+    Returns:
+      A new `Dataset` with the transformation applied as described above.
+    """
+    # Loaded lazily due to a circular dependency (dataset_ops ->
+    # ragged_batch_op -> dataset_ops).
+    from tensorflow.python.data.ops import ragged_batch_op  # pylint: disable=g-import-not-at-top
+    return ragged_batch_op.ragged_batch(self, batch_size, drop_remainder,
+                                        row_splits_dtype, name)
+
   def map(self,
           map_func,
           num_parallel_calls=None,
diff --git a/tensorflow/python/data/ops/ragged_batch_op.py b/tensorflow/python/data/ops/ragged_batch_op.py
new file mode 100644
index 00000000000..1868925873d
--- /dev/null
+++ b/tensorflow/python/data/ops/ragged_batch_op.py
@@ -0,0 +1,109 @@
+# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""The implementation of `tf.data.Dataset.ragged_batch`."""
+from tensorflow.python.data.ops import batch_op
+from tensorflow.python.data.ops import dataset_ops
+from tensorflow.python.data.ops import structured_function
+from tensorflow.python.data.util import nest
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import ops
+from tensorflow.python.framework import tensor_spec
+from tensorflow.python.ops.ragged import ragged_tensor
+
+
+def ragged_batch(self,
+                 batch_size,
+                 drop_remainder=False,
+                 row_splits_dtype=dtypes.int64,
+                 name=None):
+  ragged_dataset = _DenseToRaggedDataset(self, row_splits_dtype, name)
+  return batch_op.BatchDataset(
+      ragged_dataset, batch_size=batch_size, drop_remainder=drop_remainder)
+
+
+class _DenseToRaggedDataset(dataset_ops.UnaryDataset):
+  """A `Dataset` that encodes dense inputs as ragged (w/ ragged_rank=0).
+
+  In particular:
+
+  * Any tf.Tensor elements with rank>0 are encoded as ragged tensors with
+    ragged_rank=0.  This allows tensors with varying shape to be batched
+    together.
+  * Any other elements are left as-is.
+  """
+
+  def __init__(self, input_dataset, row_splits_dtype, name=None):
+    """Constructs a new _DenseToRaggedDataset.
+
+    Args:
+      input_dataset: The dataset whose tf.Tensor elements should be made ragged.
+      row_splits_dtype: The dtype that should be used for the `row_splits` of
+        any new ragged tensors.  Existing `tf.RaggedTensor` elements do *not*
+        have their row_splits dtype changed.
+      name: (Optional.) A string indicating a name for the `tf.data` operation.
+    """
+    # Replace each TensorSpec in the input dataset's structure with a
+    # corresponding RaggedTensorSpec.
+    def to_ragged_spec(spec):
+      """Returns the new spec based on RaggedTensors."""
+      if (not isinstance(spec, tensor_spec.TensorSpec) or
+          spec.shape.rank is None or
+          spec.shape.is_fully_defined()):
+        return spec
+      else:
+        ragged_rank = max([
+            axis for (axis, size) in enumerate(spec.shape.as_list())
+            if size is None
+        ])
+        return ragged_tensor.RaggedTensorSpec(
+            shape=spec.shape,
+            dtype=spec.dtype,
+            ragged_rank=ragged_rank,
+            row_splits_dtype=row_splits_dtype)
+
+    self._structure = nest.map_structure(to_ragged_spec,
+                                         input_dataset.element_spec)
+
+    # Replace each tf.Tensor value in the input dataset with a variant-encoded
+    # RaggedTensor. Since we're updating the corresponding structure to be
+    # a RaggedTensorSpec, this variant-encoded tensor will be decoded with
+    # RaggedTensorSpec._from_tensor_list.
+    def to_ragged_variant(value):
+      """Re-encode Tensors as RaggedTensors."""
+      if (not isinstance(value, ops.Tensor) or
+          value.shape.rank is None or
+          value.shape.is_fully_defined()):
+        return value
+      else:
+        spec = to_ragged_spec(tensor_spec.TensorSpec.from_tensor(value))
+        if spec._ragged_rank > 0:  # pylint: disable=protected-access
+          value = ragged_tensor.RaggedTensor.from_tensor(
+              value, ragged_rank=spec._ragged_rank)  # pylint: disable=protected-access
+        return spec._to_tensor_list(value)[0]  # pylint: disable=protected-access
+
+    # Tuples are automatically unpacked by `dataset.map` so we repack them.
+    if structured_function._should_unpack(input_dataset.element_spec):  # pylint: disable=protected-access
+      map_fn = lambda *value: nest.map_structure(to_ragged_variant, value)
+    else:
+      map_fn = lambda value: nest.map_structure(to_ragged_variant, value)
+
+    self._mapped_dataset = input_dataset.map(map_fn)
+    self._name = name
+    variant = self._mapped_dataset._variant_tensor  # pylint: disable=protected-access
+    super(_DenseToRaggedDataset, self).__init__(input_dataset, variant)
+
+  @property
+  def element_spec(self):
+    return self._structure
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.data.-dataset.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.data.-dataset.pbtxt
index 09793fd81ce..cd18d209660 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.data.-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.data.-dataset.pbtxt
@@ -143,6 +143,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.data.-fixed-length-record-dataset.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.data.-fixed-length-record-dataset.pbtxt
index 50c35bcbcdd..51740951cec 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.data.-fixed-length-record-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.data.-fixed-length-record-dataset.pbtxt
@@ -145,6 +145,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.data.-t-f-record-dataset.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.data.-t-f-record-dataset.pbtxt
index 7c4b9fb2562..319ffa68ffb 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.data.-t-f-record-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.data.-t-f-record-dataset.pbtxt
@@ -145,6 +145,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.data.-text-line-dataset.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.data.-text-line-dataset.pbtxt
index a5966884153..d303899d9f7 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.data.-text-line-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.data.-text-line-dataset.pbtxt
@@ -145,6 +145,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-csv-dataset.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-csv-dataset.pbtxt
index a5817d5d09d..b4adfd7c94c 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-csv-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-csv-dataset.pbtxt
@@ -145,6 +145,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-random-dataset.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-random-dataset.pbtxt
index bd4abcbb0a1..b347b1bcdda 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-random-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-random-dataset.pbtxt
@@ -145,6 +145,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-sql-dataset.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-sql-dataset.pbtxt
index e6883494d8b..318f7746579 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-sql-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-sql-dataset.pbtxt
@@ -145,6 +145,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.data.-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.data.-dataset.pbtxt
index 6f93210ff22..109736eeca2 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.data.-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.data.-dataset.pbtxt
@@ -110,6 +110,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.data.-fixed-length-record-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.data.-fixed-length-record-dataset.pbtxt
index 5bd5aa8647e..4bf9ff2ea16 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.data.-fixed-length-record-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.data.-fixed-length-record-dataset.pbtxt
@@ -112,6 +112,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.data.-t-f-record-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.data.-t-f-record-dataset.pbtxt
index 4822e276b94..f29a2a38568 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.data.-t-f-record-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.data.-t-f-record-dataset.pbtxt
@@ -111,6 +111,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.data.-text-line-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.data.-text-line-dataset.pbtxt
index 1f2b6f44764..02ab7ca30df 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.data.-text-line-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.data.-text-line-dataset.pbtxt
@@ -112,6 +112,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-csv-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-csv-dataset.pbtxt
index 397beba8f08..635e6eb27ab 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-csv-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-csv-dataset.pbtxt
@@ -112,6 +112,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-random-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-random-dataset.pbtxt
index 52911a8e1b7..c05ff5c583b 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-random-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-random-dataset.pbtxt
@@ -113,6 +113,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-sql-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-sql-dataset.pbtxt
index 5724e284469..fd853758921 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-sql-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-sql-dataset.pbtxt
@@ -112,6 +112,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.experimental.dtensor.-d-tensor-dataset.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.experimental.dtensor.-d-tensor-dataset.pbtxt
index cffcddb10b6..41af206fd97 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.experimental.dtensor.-d-tensor-dataset.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.experimental.dtensor.-d-tensor-dataset.pbtxt
@@ -113,6 +113,10 @@ tf_class {
     name: "prefetch"
     argspec: "args=[\'self\', \'buffer_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ragged_batch"
+    argspec: "args=[\'self\', \'batch_size\', \'drop_remainder\', \'row_splits_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \"<dtype: \'int64\'>\", \'None\'], "
+  }
   member_method {
     name: "random"
     argspec: "args=[\'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "