diff --git a/tensorflow/contrib/data/python/ops/readers.py b/tensorflow/contrib/data/python/ops/readers.py
index 2e759f09a1f..1ea118607d2 100644
--- a/tensorflow/contrib/data/python/ops/readers.py
+++ b/tensorflow/contrib/data/python/ops/readers.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.experimental.ops import readers
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.ops import readers as core_readers
@@ -390,8 +391,12 @@ class LMDBDataset(dataset_ops.DatasetSource):
     """
     self._filenames = ops.convert_to_tensor(
         filenames, dtype=dtypes.string, name="filenames")
-    variant_tensor = gen_experimental_dataset_ops.experimental_lmdb_dataset(
-        self._filenames, **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = gen_experimental_dataset_ops.lmdb_dataset(
+          self._filenames, **self._flat_structure)
+    else:
+      variant_tensor = gen_experimental_dataset_ops.experimental_lmdb_dataset(
+          self._filenames, **self._flat_structure)
     super(LMDBDataset, self).__init__(variant_tensor)
 
   @property
diff --git a/tensorflow/contrib/data/python/ops/sliding.py b/tensorflow/contrib/data/python/ops/sliding.py
index 672ead9c117..c329b6559f9 100644
--- a/tensorflow/contrib/data/python/ops/sliding.py
+++ b/tensorflow/contrib/data/python/ops/sliding.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
 from tensorflow.python.framework import dtypes
@@ -41,12 +42,20 @@ class _SlideDataset(dataset_ops.UnaryDataset):
     input_structure = dataset_ops.get_structure(input_dataset)
     self._element_spec = nest.map_structure(
         lambda component_spec: component_spec._batch(None), input_structure)  # pylint: disable=protected-access
-    variant_tensor = ged_ops.experimental_sliding_window_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        window_size=self._window_size,
-        window_shift=self._window_shift,
-        window_stride=self._window_stride,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.sliding_window_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          window_size=self._window_size,
+          window_shift=self._window_shift,
+          window_stride=self._window_stride,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_sliding_window_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          window_size=self._window_size,
+          window_shift=self._window_shift,
+          window_stride=self._window_stride,
+          **self._flat_structure)
     super(_SlideDataset, self).__init__(input_dataset, variant_tensor)
 
   @property
diff --git a/tensorflow/core/api_def/base_api/api_def_AssertNextDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_AssertNextDataset.pbtxt
new file mode 100644
index 00000000000..c97b807713f
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_AssertNextDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "AssertNextDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_AutoShardDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_AutoShardDataset.pbtxt
new file mode 100644
index 00000000000..403499e9b6f
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_AutoShardDataset.pbtxt
@@ -0,0 +1,32 @@
+op {
+  graph_op_name: "AutoShardDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "input_dataset"
+    description: <<END
+A variant tensor representing the input dataset.
+END
+  }
+  in_arg {
+  name: "num_workers"
+  description: <<END
+A scalar representing the number of workers to distribute this dataset across.
+END
+  }
+  in_arg {
+  name: "index"
+  description: <<END
+A scalar representing the index of the current worker out of num_workers.
+END
+  }
+  summary: "Creates a dataset that shards the input dataset."
+  description: <<END
+Creates a dataset that shards the input dataset by num_workers, returning a
+sharded dataset for the index-th worker. This attempts to automatically shard
+a dataset by examining the Dataset graph and inserting a shard op before the
+inputs to a reader Dataset (e.g. CSVDataset, TFRecordDataset).
+
+This dataset will throw a NotFound error if we cannot shard the dataset
+automatically.
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_BytesProducedStatsDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_BytesProducedStatsDataset.pbtxt
new file mode 100644
index 00000000000..65be450c93f
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_BytesProducedStatsDataset.pbtxt
@@ -0,0 +1,5 @@
+op {
+  graph_op_name: "BytesProducedStatsDataset"
+  visibility: HIDDEN
+  summary: "Records the bytes size of each element of `input_dataset` in a StatsAggregator."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_CSVDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_CSVDataset.pbtxt
new file mode 100644
index 00000000000..d21f236ccf6
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_CSVDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "CSVDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ChooseFastestDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_ChooseFastestDataset.pbtxt
new file mode 100644
index 00000000000..f35b8a0c120
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ChooseFastestDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "ChooseFastestDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_DatasetCardinality.pbtxt b/tensorflow/core/api_def/base_api/api_def_DatasetCardinality.pbtxt
new file mode 100644
index 00000000000..62a2296124f
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_DatasetCardinality.pbtxt
@@ -0,0 +1,21 @@
+op {
+  graph_op_name: "DatasetCardinality"
+  visibility: HIDDEN
+  in_arg {
+    name: "input_dataset"
+    description: <<END
+A variant tensor representing the dataset to return cardinality for.
+END
+  }
+  out_arg {
+    name: "cardinality"
+    description: <<END
+The cardinality of `input_dataset`. Named constants are used to represent
+infinite and unknown cardinality.
+END
+  }
+  summary: "Returns the cardinality of `input_dataset`."
+  description: <<END
+Returns the cardinality of `input_dataset`.
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_DatasetToTFRecord.pbtxt b/tensorflow/core/api_def/base_api/api_def_DatasetToTFRecord.pbtxt
new file mode 100644
index 00000000000..e1b8a9abdd2
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_DatasetToTFRecord.pbtxt
@@ -0,0 +1,24 @@
+op {
+  graph_op_name: "DatasetToTFRecord"
+  visibility: HIDDEN
+  in_arg {
+    name: "input_dataset"
+    description: <<END
+A variant tensor representing the dataset to write.
+END
+  }
+  in_arg {
+    name: "filename"
+    description: <<END
+A scalar string tensor representing the filename to use.
+END
+  }
+  in_arg {
+    name: "compression_type"
+    description: <<END
+A scalar string tensor containing either (i) the empty string (no
+compression), (ii) "ZLIB", or (iii) "GZIP".
+END
+  }
+  summary: "Writes the given dataset to the given file using the TFRecord format."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_DenseToSparseBatchDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_DenseToSparseBatchDataset.pbtxt
new file mode 100644
index 00000000000..2d9be1341b8
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_DenseToSparseBatchDataset.pbtxt
@@ -0,0 +1,26 @@
+op {
+  graph_op_name: "DenseToSparseBatchDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "input_dataset"
+    description: <<END
+A handle to an input dataset. Must have a single component.
+END
+  }
+  in_arg {
+    name: "batch_size"
+    description: <<END
+A scalar representing the number of elements to accumulate in a
+batch.
+END
+  }
+  in_arg {
+    name: "row_shape"
+    description: <<END
+A vector representing the dense shape of each row in the produced
+SparseTensor. The shape may be partially specified, using `-1` to indicate
+that a particular dimension should use the maximum size of all batch elements.
+END
+  }
+  summary: "Creates a dataset that batches input elements into a SparseTensor."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_DirectedInterleaveDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_DirectedInterleaveDataset.pbtxt
new file mode 100644
index 00000000000..e03aab6088e
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_DirectedInterleaveDataset.pbtxt
@@ -0,0 +1,21 @@
+op {
+  graph_op_name: "DirectedInterleaveDataset"
+  in_arg {
+    name: "selector_input_dataset"
+    description: <<END
+A dataset of scalar `DT_INT64` elements that determines which of the
+`N` data inputs should produce the next output element.
+END
+  }
+  in_arg {
+    name: "data_input_datasets"
+    description: <<END
+`N` datasets with the same type that will be interleaved according to
+the values of `selector_input_dataset`.
+END
+  }
+  summary: <<END
+A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
+END
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt
deleted file mode 100644
index fe266c111f2..00000000000
--- a/tensorflow/core/api_def/base_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt
+++ /dev/null
@@ -1,4 +0,0 @@
-op {
-  graph_op_name: "ExperimentalIdentityIndexedDataset"
-  visibility: HIDDEN
-}
diff --git a/tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetGet.pbtxt b/tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetGet.pbtxt
deleted file mode 100644
index e285f87e10b..00000000000
--- a/tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetGet.pbtxt
+++ /dev/null
@@ -1,4 +0,0 @@
-op {
-  graph_op_name: "ExperimentalIndexedDatasetGet"
-  visibility: HIDDEN
-}
diff --git a/tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt b/tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt
deleted file mode 100644
index 60c32473b5e..00000000000
--- a/tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt
+++ /dev/null
@@ -1,4 +0,0 @@
-op {
-  graph_op_name: "ExperimentalIndexedDatasetMaterialize"
-  visibility: HIDDEN
-}
diff --git a/tensorflow/core/api_def/base_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt b/tensorflow/core/api_def/base_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt
deleted file mode 100644
index 9676b9d284e..00000000000
--- a/tensorflow/core/api_def/base_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt
+++ /dev/null
@@ -1,4 +0,0 @@
-op {
-  graph_op_name: "ExperimentalMaterializedIndexDatasetHandle"
-  visibility: HIDDEN
-}
diff --git a/tensorflow/core/api_def/base_api/api_def_GroupByReducerDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_GroupByReducerDataset.pbtxt
new file mode 100644
index 00000000000..067ad4018b0
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_GroupByReducerDataset.pbtxt
@@ -0,0 +1,69 @@
+op {
+  graph_op_name: "GroupByReducerDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "input_dataset"
+    description: <<END
+A variant tensor representing the input dataset.
+END
+  }
+  in_arg {
+    name: "key_func_other_arguments"
+    description: <<END
+A list of tensors, typically values that were captured when
+building a closure for `key_func`.
+END
+  }
+  attr {
+    name: "key_func"
+    description: <<END
+A function mapping an element of `input_dataset`, concatenated
+with `key_func_other_arguments` to a scalar value of type DT_INT64.
+END
+  }
+  in_arg {
+    name: "init_func_other_arguments"
+    description: <<END
+A list of tensors, typically values that were captured when
+building a closure for `init_func`.
+END
+  }
+  attr {
+    name: "init_func"
+    description: <<END
+A function mapping a key of type DT_INT64, concatenated with
+`init_func_other_arguments` to the initial reducer state.
+END
+  }
+  in_arg {
+    name: "reduce_func_other_arguments"
+    description: <<END
+A list of tensors, typically values that were captured when
+building a closure for `reduce_func`.
+END
+  }
+  attr {
+    name: "reduce_func"
+    description: <<END
+A function mapping the current reducer state and an element of `input_dataset`,
+concatenated with `reduce_func_other_arguments` to a new reducer state.
+END
+  }
+  in_arg {
+    name: "finalize_func_other_arguments"
+    description: <<END
+A list of tensors, typically values that were captured when
+building a closure for `finalize_func`.
+END
+  }
+  attr {
+    name: "finalize_func"
+    description: <<END
+A function mapping the final reducer state to an output element.
+END
+  }
+  summary: "Creates a dataset that computes a group-by on `input_dataset`."
+  description: <<END
+Creates a dataset that computes a group-by on `input_dataset`.
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_GroupByWindowDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_GroupByWindowDataset.pbtxt
new file mode 100644
index 00000000000..592b0eb8f76
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_GroupByWindowDataset.pbtxt
@@ -0,0 +1,15 @@
+op {
+  graph_op_name: "GroupByWindowDataset"
+  visibility: HIDDEN
+  attr {
+    name: "key_func"
+    description: <<END
+A function mapping an element of `input_dataset`, concatenated
+with `key_func_other_arguments` to a scalar value of type DT_INT64.
+END
+  }
+  summary: "Creates a dataset that computes a windowed group-by on `input_dataset`."
+  description: <<END
+// TODO(mrry): Support non-int64 keys.
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_IgnoreErrorsDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_IgnoreErrorsDataset.pbtxt
new file mode 100644
index 00000000000..3f8ee80d28d
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_IgnoreErrorsDataset.pbtxt
@@ -0,0 +1,8 @@
+op {
+  graph_op_name: "IgnoreErrorsDataset"
+  summary: <<END
+Creates a dataset that contains the elements of `input_dataset` ignoring errors.
+END
+  visibility: HIDDEN
+}
+
diff --git a/tensorflow/core/api_def/base_api/api_def_IteratorGetDevice.pbtxt b/tensorflow/core/api_def/base_api/api_def_IteratorGetDevice.pbtxt
new file mode 100644
index 00000000000..51e229716c4
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_IteratorGetDevice.pbtxt
@@ -0,0 +1,8 @@
+op {
+  graph_op_name: "IteratorGetDevice"
+  summary: <<END
+Returns the name of the device on which `resource` has been placed.
+END
+  visibility: HIDDEN
+}
+
diff --git a/tensorflow/core/api_def/base_api/api_def_LMDBDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_LMDBDataset.pbtxt
new file mode 100644
index 00000000000..2994a874519
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_LMDBDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "LMDBDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_LatencyStatsDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_LatencyStatsDataset.pbtxt
new file mode 100644
index 00000000000..c54348b2b20
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_LatencyStatsDataset.pbtxt
@@ -0,0 +1,5 @@
+op {
+  graph_op_name: "LatencyStatsDataset"
+  visibility: HIDDEN
+  summary: "Records the latency of producing `input_dataset` elements in a StatsAggregator."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ExperimentalNumaMapAndBatchDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_MapAndBatchDataset.pbtxt
similarity index 85%
rename from tensorflow/core/api_def/base_api/api_def_ExperimentalNumaMapAndBatchDataset.pbtxt
rename to tensorflow/core/api_def/base_api/api_def_MapAndBatchDataset.pbtxt
index 243922d9694..2be79dabaa8 100644
--- a/tensorflow/core/api_def/base_api/api_def_ExperimentalNumaMapAndBatchDataset.pbtxt
+++ b/tensorflow/core/api_def/base_api/api_def_MapAndBatchDataset.pbtxt
@@ -1,5 +1,5 @@
 op {
-  graph_op_name: "ExperimentalNumaMapAndBatchDataset"
+  graph_op_name: "MapAndBatchDataset"
   visibility: HIDDEN
   in_arg {
     name: "input_dataset"
@@ -50,9 +50,5 @@ batches `batch_size` of them.
 
 Unlike a "MapDataset", which applies `f` sequentially, this dataset invokes up
 to `batch_size * num_parallel_batches` copies of `f` in parallel.
-
-Unlike "MapAndBatchDatasetV2", this dataset uses a NUMA-aware thread scheduling
-policy. Because it uses the single-threaded executor, it only supports the
-function-based control flow ops.
 END
 }
diff --git a/tensorflow/core/api_def/base_api/api_def_MatchingFilesDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_MatchingFilesDataset.pbtxt
new file mode 100644
index 00000000000..ab2a33108d1
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_MatchingFilesDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "MatchingFilesDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_MaxIntraOpParallelismDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_MaxIntraOpParallelismDataset.pbtxt
new file mode 100644
index 00000000000..46ceabd4cb2
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_MaxIntraOpParallelismDataset.pbtxt
@@ -0,0 +1,13 @@
+op {
+  graph_op_name: "MaxIntraOpParallelismDataset"
+  in_arg {
+    name: "max_intra_op_parallelism"
+    description: <<END
+Identifies the maximum intra-op parallelism to use.
+END
+  }
+  summary: <<END
+Creates a dataset that overrides the maximum intra-op parallelism.
+END
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_NonSerializableDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_NonSerializableDataset.pbtxt
new file mode 100644
index 00000000000..2a8abb0840a
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_NonSerializableDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "NonSerializableDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ParallelInterleaveDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_ParallelInterleaveDataset.pbtxt
new file mode 100644
index 00000000000..9599573c384
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ParallelInterleaveDataset.pbtxt
@@ -0,0 +1,22 @@
+op {
+  graph_op_name: "ParallelInterleaveDataset"
+  visibility: HIDDEN
+  attr {
+    name: "f"
+    description: <<END
+A function mapping elements of `input_dataset`, concatenated with
+`other_arguments`, to a Dataset variant that contains elements matching
+`output_types` and `output_shapes`.
+END
+  }
+  summary: "Creates a dataset that applies `f` to the outputs of `input_dataset`."
+  description: <<END
+The resulting dataset is similar to the `InterleaveDataset`, with the exception
+that if retrieving the next value from a dataset would cause the requester to
+block, it will skip that input dataset. This dataset is especially useful
+when loading data from a variable-latency datastores (e.g. HDFS, GCS), as it
+allows the training step to proceed so long as some data is available.
+
+!! WARNING !! This dataset is not deterministic!
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ParseExampleDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_ParseExampleDataset.pbtxt
new file mode 100644
index 00000000000..ede9ca4556c
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ParseExampleDataset.pbtxt
@@ -0,0 +1,70 @@
+op {
+  graph_op_name: "ParseExampleDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "dense_defaults"
+    description: <<END
+A dict mapping string keys to `Tensor`s.
+The keys of the dict must match the dense_keys of the feature.
+END
+  }
+  attr {
+    name: "sparse_keys"
+    description: <<END
+A list of string keys in the examples features.
+The results for these keys will be returned as `SparseTensor` objects.
+END
+  }
+  attr {
+    name: "dense_keys"
+    description: <<END
+A list of Ndense string Tensors (scalars).
+The keys expected in the Examples features associated with dense values.
+END
+  }
+  attr {
+    name: "sparse_types"
+    description: <<END
+A list of `DTypes` of the same length as `sparse_keys`.
+Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
+and `tf.string` (`BytesList`) are supported.
+END
+  }
+    attr {
+    name: "Tdense"
+    description: <<END
+A list of DTypes of the same length as `dense_keys`.
+Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
+and `tf.string` (`BytesList`) are supported.
+
+END
+  }
+  attr {
+    name: "dense_shapes"
+    description: <<END
+List of tuples with the same length as `dense_keys`.
+The shape of the data for each dense feature referenced by `dense_keys`.
+Required for any input tensors identified by `dense_keys`.  Must be
+either fully defined, or may contain an unknown first dimension.
+An unknown first dimension means the feature is treated as having
+a variable number of blocks, and the output shape along this dimension
+is considered unknown at graph build time.  Padding is applied for
+minibatch elements smaller than the maximum number of blocks for the
+given feature along this dimension.
+END
+  }
+    attr {
+    name: "output_types"
+    description: <<END
+The type list for the return values.
+END
+  }
+    attr {
+    name: "output_shapes"
+    description: <<END
+The list of shapes being produced.
+END
+  }
+   summary: "Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features."
+}
+
diff --git a/tensorflow/core/api_def/base_api/api_def_PrivateThreadPoolDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_PrivateThreadPoolDataset.pbtxt
new file mode 100644
index 00000000000..0b082117f1c
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_PrivateThreadPoolDataset.pbtxt
@@ -0,0 +1,13 @@
+op {
+  graph_op_name: "PrivateThreadPoolDataset"
+  in_arg {
+    name: "num_threads"
+    description: <<END
+Identifies the number of threads to use for the private threadpool.
+END
+  }
+  summary: <<END
+Creates a dataset that uses a custom thread pool to compute `input_dataset`.
+END
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_RandomDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_RandomDataset.pbtxt
new file mode 100644
index 00000000000..103e608ae8f
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_RandomDataset.pbtxt
@@ -0,0 +1,19 @@
+op {
+  graph_op_name: "RandomDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "seed"
+    description: <<END
+A scalar seed for the random number generator. If either seed or
+seed2 is set to be non-zero, the random number generator is seeded
+by the given seed.  Otherwise, a random seed is used.
+END
+  }
+  in_arg {
+    name: "seed2"
+    description: <<END
+A second scalar seed to avoid seed collision.
+END
+  }
+  summary: "Creates a Dataset that returns pseudorandom numbers."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_RebatchDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_RebatchDataset.pbtxt
new file mode 100644
index 00000000000..7017e37ce58
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_RebatchDataset.pbtxt
@@ -0,0 +1,23 @@
+op {
+  graph_op_name: "RebatchDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "input_dataset"
+    description: <<END
+A variant tensor representing the input dataset.
+END
+  }
+  in_arg {
+  name: "num_workers"
+  description: <<END
+A scalar representing the number of workers to distribute this batch across. As
+a result of this transformation the current batch size would end up being
+divided  by this parameter.
+END
+  }
+  summary: "Creates a dataset that changes the batch size."
+  description: <<END
+Creates a dataset that changes the batch size of the dataset to current batch
+size // num_workers.
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ScanDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_ScanDataset.pbtxt
new file mode 100644
index 00000000000..f0dc1a3e0d0
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ScanDataset.pbtxt
@@ -0,0 +1,5 @@
+op {
+  graph_op_name: "ScanDataset"
+  visibility: HIDDEN
+  summary: "Creates a dataset successively reduces `f` over the elements of `input_dataset`."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_SetStatsAggregatorDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_SetStatsAggregatorDataset.pbtxt
new file mode 100644
index 00000000000..3a8c1036ca3
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_SetStatsAggregatorDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "SetStatsAggregatorDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_SleepDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_SleepDataset.pbtxt
new file mode 100644
index 00000000000..60b54ab4983
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_SleepDataset.pbtxt
@@ -0,0 +1,4 @@
+op {
+  graph_op_name: "SleepDataset"
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_SlidingWindowDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_SlidingWindowDataset.pbtxt
new file mode 100644
index 00000000000..e8ae10cef21
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_SlidingWindowDataset.pbtxt
@@ -0,0 +1,26 @@
+op {
+  graph_op_name: "SlidingWindowDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "window_size"
+    description: <<END
+A scalar representing the number of elements in the
+sliding window.
+END
+  }
+  in_arg {
+    name: "window_shift"
+    description: <<END
+A scalar representing the steps moving the sliding window
+forward in one iteration. It must be positive.
+END
+  }
+  in_arg {
+    name: "window_stride"
+    description: <<END
+A scalar representing the stride of the input elements of the sliding window.
+It must be positive.
+END
+  }
+  summary: "Creates a dataset that passes a sliding window over `input_dataset`."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_SqlDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_SqlDataset.pbtxt
new file mode 100644
index 00000000000..e8c1b73720c
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_SqlDataset.pbtxt
@@ -0,0 +1,23 @@
+op {
+  graph_op_name: "SqlDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "driver_name"
+    description: <<END
+The database type. Currently, the only supported type is 'sqlite'.
+END
+  }
+  in_arg {
+    name: "data_source_name"
+    description: <<END
+A connection string to connect to the database.
+END
+  }
+  in_arg {
+    name: "query"
+    description: <<END
+A SQL query to execute.
+END
+  }
+  summary: "Creates a dataset that executes a SQL query and emits rows of the result set."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_StatsAggregatorHandle.pbtxt b/tensorflow/core/api_def/base_api/api_def_StatsAggregatorHandle.pbtxt
new file mode 100644
index 00000000000..f6c39fb4c62
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_StatsAggregatorHandle.pbtxt
@@ -0,0 +1,5 @@
+op {
+  graph_op_name: "StatsAggregatorHandle"
+  visibility: HIDDEN
+  summary: "Creates a statistics manager resource."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_StatsAggregatorSummary.pbtxt b/tensorflow/core/api_def/base_api/api_def_StatsAggregatorSummary.pbtxt
new file mode 100644
index 00000000000..2cce591a52d
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_StatsAggregatorSummary.pbtxt
@@ -0,0 +1,5 @@
+op {
+  graph_op_name: "StatsAggregatorSummary"
+  visibility: HIDDEN
+  summary: "Produces a summary of any statistics recorded by the given statistics manager."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_TakeWhileDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_TakeWhileDataset.pbtxt
new file mode 100644
index 00000000000..c8201c1a3fb
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_TakeWhileDataset.pbtxt
@@ -0,0 +1,25 @@
+op {
+  graph_op_name: "TakeWhileDataset"
+  visibility: HIDDEN
+  in_arg {
+    name: "other_arguments"
+    description: <<END
+A list of tensors, typically values that were captured when
+building a closure for `predicate`.
+END
+  }
+  attr {
+    name: "predicate"
+    description: <<END
+A function returning a scalar boolean.
+END
+  }
+  summary: "Creates a dataset that stops iteration when predicate` is false."
+  description: <<END
+The `predicate` function must return a scalar boolean and accept the
+following arguments:
+
+* One tensor for each component of an element of `input_dataset`.
+* One tensor for each value in `other_arguments`.
+END
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ThreadPoolDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_ThreadPoolDataset.pbtxt
new file mode 100644
index 00000000000..bd4f7d0586d
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ThreadPoolDataset.pbtxt
@@ -0,0 +1,13 @@
+op {
+  graph_op_name: "ThreadPoolDataset"
+  in_arg {
+    name: "thread_pool"
+    description: <<END
+A resource produced by the ThreadPoolHandle op.
+END
+  }
+  summary: <<END
+Creates a dataset that uses a custom thread pool to compute `input_dataset`.
+END
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_ThreadPoolHandle.pbtxt b/tensorflow/core/api_def/base_api/api_def_ThreadPoolHandle.pbtxt
new file mode 100644
index 00000000000..0bc34ecb077
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_ThreadPoolHandle.pbtxt
@@ -0,0 +1,35 @@
+op {
+  graph_op_name: "ThreadPoolHandle"
+  out_arg {
+    name: "handle"
+    description: <<END
+A resource that can be consumed by one or more ExperimentalThreadPoolDataset
+ops.
+END
+  }
+  attr {
+    name: "num_threads"
+    description: <<END
+The number of threads in the thread pool.
+END
+  }
+  attr {
+    name: "max_intra_op_parallelism"
+    description: <<END
+The maximum degree of parallelism to use within operations that execute on this
+threadpool.
+END
+  }
+  attr {
+    name: "display_name"
+    description: <<END
+A human-readable name for the threads that may be visible in some
+visualizations.
+threadpool.
+END
+  }
+  summary: <<END
+Creates a dataset that uses a custom thread pool to compute `input_dataset`.
+END
+  visibility: HIDDEN
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_UnbatchDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_UnbatchDataset.pbtxt
new file mode 100644
index 00000000000..eaa617c30f0
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_UnbatchDataset.pbtxt
@@ -0,0 +1,5 @@
+op {
+  graph_op_name: "UnbatchDataset"
+  visibility: HIDDEN
+  summary: "A dataset that splits the elements of its input into multiple elements."
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_UniqueDataset.pbtxt b/tensorflow/core/api_def/base_api/api_def_UniqueDataset.pbtxt
new file mode 100644
index 00000000000..7de4f777f87
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_UniqueDataset.pbtxt
@@ -0,0 +1,8 @@
+op {
+  graph_op_name: "UniqueDataset"
+  summary: <<END
+Creates a dataset that contains the unique elements of `input_dataset`.
+END
+  visibility: HIDDEN
+}
+
diff --git a/tensorflow/core/api_def/java_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt b/tensorflow/core/api_def/java_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt
deleted file mode 100644
index c49c6de2177..00000000000
--- a/tensorflow/core/api_def/java_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt
+++ /dev/null
@@ -1,6 +0,0 @@
-op {
-  graph_op_name: "ExperimentalIdentityIndexedDataset"
-  endpoint {
-    name: "data.ExperimentalIdentityIndexedDataset"
-  }
-}
diff --git a/tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetGet.pbtxt b/tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetGet.pbtxt
deleted file mode 100644
index 96a3befe8bb..00000000000
--- a/tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetGet.pbtxt
+++ /dev/null
@@ -1,6 +0,0 @@
-op {
-  graph_op_name: "ExperimentalIndexedDatasetGet"
-  endpoint {
-    name: "data.ExperimentalIndexedDatasetGet"
-  }
-}
diff --git a/tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt b/tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt
deleted file mode 100644
index 731309d3291..00000000000
--- a/tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt
+++ /dev/null
@@ -1,6 +0,0 @@
-op {
-  graph_op_name: "ExperimentalIndexedDatasetMaterialize"
-  endpoint {
-    name: "data.ExperimentalIndexedDatasetMaterialize"
-  }
-}
diff --git a/tensorflow/core/api_def/java_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt b/tensorflow/core/api_def/java_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt
deleted file mode 100644
index 06632e9041d..00000000000
--- a/tensorflow/core/api_def/java_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt
+++ /dev/null
@@ -1,6 +0,0 @@
-op {
-  graph_op_name: "ExperimentalMaterializedIndexDatasetHandle"
-  endpoint {
-    name: "data.ExperimentalMaterializedIndexDatasetHandle"
-  }
-}
diff --git a/tensorflow/core/api_def/java_api/api_def_ExperimentalNumaMapAndBatchDataset.pbtxt b/tensorflow/core/api_def/java_api/api_def_ExperimentalNumaMapAndBatchDataset.pbtxt
deleted file mode 100644
index a2c0d92f896..00000000000
--- a/tensorflow/core/api_def/java_api/api_def_ExperimentalNumaMapAndBatchDataset.pbtxt
+++ /dev/null
@@ -1,6 +0,0 @@
-op {
-  graph_op_name: "ExperimentalNumaMapAndBatchDataset"
-  endpoint {
-    name: "data.ExperimentalNumaMapAndBatchDataset"
-  }
-}
diff --git a/tensorflow/core/kernels/data/dataset_ops.cc b/tensorflow/core/kernels/data/dataset_ops.cc
index d75634a6cb4..6de11f4cbcc 100644
--- a/tensorflow/core/kernels/data/dataset_ops.cc
+++ b/tensorflow/core/kernels/data/dataset_ops.cc
@@ -56,6 +56,8 @@ class DatasetCardinalityOp : public OpKernel {
 REGISTER_KERNEL_BUILDER(Name("DatasetToGraph").Device(DEVICE_CPU),
                         DatasetToGraphOp);
 
+REGISTER_KERNEL_BUILDER(Name("DatasetCardinality").Device(DEVICE_CPU),
+                        DatasetCardinalityOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalDatasetCardinality").Device(DEVICE_CPU),
     DatasetCardinalityOp);
diff --git a/tensorflow/core/kernels/data/experimental/assert_next_dataset_op.cc b/tensorflow/core/kernels/data/experimental/assert_next_dataset_op.cc
index cda0885e7f0..b84d813c023 100644
--- a/tensorflow/core/kernels/data/experimental/assert_next_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/assert_next_dataset_op.cc
@@ -155,6 +155,8 @@ class AssertNextDatasetOp : public UnaryDatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("AssertNextDataset").Device(DEVICE_CPU),
+                        AssertNextDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalAssertNextDataset").Device(DEVICE_CPU),
     AssertNextDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/auto_shard_dataset_op.cc b/tensorflow/core/kernels/data/experimental/auto_shard_dataset_op.cc
index 7531225b817..23797606d29 100644
--- a/tensorflow/core/kernels/data/experimental/auto_shard_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/auto_shard_dataset_op.cc
@@ -76,6 +76,8 @@ class AutoShardDatasetOp : public UnaryDatasetOpKernel {
   }
 };
 
+REGISTER_KERNEL_BUILDER(Name("AutoShardDataset").Device(DEVICE_CPU),
+                        AutoShardDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalAutoShardDataset").Device(DEVICE_CPU),
                         AutoShardDatasetOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/choose_fastest_dataset_op.cc b/tensorflow/core/kernels/data/experimental/choose_fastest_dataset_op.cc
index 1ae86c1dbfa..2c934eb65df 100644
--- a/tensorflow/core/kernels/data/experimental/choose_fastest_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/choose_fastest_dataset_op.cc
@@ -357,7 +357,8 @@ class ChooseFastestDatasetOp : public DatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };  // class ChooseFastestDatasetOp
 
-// Register the kernel implementation for ChooseFastestDataset.
+REGISTER_KERNEL_BUILDER(Name("ChooseFastestDataset").Device(DEVICE_CPU),
+                        ChooseFastestDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalChooseFastestDataset").Device(DEVICE_CPU),
     ChooseFastestDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/csv_dataset_op.cc b/tensorflow/core/kernels/data/experimental/csv_dataset_op.cc
index fecafaacf2d..d721e69b7ad 100644
--- a/tensorflow/core/kernels/data/experimental/csv_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/csv_dataset_op.cc
@@ -854,7 +854,7 @@ class CSVDatasetOp : public DatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };  // class CSVDatasetOp
 
-// Register the kernel implementation for CSVDataset.
+REGISTER_KERNEL_BUILDER(Name("CSVDataset").Device(DEVICE_CPU), CSVDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalCSVDataset").Device(DEVICE_CPU),
                         CSVDatasetOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/dense_to_sparse_batch_dataset_op.cc b/tensorflow/core/kernels/data/experimental/dense_to_sparse_batch_dataset_op.cc
index 31f081a7277..b3003aae455 100644
--- a/tensorflow/core/kernels/data/experimental/dense_to_sparse_batch_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/dense_to_sparse_batch_dataset_op.cc
@@ -312,6 +312,8 @@ class DenseToSparseBatchDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("DenseToSparseBatchDataset").Device(DEVICE_CPU),
+                        DenseToSparseBatchDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalDenseToSparseBatchDataset").Device(DEVICE_CPU),
     DenseToSparseBatchDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/directed_interleave_dataset_op.cc b/tensorflow/core/kernels/data/experimental/directed_interleave_dataset_op.cc
index f55718a0064..5d94ec0721d 100644
--- a/tensorflow/core/kernels/data/experimental/directed_interleave_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/directed_interleave_dataset_op.cc
@@ -277,6 +277,8 @@ class DirectedInterleaveDatasetOp : public DatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("DirectedInterleaveDataset").Device(DEVICE_CPU),
+                        DirectedInterleaveDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalDirectedInterleaveDataset").Device(DEVICE_CPU),
     DirectedInterleaveDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/group_by_reducer_dataset_op.cc b/tensorflow/core/kernels/data/experimental/group_by_reducer_dataset_op.cc
index b94ae5f9b97..6aa2ae77d4c 100644
--- a/tensorflow/core/kernels/data/experimental/group_by_reducer_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/group_by_reducer_dataset_op.cc
@@ -412,9 +412,13 @@ class GroupByReducerDatasetOp : public UnaryDatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("GroupByReducerDataset").Device(DEVICE_CPU),
+                        GroupByReducerDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalGroupByReducerDataset").Device(DEVICE_CPU),
     GroupByReducerDatasetOp);
+
+REGISTER_INPUT_COLOCATION_EXEMPTION("GroupByReducerDataset");
 REGISTER_INPUT_COLOCATION_EXEMPTION("ExperimentalGroupByReducerDataset");
 
 }  // namespace
diff --git a/tensorflow/core/kernels/data/experimental/group_by_window_dataset_op.cc b/tensorflow/core/kernels/data/experimental/group_by_window_dataset_op.cc
index ba1dd88a231..38a520126f9 100644
--- a/tensorflow/core/kernels/data/experimental/group_by_window_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/group_by_window_dataset_op.cc
@@ -507,9 +507,13 @@ class GroupByWindowDatasetOp : public UnaryDatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("GroupByWindowDataset").Device(DEVICE_CPU),
+                        GroupByWindowDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalGroupByWindowDataset").Device(DEVICE_CPU),
     GroupByWindowDatasetOp);
+
+REGISTER_INPUT_COLOCATION_EXEMPTION("GroupByWindowDataset");
 REGISTER_INPUT_COLOCATION_EXEMPTION("ExperimentalGroupByWindowDataset");
 
 }  // namespace
diff --git a/tensorflow/core/kernels/data/experimental/ignore_errors_dataset_op.cc b/tensorflow/core/kernels/data/experimental/ignore_errors_dataset_op.cc
index 5e07bdb32eb..410861de78a 100644
--- a/tensorflow/core/kernels/data/experimental/ignore_errors_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/ignore_errors_dataset_op.cc
@@ -140,6 +140,8 @@ class IgnoreErrorsDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("IgnoreErrorsDataset").Device(DEVICE_CPU),
+                        IgnoreErrorsDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalIgnoreErrorsDataset").Device(DEVICE_CPU),
     IgnoreErrorsDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/lmdb_dataset_op.cc b/tensorflow/core/kernels/data/experimental/lmdb_dataset_op.cc
index cf900f13361..0c75995d5de 100644
--- a/tensorflow/core/kernels/data/experimental/lmdb_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/lmdb_dataset_op.cc
@@ -216,6 +216,7 @@ class LMDBDatasetOp : public DatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("LMDBDataset").Device(DEVICE_CPU), LMDBDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalLMDBDataset").Device(DEVICE_CPU),
                         LMDBDatasetOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/map_and_batch_dataset_op.cc b/tensorflow/core/kernels/data/experimental/map_and_batch_dataset_op.cc
index 30f41e46532..2eddf4a775a 100644
--- a/tensorflow/core/kernels/data/experimental/map_and_batch_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/map_and_batch_dataset_op.cc
@@ -764,9 +764,13 @@ class MapAndBatchDatasetOp : public UnaryDatasetOpKernel {
   bool preserve_cardinality_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("MapAndBatchDataset").Device(DEVICE_CPU),
+                        MapAndBatchDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalMapAndBatchDataset").Device(DEVICE_CPU),
     MapAndBatchDatasetOp);
+
+REGISTER_INPUT_COLOCATION_EXEMPTION("MapAndBatchDataset");
 REGISTER_INPUT_COLOCATION_EXEMPTION("ExperimentalMapAndBatchDataset");
 
 }  // namespace
diff --git a/tensorflow/core/kernels/data/experimental/matching_files_dataset_op.cc b/tensorflow/core/kernels/data/experimental/matching_files_dataset_op.cc
index 6a8c9939a33..0c3d06a4ace 100644
--- a/tensorflow/core/kernels/data/experimental/matching_files_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/matching_files_dataset_op.cc
@@ -366,6 +366,8 @@ class MatchingFilesDatasetOp : public DatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("MatchingFilesDataset").Device(DEVICE_CPU),
+                        MatchingFilesDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalMatchingFilesDataset").Device(DEVICE_CPU),
     MatchingFilesDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/non_serializable_dataset_op.cc b/tensorflow/core/kernels/data/experimental/non_serializable_dataset_op.cc
index 9ca8e33b946..9086e13eae4 100644
--- a/tensorflow/core/kernels/data/experimental/non_serializable_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/non_serializable_dataset_op.cc
@@ -123,6 +123,8 @@ class NonSerializableDatasetOp : public UnaryDatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("NonSerializableDataset").Device(DEVICE_CPU),
+                        NonSerializableDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalNonSerializableDataset").Device(DEVICE_CPU),
     NonSerializableDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/parallel_interleave_dataset_op.cc b/tensorflow/core/kernels/data/experimental/parallel_interleave_dataset_op.cc
index af4c8dd0025..2ce26f6b01b 100644
--- a/tensorflow/core/kernels/data/experimental/parallel_interleave_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/parallel_interleave_dataset_op.cc
@@ -1069,9 +1069,13 @@ class ParallelInterleaveDatasetOp : public UnaryDatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("ParallelInterleaveDataset").Device(DEVICE_CPU),
+                        ParallelInterleaveDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalParallelInterleaveDataset").Device(DEVICE_CPU),
     ParallelInterleaveDatasetOp);
+
+REGISTER_INPUT_COLOCATION_EXEMPTION("ParallelInterleaveDataset");
 REGISTER_INPUT_COLOCATION_EXEMPTION("ExperimentalParallelInterleaveDataset");
 
 }  // namespace
diff --git a/tensorflow/core/kernels/data/experimental/parse_example_dataset_op.cc b/tensorflow/core/kernels/data/experimental/parse_example_dataset_op.cc
index 1d7ca30c8ec..97b91d80b10 100644
--- a/tensorflow/core/kernels/data/experimental/parse_example_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/parse_example_dataset_op.cc
@@ -397,6 +397,8 @@ class ParseExampleDatasetOp : public UnaryDatasetOpKernel {
   std::vector<std::size_t> elements_per_stride_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("ParseExampleDataset").Device(DEVICE_CPU),
+                        ParseExampleDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalParseExampleDataset").Device(DEVICE_CPU),
     ParseExampleDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/prefetching_kernels.cc b/tensorflow/core/kernels/data/experimental/prefetching_kernels.cc
index af024520982..0a640c5f877 100644
--- a/tensorflow/core/kernels/data/experimental/prefetching_kernels.cc
+++ b/tensorflow/core/kernels/data/experimental/prefetching_kernels.cc
@@ -45,6 +45,8 @@ class IteratorGetDeviceOp : public OpKernel {
   }
 };
 
+REGISTER_KERNEL_BUILDER(Name("IteratorGetDevice").Device(DEVICE_CPU),
+                        IteratorGetDeviceOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalIteratorGetDevice").Device(DEVICE_CPU),
     IteratorGetDeviceOp);
diff --git a/tensorflow/core/kernels/data/experimental/random_dataset_op.cc b/tensorflow/core/kernels/data/experimental/random_dataset_op.cc
index 114bb6a856c..80a37764edd 100644
--- a/tensorflow/core/kernels/data/experimental/random_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/random_dataset_op.cc
@@ -154,6 +154,8 @@ class RandomDatasetOp : public DatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("RandomDataset").Device(DEVICE_CPU),
+                        RandomDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalRandomDataset").Device(DEVICE_CPU),
                         RandomDatasetOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/rebatch_dataset_op.cc b/tensorflow/core/kernels/data/experimental/rebatch_dataset_op.cc
index 3078005a00d..cedac95a749 100644
--- a/tensorflow/core/kernels/data/experimental/rebatch_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/rebatch_dataset_op.cc
@@ -64,6 +64,8 @@ class RebatchDatasetOp : public UnaryDatasetOpKernel {
   }
 };
 
+REGISTER_KERNEL_BUILDER(Name("RebatchDataset").Device(DEVICE_CPU),
+                        RebatchDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalRebatchDataset").Device(DEVICE_CPU),
                         RebatchDatasetOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/scan_dataset_op.cc b/tensorflow/core/kernels/data/experimental/scan_dataset_op.cc
index 5dd36abf92e..31ec0868048 100644
--- a/tensorflow/core/kernels/data/experimental/scan_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/scan_dataset_op.cc
@@ -290,9 +290,11 @@ class ScanDatasetOp : public UnaryDatasetOpKernel {
   bool preserve_cardinality_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("ScanDataset").Device(DEVICE_CPU), ScanDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalScanDataset").Device(DEVICE_CPU),
                         ScanDatasetOp);
 
+REGISTER_INPUT_COLOCATION_EXEMPTION("ScanDataset");
 REGISTER_INPUT_COLOCATION_EXEMPTION("ExperimentalScanDataset");
 
 }  // namespace
diff --git a/tensorflow/core/kernels/data/experimental/set_stats_aggregator_dataset_op.cc b/tensorflow/core/kernels/data/experimental/set_stats_aggregator_dataset_op.cc
index 3129edf77cd..64390e72fd2 100644
--- a/tensorflow/core/kernels/data/experimental/set_stats_aggregator_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/set_stats_aggregator_dataset_op.cc
@@ -211,9 +211,12 @@ class SetStatsAggregatorDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("SetStatsAggregatorDataset").Device(DEVICE_CPU),
+                        SetStatsAggregatorDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalSetStatsAggregatorDataset").Device(DEVICE_CPU),
     SetStatsAggregatorDatasetOp);
+
 }  // namespace
 }  // namespace data
 }  // namespace tensorflow
diff --git a/tensorflow/core/kernels/data/experimental/sleep_dataset_op.cc b/tensorflow/core/kernels/data/experimental/sleep_dataset_op.cc
index a3bccedd014..afe44dc9ecc 100644
--- a/tensorflow/core/kernels/data/experimental/sleep_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/sleep_dataset_op.cc
@@ -133,8 +133,17 @@ class SleepDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("SleepDataset").Device(DEVICE_CPU),
+                        SleepDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalSleepDataset").Device(DEVICE_CPU),
                         SleepDatasetOp);
+
+REGISTER_KERNEL_BUILDER(Name("SleepDataset")
+                            .Device(DEVICE_GPU)
+                            .HostMemory("sleep_microseconds")
+                            .HostMemory("input_dataset")
+                            .HostMemory("handle"),
+                        SleepDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalSleepDataset")
                             .Device(DEVICE_GPU)
                             .HostMemory("sleep_microseconds")
diff --git a/tensorflow/core/kernels/data/experimental/sliding_window_dataset_op.cc b/tensorflow/core/kernels/data/experimental/sliding_window_dataset_op.cc
index dec136dd35e..154ce7dfd48 100644
--- a/tensorflow/core/kernels/data/experimental/sliding_window_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/sliding_window_dataset_op.cc
@@ -302,6 +302,8 @@ class SlidingWindowDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("SlidingWindowDataset").Device(DEVICE_CPU),
+                        SlidingWindowDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalSlidingWindowDataset").Device(DEVICE_CPU),
     SlidingWindowDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/sql_dataset_op.cc b/tensorflow/core/kernels/data/experimental/sql_dataset_op.cc
index bd941550488..8a095d9c445 100644
--- a/tensorflow/core/kernels/data/experimental/sql_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/sql_dataset_op.cc
@@ -214,6 +214,7 @@ class SqlDatasetOp : public DatasetOpKernel {
   std::vector<PartialTensorShape> output_shapes_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("SqlDataset").Device(DEVICE_CPU), SqlDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalSqlDataset").Device(DEVICE_CPU),
                         SqlDatasetOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/stats_aggregator_ops.cc b/tensorflow/core/kernels/data/experimental/stats_aggregator_ops.cc
index 8145f7d45b3..9b5a4832d85 100644
--- a/tensorflow/core/kernels/data/experimental/stats_aggregator_ops.cc
+++ b/tensorflow/core/kernels/data/experimental/stats_aggregator_ops.cc
@@ -296,14 +296,21 @@ class StatsAggregatorSetSummaryWriterOp : public OpKernel {
   }
 };
 
+REGISTER_KERNEL_BUILDER(Name("StatsAggregatorHandle").Device(DEVICE_CPU),
+                        StatsAggregatorHandleOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalStatsAggregatorHandle").Device(DEVICE_CPU),
     StatsAggregatorHandleOp);
+
 REGISTER_KERNEL_BUILDER(Name("StatsAggregatorHandleV2").Device(DEVICE_CPU),
                         StatsAggregatorHandleOpV2);
+
+REGISTER_KERNEL_BUILDER(Name("StatsAggregatorSummary").Device(DEVICE_CPU),
+                        StatsAggregatorSummaryOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalStatsAggregatorSummary").Device(DEVICE_CPU),
     StatsAggregatorSummaryOp);
+
 REGISTER_KERNEL_BUILDER(
     Name("StatsAggregatorSetSummaryWriter").Device(DEVICE_CPU),
     StatsAggregatorSetSummaryWriterOp);
diff --git a/tensorflow/core/kernels/data/experimental/stats_dataset_ops.cc b/tensorflow/core/kernels/data/experimental/stats_dataset_ops.cc
index 08a144049db..70a95faf707 100644
--- a/tensorflow/core/kernels/data/experimental/stats_dataset_ops.cc
+++ b/tensorflow/core/kernels/data/experimental/stats_dataset_ops.cc
@@ -258,13 +258,18 @@ class BytesProducedStatsDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
-REGISTER_KERNEL_BUILDER(
-    Name("ExperimentalLatencyStatsDataset").Device(DEVICE_CPU),
-    LatencyStatsDatasetOp);
+REGISTER_KERNEL_BUILDER(Name("BytesProducedStatsDataset").Device(DEVICE_CPU),
+                        BytesProducedStatsDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalBytesProducedStatsDataset").Device(DEVICE_CPU),
     BytesProducedStatsDatasetOp);
 
+REGISTER_KERNEL_BUILDER(Name("LatencyStatsDataset").Device(DEVICE_CPU),
+                        LatencyStatsDatasetOp);
+REGISTER_KERNEL_BUILDER(
+    Name("ExperimentalLatencyStatsDataset").Device(DEVICE_CPU),
+    LatencyStatsDatasetOp);
+
 }  // namespace
 }  // namespace data
 }  // namespace tensorflow
diff --git a/tensorflow/core/kernels/data/experimental/take_while_dataset_op.cc b/tensorflow/core/kernels/data/experimental/take_while_dataset_op.cc
index ae4fa73482f..af7f778fa74 100644
--- a/tensorflow/core/kernels/data/experimental/take_while_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/take_while_dataset_op.cc
@@ -198,8 +198,12 @@ class TakeWhileDatasetOp : public UnaryDatasetOpKernel {
   std::shared_ptr<FunctionMetadata> func_metadata_ = nullptr;
 };
 
+REGISTER_KERNEL_BUILDER(Name("TakeWhileDataset").Device(DEVICE_CPU),
+                        TakeWhileDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalTakeWhileDataset").Device(DEVICE_CPU),
                         TakeWhileDatasetOp);
+
+REGISTER_INPUT_COLOCATION_EXEMPTION("TakeWhileDataset");
 REGISTER_INPUT_COLOCATION_EXEMPTION("ExperimentalTakeWhileDataset");
 
 }  // namespace
diff --git a/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc b/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc
index 5c6af068ef7..8aa26ea4bec 100644
--- a/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc
@@ -431,14 +431,25 @@ class PrivateThreadPoolDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("MaxIntraOpParallelismDataset").Device(DEVICE_CPU),
+                        MaxIntraOpParallelismDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalMaxIntraOpParallelismDataset").Device(DEVICE_CPU),
     MaxIntraOpParallelismDatasetOp);
+
+REGISTER_KERNEL_BUILDER(Name("PrivateThreadPoolDataset").Device(DEVICE_CPU),
+                        PrivateThreadPoolDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalPrivateThreadPoolDataset").Device(DEVICE_CPU),
     PrivateThreadPoolDatasetOp);
+
+REGISTER_KERNEL_BUILDER(Name("ThreadPoolHandle").Device(DEVICE_CPU),
+                        ThreadPoolHandleOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalThreadPoolHandle").Device(DEVICE_CPU),
                         ThreadPoolHandleOp);
+
+REGISTER_KERNEL_BUILDER(Name("ThreadPoolDataset").Device(DEVICE_CPU),
+                        ThreadPoolDatasetOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalThreadPoolDataset").Device(DEVICE_CPU),
     ThreadPoolDatasetOp);
diff --git a/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc b/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc
index b450970a717..24262a50f11 100644
--- a/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc
+++ b/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc
@@ -100,6 +100,8 @@ class ToTFRecordOp : public AsyncOpKernel {
   BackgroundWorker background_worker_;
 };
 
+REGISTER_KERNEL_BUILDER(Name("DatasetToTFRecord").Device(DEVICE_CPU),
+                        ToTFRecordOp);
 REGISTER_KERNEL_BUILDER(
     Name("ExperimentalDatasetToTFRecord").Device(DEVICE_CPU), ToTFRecordOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/unbatch_dataset_op.cc b/tensorflow/core/kernels/data/experimental/unbatch_dataset_op.cc
index cb26fd3e43d..3252196acfe 100644
--- a/tensorflow/core/kernels/data/experimental/unbatch_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/unbatch_dataset_op.cc
@@ -221,6 +221,8 @@ class UnbatchDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("UnbatchDataset").Device(DEVICE_CPU),
+                        UnbatchDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalUnbatchDataset").Device(DEVICE_CPU),
                         UnbatchDatasetOp);
 
diff --git a/tensorflow/core/kernels/data/experimental/unique_dataset_op.cc b/tensorflow/core/kernels/data/experimental/unique_dataset_op.cc
index 57865c45fc0..613b2fd641b 100644
--- a/tensorflow/core/kernels/data/experimental/unique_dataset_op.cc
+++ b/tensorflow/core/kernels/data/experimental/unique_dataset_op.cc
@@ -221,6 +221,8 @@ class UniqueDatasetOp : public UnaryDatasetOpKernel {
   };
 };
 
+REGISTER_KERNEL_BUILDER(Name("UniqueDataset").Device(DEVICE_CPU),
+                        UniqueDatasetOp);
 REGISTER_KERNEL_BUILDER(Name("ExperimentalUniqueDataset").Device(DEVICE_CPU),
                         UniqueDatasetOp);
 
diff --git a/tensorflow/core/ops/compat/ops_history.v1.pbtxt b/tensorflow/core/ops/compat/ops_history.v1.pbtxt
index b699fb646d6..d24d8f28d66 100644
--- a/tensorflow/core/ops/compat/ops_history.v1.pbtxt
+++ b/tensorflow/core/ops/compat/ops_history.v1.pbtxt
@@ -25428,18 +25428,6 @@ op {
     minimum: 1
   }
 }
-op {
-  name: "ExperimentalIdentityIndexedDataset"
-  input_arg {
-    name: "size"
-    type: DT_UINT64
-  }
-  output_arg {
-    name: "handle"
-    type: DT_VARIANT
-  }
-  is_stateful: true
-}
 op {
   name: "ExperimentalIgnoreErrorsDataset"
   input_arg {
@@ -25463,46 +25451,6 @@ op {
     minimum: 1
   }
 }
-op {
-  name: "ExperimentalIndexedDatasetGet"
-  input_arg {
-    name: "materialized"
-    type: DT_RESOURCE
-  }
-  input_arg {
-    name: "index"
-    type: DT_UINT64
-  }
-  output_arg {
-    name: "components"
-    type_list_attr: "output_types"
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-  is_stateful: true
-}
-op {
-  name: "ExperimentalIndexedDatasetMaterialize"
-  input_arg {
-    name: "dataset"
-    type: DT_VARIANT
-  }
-  input_arg {
-    name: "materialized"
-    type: DT_RESOURCE
-  }
-  is_stateful: true
-}
 op {
   name: "ExperimentalIteratorGetDevice"
   input_arg {
@@ -25774,34 +25722,6 @@ op {
   }
   is_stateful: true
 }
-op {
-  name: "ExperimentalMaterializedIndexDatasetHandle"
-  output_arg {
-    name: "handle"
-    type: DT_RESOURCE
-  }
-  attr {
-    name: "container"
-    type: "string"
-  }
-  attr {
-    name: "shared_name"
-    type: "string"
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-  is_stateful: true
-}
 op {
   name: "ExperimentalMaxIntraOpParallelismDataset"
   input_arg {
@@ -25852,109 +25772,6 @@ op {
     minimum: 1
   }
 }
-op {
-  name: "ExperimentalNumaMapAndBatchDataset"
-  input_arg {
-    name: "input_dataset"
-    type: DT_VARIANT
-  }
-  input_arg {
-    name: "other_arguments"
-    type_list_attr: "Targuments"
-  }
-  input_arg {
-    name: "batch_size"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "num_parallel_calls"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "drop_remainder"
-    type: DT_BOOL
-  }
-  output_arg {
-    name: "handle"
-    type: DT_VARIANT
-  }
-  attr {
-    name: "f"
-    type: "func"
-  }
-  attr {
-    name: "Targuments"
-    type: "list(type)"
-    has_minimum: true
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-}
-op {
-  name: "ExperimentalNumaMapAndBatchDataset"
-  input_arg {
-    name: "input_dataset"
-    type: DT_VARIANT
-  }
-  input_arg {
-    name: "other_arguments"
-    type_list_attr: "Targuments"
-  }
-  input_arg {
-    name: "batch_size"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "num_parallel_calls"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "drop_remainder"
-    type: DT_BOOL
-  }
-  output_arg {
-    name: "handle"
-    type: DT_VARIANT
-  }
-  attr {
-    name: "f"
-    type: "func"
-  }
-  attr {
-    name: "Targuments"
-    type: "list(type)"
-    has_minimum: true
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "preserve_cardinality"
-    type: "bool"
-    default_value {
-      b: false
-    }
-  }
-}
 op {
   name: "ExperimentalParallelInterleaveDataset"
   input_arg {
diff --git a/tensorflow/core/ops/compat/ops_history.v2.pbtxt b/tensorflow/core/ops/compat/ops_history.v2.pbtxt
index 2cf89d79979..8bfe6ad275f 100644
--- a/tensorflow/core/ops/compat/ops_history.v2.pbtxt
+++ b/tensorflow/core/ops/compat/ops_history.v2.pbtxt
@@ -23524,18 +23524,6 @@ op {
     minimum: 1
   }
 }
-op {
-  name: "ExperimentalIdentityIndexedDataset"
-  input_arg {
-    name: "size"
-    type: DT_UINT64
-  }
-  output_arg {
-    name: "handle"
-    type: DT_VARIANT
-  }
-  is_stateful: true
-}
 op {
   name: "ExperimentalIgnoreErrorsDataset"
   input_arg {
@@ -23559,46 +23547,6 @@ op {
     minimum: 1
   }
 }
-op {
-  name: "ExperimentalIndexedDatasetGet"
-  input_arg {
-    name: "materialized"
-    type: DT_RESOURCE
-  }
-  input_arg {
-    name: "index"
-    type: DT_UINT64
-  }
-  output_arg {
-    name: "components"
-    type_list_attr: "output_types"
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-  is_stateful: true
-}
-op {
-  name: "ExperimentalIndexedDatasetMaterialize"
-  input_arg {
-    name: "dataset"
-    type: DT_VARIANT
-  }
-  input_arg {
-    name: "materialized"
-    type: DT_RESOURCE
-  }
-  is_stateful: true
-}
 op {
   name: "ExperimentalIteratorGetDevice"
   input_arg {
@@ -23870,34 +23818,6 @@ op {
   }
   is_stateful: true
 }
-op {
-  name: "ExperimentalMaterializedIndexDatasetHandle"
-  output_arg {
-    name: "handle"
-    type: DT_RESOURCE
-  }
-  attr {
-    name: "container"
-    type: "string"
-  }
-  attr {
-    name: "shared_name"
-    type: "string"
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-  is_stateful: true
-}
 op {
   name: "ExperimentalMaxIntraOpParallelismDataset"
   input_arg {
@@ -23948,109 +23868,6 @@ op {
     minimum: 1
   }
 }
-op {
-  name: "ExperimentalNumaMapAndBatchDataset"
-  input_arg {
-    name: "input_dataset"
-    type: DT_VARIANT
-  }
-  input_arg {
-    name: "other_arguments"
-    type_list_attr: "Targuments"
-  }
-  input_arg {
-    name: "batch_size"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "num_parallel_calls"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "drop_remainder"
-    type: DT_BOOL
-  }
-  output_arg {
-    name: "handle"
-    type: DT_VARIANT
-  }
-  attr {
-    name: "f"
-    type: "func"
-  }
-  attr {
-    name: "Targuments"
-    type: "list(type)"
-    has_minimum: true
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-}
-op {
-  name: "ExperimentalNumaMapAndBatchDataset"
-  input_arg {
-    name: "input_dataset"
-    type: DT_VARIANT
-  }
-  input_arg {
-    name: "other_arguments"
-    type_list_attr: "Targuments"
-  }
-  input_arg {
-    name: "batch_size"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "num_parallel_calls"
-    type: DT_INT64
-  }
-  input_arg {
-    name: "drop_remainder"
-    type: DT_BOOL
-  }
-  output_arg {
-    name: "handle"
-    type: DT_VARIANT
-  }
-  attr {
-    name: "f"
-    type: "func"
-  }
-  attr {
-    name: "Targuments"
-    type: "list(type)"
-    has_minimum: true
-  }
-  attr {
-    name: "output_types"
-    type: "list(type)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "output_shapes"
-    type: "list(shape)"
-    has_minimum: true
-    minimum: 1
-  }
-  attr {
-    name: "preserve_cardinality"
-    type: "bool"
-    default_value {
-      b: false
-    }
-  }
-}
 op {
   name: "ExperimentalParallelInterleaveDataset"
   input_arg {
diff --git a/tensorflow/core/ops/experimental_dataset_ops.cc b/tensorflow/core/ops/experimental_dataset_ops.cc
index 8d6fa2dd1d8..1e1525e10c7 100644
--- a/tensorflow/core/ops/experimental_dataset_ops.cc
+++ b/tensorflow/core/ops/experimental_dataset_ops.cc
@@ -17,10 +17,40 @@ limitations under the License.
 
 namespace tensorflow {
 
-REGISTER_OP("StatsAggregatorSetSummaryWriter")
-    .Input("stats_aggregator: resource")
-    .Input("summary: resource")
-    .SetShapeFn(shape_inference::NoOutputs);
+REGISTER_OP("AssertNextDataset")
+    .Input("input_dataset: variant")
+    .Input("transformations: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // transformations should be a vector.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 1, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
+REGISTER_OP("ExperimentalAssertNextDataset")
+    .Input("input_dataset: variant")
+    .Input("transformations: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // transformations should be a vector.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 1, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
+REGISTER_OP("AutoShardDataset")
+    .Input("input_dataset: variant")
+    .Input("num_workers: int64")
+    .Input("index: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
 
 REGISTER_OP("ExperimentalAutoShardDataset")
     .Input("input_dataset: variant")
@@ -31,6 +61,18 @@ REGISTER_OP("ExperimentalAutoShardDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("BytesProducedStatsDataset")
+    .Input("input_dataset: variant")
+    .Input("tag: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle tag_shape;
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &tag_shape));
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalBytesProducedStatsDataset")
     .Input("input_dataset: variant")
     .Input("tag: string")
@@ -57,6 +99,66 @@ REGISTER_OP("ChooseFastestBranchDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("ChooseFastestDataset")
+    .Input("input_datasets: N * variant")
+    .Output("handle: variant")
+    .Attr("N: int >= 2")
+    .Attr("num_experiments: int")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("ExperimentalChooseFastestDataset")
+    .Input("input_datasets: N * variant")
+    .Output("handle: variant")
+    .Attr("N: int >= 2")
+    .Attr("num_experiments: int")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("CSVDataset")
+    .Input("filenames: string")
+    .Input("compression_type: string")
+    .Input("buffer_size: int64")
+    .Input("header: bool")
+    .Input("field_delim: string")
+    .Input("use_quote_delim: bool")
+    .Input("na_value: string")
+    .Input("select_cols: int64")
+    .Input("record_defaults: output_types")
+    .Output("handle: variant")
+    .Attr("output_types: list({float,double,int32,int64,string}) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetIsStateful()  // TODO(b/123753214): Source dataset ops must be marked
+                      // stateful to inhibit constant folding.
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // `filenames` must be a scalar or a vector.
+      TF_RETURN_IF_ERROR(c->WithRankAtMost(c->input(0), 1, &unused));
+      // `compression_type`, `buffer_size`, `header`, `field_delim`,
+      // `use_quote_delim`, `na_value` must be scalars
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(2), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(3), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(4), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(5), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(6), 0, &unused));
+      // `select_cols` must be a vector
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(7), 1, &unused));
+      // `record_defaults` must be lists of scalars
+      for (size_t i = 8; i < c->num_inputs(); ++i) {
+        shape_inference::ShapeHandle v;
+        TF_RETURN_IF_ERROR(c->WithRankAtMost(c->input(i), 1, &v));
+        if (c->Rank(c->input(i)) == 1 && c->Value(c->Dim(v, 0)) > 1) {
+          return errors::InvalidArgument(
+              "Shape of a default must be a length-0 or length-1 vector, or a "
+              "scalar.");
+        }
+      }
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalCSVDataset")
     .Input("filenames: string")
     .Input("compression_type: string")
@@ -99,6 +201,11 @@ REGISTER_OP("ExperimentalCSVDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("DatasetCardinality")
+    .Input("input_dataset: variant")
+    .Output("cardinality: int64")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalDatasetCardinality")
     .Input("input_dataset: variant")
     .Output("cardinality: int64")
@@ -108,6 +215,13 @@ REGISTER_OP("ExperimentalDatasetCardinality")
 // implement a mechanism to determine whether `dataset` has a side-effect
 // and use it to decide whether to use a stateless or stateful version of this
 // op.
+REGISTER_OP("DatasetToTFRecord")
+    .Input("input_dataset: variant")
+    .Input("filename: string")
+    .Input("compression_type: string")
+    .SetIsStateful()
+    .SetShapeFn(shape_inference::NoOutputs);
+
 REGISTER_OP("ExperimentalDatasetToTFRecord")
     .Input("input_dataset: variant")
     .Input("filename: string")
@@ -115,6 +229,22 @@ REGISTER_OP("ExperimentalDatasetToTFRecord")
     .SetIsStateful()
     .SetShapeFn(shape_inference::NoOutputs);
 
+REGISTER_OP("DenseToSparseBatchDataset")
+    .Input("input_dataset: variant")
+    .Input("batch_size: int64")
+    .Input("row_shape: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // batch_size should be a scalar.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &unused));
+      // row_shape should be a 1-D vector.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(2), 1, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalDenseToSparseBatchDataset")
     .Input("input_dataset: variant")
     .Input("batch_size: int64")
@@ -131,6 +261,15 @@ REGISTER_OP("ExperimentalDenseToSparseBatchDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("DirectedInterleaveDataset")
+    .Input("selector_input_dataset: variant")
+    .Input("data_input_datasets: N * variant")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .Attr("N: int >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalDirectedInterleaveDataset")
     .Input("selector_input_dataset: variant")
     .Input("data_input_datasets: N * variant")
@@ -140,6 +279,26 @@ REGISTER_OP("ExperimentalDirectedInterleaveDataset")
     .Attr("N: int >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("GroupByReducerDataset")
+    .Input("input_dataset: variant")
+    .Input("key_func_other_arguments: Tkey_func_other_arguments")
+    .Input("init_func_other_arguments: Tinit_func_other_arguments")
+    .Input("reduce_func_other_arguments: Treduce_func_other_arguments")
+    .Input("finalize_func_other_arguments: Tfinalize_func_other_arguments")
+    .Output("handle: variant")
+    .Attr("key_func: func")
+    .Attr("init_func: func")
+    .Attr("reduce_func: func")
+    .Attr("finalize_func: func")
+    .Attr("Tkey_func_other_arguments: list(type) >= 0")
+    .Attr("Tinit_func_other_arguments: list(type) >= 0")
+    .Attr("Treduce_func_other_arguments: list(type) >= 0")
+    .Attr("Tfinalize_func_other_arguments: list(type) >= 0")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetIsStateful()
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalGroupByReducerDataset")
     .Input("input_dataset: variant")
     .Input("key_func_other_arguments: Tkey_func_other_arguments")
@@ -160,6 +319,23 @@ REGISTER_OP("ExperimentalGroupByReducerDataset")
     .SetIsStateful()
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("GroupByWindowDataset")
+    .Input("input_dataset: variant")
+    .Input("key_func_other_arguments: Tkey_func_other_arguments")
+    .Input("reduce_func_other_arguments: Treduce_func_other_arguments")
+    .Input(
+        "window_size_func_other_arguments: Twindow_size_func_other_arguments")
+    .Output("handle: variant")
+    .Attr("key_func: func")
+    .Attr("reduce_func: func")
+    .Attr("window_size_func: func")
+    .Attr("Tkey_func_other_arguments: list(type) >= 0")
+    .Attr("Treduce_func_other_arguments: list(type) >= 0")
+    .Attr("Twindow_size_func_other_arguments: list(type) >= 0")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalGroupByWindowDataset")
     .Input("input_dataset: variant")
     .Input("key_func_other_arguments: Tkey_func_other_arguments")
@@ -177,6 +353,13 @@ REGISTER_OP("ExperimentalGroupByWindowDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("IgnoreErrorsDataset")
+    .Input("input_dataset: variant")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalIgnoreErrorsDataset")
     .Input("input_dataset: variant")
     .Output("handle: variant")
@@ -184,6 +367,28 @@ REGISTER_OP("ExperimentalIgnoreErrorsDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("IteratorGetDevice")
+    .Input("resource: resource")
+    .Output("device: string")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("ExperimentalIteratorGetDevice")
+    .Input("resource: resource")
+    .Output("device: string")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("LatencyStatsDataset")
+    .Input("input_dataset: variant")
+    .Input("tag: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle tag_shape;
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &tag_shape));
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalLatencyStatsDataset")
     .Input("input_dataset: variant")
     .Input("tag: string")
@@ -196,6 +401,51 @@ REGISTER_OP("ExperimentalLatencyStatsDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("LMDBDataset")
+    .Input("filenames: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetIsStateful()  // TODO(b/123753214): Source dataset ops must be marked
+                      // stateful to inhibit constant folding.
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("ExperimentalLMDBDataset")
+    .Input("filenames: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetIsStateful()  // TODO(b/123753214): Source dataset ops must be marked
+                      // stateful to inhibit constant folding.
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("MapAndBatchDataset")
+    .Input("input_dataset: variant")
+    .Input("other_arguments: Targuments")
+    .Input("batch_size: int64")
+    .Input("num_parallel_calls: int64")
+    .Input("drop_remainder: bool")
+    .Output("handle: variant")
+    .Attr("f: func")
+    .Attr("Targuments: list(type) >= 0")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .Attr("preserve_cardinality: bool = false")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      // Use index from the end to retrieve the Input shapes,
+      // so that to avoid guessing the length of "other_arguments".
+      // batch_size, num_parallel_calls, and drop_remainder are 0-D scalars.
+      shape_inference::ShapeHandle unused;
+      TF_RETURN_IF_ERROR(
+          c->WithRank(c->input(c->num_inputs() - 3), 0, &unused));
+      TF_RETURN_IF_ERROR(
+          c->WithRank(c->input(c->num_inputs() - 2), 0, &unused));
+      TF_RETURN_IF_ERROR(
+          c->WithRank(c->input(c->num_inputs() - 1), 0, &unused));
+
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalMapAndBatchDataset")
     .Input("input_dataset: variant")
     .Input("other_arguments: Targuments")
@@ -223,14 +473,6 @@ REGISTER_OP("ExperimentalMapAndBatchDataset")
       return shape_inference::ScalarShape(c);
     });
 
-REGISTER_OP("ExperimentalRebatchDataset")
-    .Input("input_dataset: variant")
-    .Input("num_workers: int64")
-    .Output("handle: variant")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
-    .SetShapeFn(shape_inference::ScalarShape);
-
 REGISTER_OP("ExperimentalMapDataset")
     .Input("input_dataset: variant")
     .Input("other_arguments: Targuments")
@@ -243,6 +485,18 @@ REGISTER_OP("ExperimentalMapDataset")
     .Attr("preserve_cardinality: bool = false")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("MatchingFilesDataset")
+    .Input("patterns: string")
+    .Output("handle: variant")
+    .SetIsStateful()  // TODO(b/123753214): Source dataset ops must be marked
+                      // stateful to inhibit constant folding.
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // `patterns` must be a scalar or a vector.
+      TF_RETURN_IF_ERROR(c->WithRankAtMost(c->input(0), 1, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalMatchingFilesDataset")
     .Input("patterns: string")
     .Output("handle: variant")
@@ -255,6 +509,29 @@ REGISTER_OP("ExperimentalMatchingFilesDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("MaxIntraOpParallelismDataset")
+    .Input("input_dataset: variant")
+    .Input("max_intra_op_parallelism: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("ExperimentalMaxIntraOpParallelismDataset")
+    .Input("input_dataset: variant")
+    .Input("max_intra_op_parallelism: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("NonSerializableDataset")
+    .Input("input_dataset: variant")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalNonSerializableDataset")
     .Input("input_dataset: variant")
     .Output("handle: variant")
@@ -262,6 +539,21 @@ REGISTER_OP("ExperimentalNonSerializableDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("ParallelInterleaveDataset")
+    .Input("input_dataset: variant")
+    .Input("other_arguments: Targuments")
+    .Input("cycle_length: int64")
+    .Input("block_length: int64")
+    .Input("sloppy: bool")
+    .Input("buffer_output_elements: int64")
+    .Input("prefetch_input_elements: int64")
+    .Output("handle: variant")
+    .Attr("f: func")
+    .Attr("Targuments: list(type) >= 0")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalParallelInterleaveDataset")
     .Input("input_dataset: variant")
     .Input("other_arguments: Targuments")
@@ -277,6 +569,23 @@ REGISTER_OP("ExperimentalParallelInterleaveDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("ParseExampleDataset")
+    .Input("input_dataset: variant")
+    .Input("num_parallel_calls: int64")
+    .Input("dense_defaults: Tdense")
+    .Output("handle: variant")
+    .Attr("sparse_keys: list(string) >= 0")
+    .Attr("dense_keys: list(string) >= 0")
+    .Attr("sparse_types: list({float,int64,string}) >= 0")
+    .Attr("Tdense: list({float,int64,string}) >= 0")
+    .Attr("dense_shapes: list(shape) >= 0")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")  // Output components will be
+                                              // sorted by key (dense_keys and
+                                              // sparse_keys combined) here.
+    .Attr("sloppy: bool = false")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalParseExampleDataset")
     .Input("input_dataset: variant")
     .Input("num_parallel_calls: int64")
@@ -294,6 +603,22 @@ REGISTER_OP("ExperimentalParseExampleDataset")
     .Attr("sloppy: bool = false")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("PrivateThreadPoolDataset")
+    .Input("input_dataset: variant")
+    .Input("num_threads: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("ExperimentalPrivateThreadPoolDataset")
+    .Input("input_dataset: variant")
+    .Input("num_threads: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalRandomDataset")
     .Input("seed: int64")
     .Input("seed2: int64")
@@ -310,6 +635,68 @@ REGISTER_OP("ExperimentalRandomDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("RandomDataset")
+    .Input("seed: int64")
+    .Input("seed2: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetIsStateful()  // TODO(b/123753214): Source dataset ops must be marked
+                      // stateful to inhibit constant folding.
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // buffer_size, seed, and seed2 should be scalars.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
+REGISTER_OP("ExperimentalRebatchDataset")
+    .Input("input_dataset: variant")
+    .Input("num_workers: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("RebatchDataset")
+    .Input("input_dataset: variant")
+    .Input("num_workers: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("SamplingDataset")
+    .Input("input_dataset: variant")
+    .Input("rate: float32")
+    .Input("seed: int64")
+    .Input("seed2: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // rate, seed, and seed2 should be scalars.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(2), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(3), 0, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
+REGISTER_OP("ScanDataset")
+    .Input("input_dataset: variant")
+    .Input("initial_state: Tstate")
+    .Input("other_arguments: Targuments")
+    .Output("handle: variant")
+    .Attr("f: func")
+    .Attr("Tstate: list(type) >= 1")
+    .Attr("Targuments: list(type) >= 0")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .Attr("preserve_cardinality: bool = false")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalScanDataset")
     .Input("input_dataset: variant")
     .Input("initial_state: Tstate")
@@ -323,6 +710,16 @@ REGISTER_OP("ExperimentalScanDataset")
     .Attr("preserve_cardinality: bool = false")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("SetStatsAggregatorDataset")
+    .Input("input_dataset: variant")
+    .Input("stats_aggregator: resource")
+    .Input("tag: string")
+    .Input("counter_prefix: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalSetStatsAggregatorDataset")
     .Input("input_dataset: variant")
     .Input("stats_aggregator: resource")
@@ -333,6 +730,20 @@ REGISTER_OP("ExperimentalSetStatsAggregatorDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("SleepDataset")
+    .Input("input_dataset: variant")
+    .Input("sleep_microseconds: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // Both inputs are scalar.
+      TF_RETURN_IF_ERROR(c->WithRankAtMost(c->input(0), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRankAtMost(c->input(1), 0, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalSleepDataset")
     .Input("input_dataset: variant")
     .Input("sleep_microseconds: int64")
@@ -347,6 +758,23 @@ REGISTER_OP("ExperimentalSleepDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("SlidingWindowDataset")
+    .Input("input_dataset: variant")
+    .Input("window_size: int64")
+    .Input("window_shift: int64")
+    .Input("window_stride: int64")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // window_size, window_shift, and window_stride should be scalars.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(2), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(3), 0, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalSlidingWindowDataset")
     .Input("input_dataset: variant")
     .Input("window_size: int64")
@@ -382,6 +810,24 @@ REGISTER_OP("SnapshotDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("SqlDataset")
+    .Input("driver_name: string")
+    .Input("data_source_name: string")
+    .Input("query: string")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetIsStateful()  // TODO(b/123753214): Source dataset ops must be marked
+                      // stateful to inhibit constant folding.
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      shape_inference::ShapeHandle unused;
+      // driver_name, data_source_name, and query should be scalars.
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &unused));
+      TF_RETURN_IF_ERROR(c->WithRank(c->input(2), 0, &unused));
+      return shape_inference::ScalarShape(c);
+    });
+
 REGISTER_OP("ExperimentalSqlDataset")
     .Input("driver_name: string")
     .Input("data_source_name: string")
@@ -400,6 +846,12 @@ REGISTER_OP("ExperimentalSqlDataset")
       return shape_inference::ScalarShape(c);
     });
 
+REGISTER_OP("StatsAggregatorHandle")
+    .Output("handle: resource")
+    .SetShapeFn(shape_inference::ScalarShape)
+    .Attr("container: string = ''")
+    .Attr("shared_name: string = ''");
+
 REGISTER_OP("ExperimentalStatsAggregatorHandle")
     .Output("handle: resource")
     .SetShapeFn(shape_inference::ScalarShape)
@@ -412,11 +864,31 @@ REGISTER_OP("StatsAggregatorHandleV2")
     .Attr("container: string = ''")
     .Attr("shared_name: string = ''");
 
+REGISTER_OP("StatsAggregatorSetSummaryWriter")
+    .Input("stats_aggregator: resource")
+    .Input("summary: resource")
+    .SetShapeFn(shape_inference::NoOutputs);
+
+REGISTER_OP("StatsAggregatorSummary")
+    .Input("iterator: resource")
+    .Output("summary: string")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalStatsAggregatorSummary")
     .Input("iterator: resource")
     .Output("summary: string")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("TakeWhileDataset")
+    .Input("input_dataset: variant")
+    .Input("other_arguments: Targuments")
+    .Output("handle: variant")
+    .Attr("predicate: func")
+    .Attr("Targuments: list(type) >= 0")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
+
 REGISTER_OP("ExperimentalTakeWhileDataset")
     .Input("input_dataset: variant")
     .Input("other_arguments: Targuments")
@@ -427,36 +899,9 @@ REGISTER_OP("ExperimentalTakeWhileDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
-REGISTER_OP("ExperimentalUnbatchDataset")
+REGISTER_OP("ThreadPoolDataset")
     .Input("input_dataset: variant")
-    .Output("handle: variant")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
-    .SetShapeFn(shape_inference::ScalarShape);
-
-REGISTER_OP("ExperimentalUniqueDataset")
-    .Input("input_dataset: variant")
-    .Output("handle: variant")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
-    .SetShapeFn(shape_inference::ScalarShape);
-
-REGISTER_OP("ExperimentalIteratorGetDevice")
-    .Input("resource: resource")
-    .Output("device: string")
-    .SetShapeFn(shape_inference::ScalarShape);
-
-REGISTER_OP("ExperimentalMaxIntraOpParallelismDataset")
-    .Input("input_dataset: variant")
-    .Input("max_intra_op_parallelism: int64")
-    .Output("handle: variant")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
-    .SetShapeFn(shape_inference::ScalarShape);
-
-REGISTER_OP("ExperimentalPrivateThreadPoolDataset")
-    .Input("input_dataset: variant")
-    .Input("num_threads: int64")
+    .Input("thread_pool: resource")
     .Output("handle: variant")
     .Attr("output_types: list(type) >= 1")
     .Attr("output_shapes: list(shape) >= 1")
@@ -470,6 +915,15 @@ REGISTER_OP("ExperimentalThreadPoolDataset")
     .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
+REGISTER_OP("ThreadPoolHandle")
+    .Output("handle: resource")
+    .SetShapeFn(shape_inference::ScalarShape)
+    .Attr("num_threads: int")
+    .Attr("max_intra_op_parallelism: int = 1")
+    .Attr("display_name: string")
+    .Attr("container: string = ''")
+    .Attr("shared_name: string = ''");
+
 REGISTER_OP("ExperimentalThreadPoolHandle")
     .Output("handle: resource")
     .SetShapeFn(shape_inference::ScalarShape)
@@ -479,136 +933,32 @@ REGISTER_OP("ExperimentalThreadPoolHandle")
     .Attr("container: string = ''")
     .Attr("shared_name: string = ''");
 
-REGISTER_OP("ExperimentalAssertNextDataset")
+REGISTER_OP("UnbatchDataset")
     .Input("input_dataset: variant")
-    .Input("transformations: string")
     .Output("handle: variant")
     .Attr("output_types: list(type) >= 1")
     .Attr("output_shapes: list(shape) >= 1")
-    .SetShapeFn([](shape_inference::InferenceContext* c) {
-      shape_inference::ShapeHandle unused;
-      // transformations should be a vector.
-      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 1, &unused));
-      return shape_inference::ScalarShape(c);
-    });
-
-REGISTER_OP("ExperimentalNumaMapAndBatchDataset")
-    .Input("input_dataset: variant")
-    .Input("other_arguments: Targuments")
-    .Input("batch_size: int64")
-    .Input("num_parallel_calls: int64")
-    .Input("drop_remainder: bool")
-    .Output("handle: variant")
-    .Attr("f: func")
-    .Attr("Targuments: list(type) >= 0")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
-    .Attr("preserve_cardinality: bool = false")
-    .SetShapeFn([](shape_inference::InferenceContext* c) {
-      // Use index from the end to retrieve the Input shapes,
-      // so that to avoid guessing the length of "other_arguments".
-      // batch_size, num_parallel_batches, and drop_remainder are 0-D scalars.
-      shape_inference::ShapeHandle unused;
-      TF_RETURN_IF_ERROR(
-          c->WithRank(c->input(c->num_inputs() - 3), 0, &unused));
-      TF_RETURN_IF_ERROR(
-          c->WithRank(c->input(c->num_inputs() - 2), 0, &unused));
-      TF_RETURN_IF_ERROR(
-          c->WithRank(c->input(c->num_inputs() - 1), 0, &unused));
-
-      return shape_inference::ScalarShape(c);
-    });
-
-REGISTER_OP("ExperimentalLMDBDataset")
-    .Input("filenames: string")
-    .Output("handle: variant")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
-    .SetIsStateful()  // TODO(b/123753214): Source dataset ops must be marked
-                      // stateful to inhibit constant folding.
-    .SetShapeFn(shape_inference::ScalarShape);
-
-REGISTER_OP("ExperimentalChooseFastestDataset")
-    .Input("input_datasets: N * variant")
-    .Output("handle: variant")
-    .Attr("N: int >= 2")
-    .Attr("num_experiments: int")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
-REGISTER_OP("ExperimentalIdentityIndexedDataset")
-    .Input("size: uint64")
-    .Output("handle: variant")
-    .SetIsStateful()
-    .SetShapeFn(
-        shape_inference::ScalarShape);  // TODO(saeta): check input shapes.
-
-REGISTER_OP("SamplingDataset")
+REGISTER_OP("ExperimentalUnbatchDataset")
     .Input("input_dataset: variant")
-    .Input("rate: float32")
-    .Input("seed: int64")
-    .Input("seed2: int64")
     .Output("handle: variant")
     .Attr("output_types: list(type) >= 1")
     .Attr("output_shapes: list(shape) >= 1")
-    .SetShapeFn([](shape_inference::InferenceContext* c) {
-      shape_inference::ShapeHandle unused;
-      // rate, seed, and seed2 should be scalars.
-      TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 0, &unused));
-      TF_RETURN_IF_ERROR(c->WithRank(c->input(2), 0, &unused));
-      TF_RETURN_IF_ERROR(c->WithRank(c->input(3), 0, &unused));
-      return shape_inference::ScalarShape(c);
-    });
-
-///////////////////////////////////////////////////////////////////////////////
-//     IndexedDataset Internals
-///////////////////////////////////////////////////////////////////////////////
-
-// Creates the handle.
-REGISTER_OP("ExperimentalMaterializedIndexDatasetHandle")
-    .Output("handle: resource")
-    .Attr("container: string")
-    .Attr("shared_name: string")
-    .Attr("output_types: list(type) >= 1")
-    .Attr("output_shapes: list(shape) >= 1")
     .SetShapeFn(shape_inference::ScalarShape);
 
-// Actually materialize the materialize handle.
-REGISTER_OP("ExperimentalIndexedDatasetMaterialize")
-    .Input("dataset: variant")
-    .Input("materialized: resource")
-    .SetShapeFn(shape_inference::NoOutputs);
-
-namespace {
-
-Status GetShapeFn(shape_inference::InferenceContext* c) {
-  shape_inference::ShapeHandle unused;
-  TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 0, &unused));
-  std::vector<PartialTensorShape> output_shapes;
-  TF_RETURN_IF_ERROR(c->GetAttr("output_shapes", &output_shapes));
-  if (output_shapes.size() != c->num_outputs()) {
-    return errors::InvalidArgument(
-        "`output_shapes` must be the same length as `output_types` (",
-        output_shapes.size(), " vs. ", c->num_outputs());
-  }
-  for (size_t i = 0; i < output_shapes.size(); ++i) {
-    shape_inference::ShapeHandle output_shape_handle;
-    TF_RETURN_IF_ERROR(c->MakeShapeFromPartialTensorShape(
-        output_shapes[i], &output_shape_handle));
-    c->set_output(static_cast<int>(i), output_shape_handle);
-  }
-  return Status::OK();
-}
-
-}  // namespace
-
-REGISTER_OP("ExperimentalIndexedDatasetGet")
-    .Input("materialized: resource")
-    .Input("index: uint64")
-    .Output("components: output_types")
+REGISTER_OP("UniqueDataset")
+    .Input("input_dataset: variant")
+    .Output("handle: variant")
     .Attr("output_types: list(type) >= 1")
     .Attr("output_shapes: list(shape) >= 1")
-    .SetShapeFn(GetShapeFn);
+    .SetShapeFn(shape_inference::ScalarShape);
+
+REGISTER_OP("ExperimentalUniqueDataset")
+    .Input("input_dataset: variant")
+    .Output("handle: variant")
+    .Attr("output_types: list(type) >= 1")
+    .Attr("output_shapes: list(shape) >= 1")
+    .SetShapeFn(shape_inference::ScalarShape);
 
 }  // namespace tensorflow
diff --git a/tensorflow/python/data/experimental/ops/batching.py b/tensorflow/python/data/experimental/ops/batching.py
index af68eb233c4..65e2b2571b4 100644
--- a/tensorflow/python/data/experimental/ops/batching.py
+++ b/tensorflow/python/data/experimental/ops/batching.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import convert
 from tensorflow.python.data.util import nest
@@ -246,11 +247,18 @@ class _DenseToSparseBatchDataset(dataset_ops.UnaryDataset):
         dataset_ops.get_legacy_output_types(input_dataset),
         tensor_shape.vector(None).concatenate(self._row_shape))
 
-    variant_tensor = ged_ops.experimental_dense_to_sparse_batch_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._batch_size,
-        row_shape=convert.partial_shape_to_tensor(self._row_shape),
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.dense_to_sparse_batch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._batch_size,
+          row_shape=convert.partial_shape_to_tensor(self._row_shape),
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_dense_to_sparse_batch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._batch_size,
+          row_shape=convert.partial_shape_to_tensor(self._row_shape),
+          **self._flat_structure)
     super(_DenseToSparseBatchDataset, self).__init__(input_dataset,
                                                      variant_tensor)
 
@@ -294,15 +302,26 @@ class _MapAndBatchDataset(dataset_ops.UnaryDataset):
           lambda component_spec: component_spec._batch(None),
           self._map_func.output_structure)
     # pylint: enable=protected-access
-    variant_tensor = ged_ops.experimental_map_and_batch_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._map_func.function.captured_inputs,
-        f=self._map_func.function,
-        batch_size=self._batch_size_t,
-        num_parallel_calls=self._num_parallel_calls_t,
-        drop_remainder=self._drop_remainder_t,
-        preserve_cardinality=True,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.map_and_batch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._map_func.function.captured_inputs,
+          f=self._map_func.function,
+          batch_size=self._batch_size_t,
+          num_parallel_calls=self._num_parallel_calls_t,
+          drop_remainder=self._drop_remainder_t,
+          preserve_cardinality=True,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_map_and_batch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._map_func.function.captured_inputs,
+          f=self._map_func.function,
+          batch_size=self._batch_size_t,
+          num_parallel_calls=self._num_parallel_calls_t,
+          drop_remainder=self._drop_remainder_t,
+          preserve_cardinality=True,
+          **self._flat_structure)
     super(_MapAndBatchDataset, self).__init__(input_dataset, variant_tensor)
 
   def _functions(self):
diff --git a/tensorflow/python/data/experimental/ops/cardinality.py b/tensorflow/python/data/experimental/ops/cardinality.py
index 0d596f68dd5..d7f47646a11 100644
--- a/tensorflow/python/data/experimental/ops/cardinality.py
+++ b/tensorflow/python/data/experimental/ops/cardinality.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.ops import gen_experimental_dataset_ops as ged_ops
 from tensorflow.python.util.tf_export import tf_export
 
@@ -47,4 +48,8 @@ def cardinality(dataset):
     the cardinality is infinite or unknown, the operation returns the named
     constant `INFINITE_CARDINALITY` and `UNKNOWN_CARDINALITY` respectively.
   """
-  return ged_ops.experimental_dataset_cardinality(dataset._variant_tensor)  # pylint: disable=protected-access
+
+  if compat.forward_compatible(2019, 8, 3):
+    return ged_ops.dataset_cardinality(dataset._variant_tensor)  # pylint: disable=protected-access
+  else:
+    return ged_ops.experimental_dataset_cardinality(dataset._variant_tensor)  # pylint: disable=protected-access
diff --git a/tensorflow/python/data/experimental/ops/distribute.py b/tensorflow/python/data/experimental/ops/distribute.py
index 78d7f7f7a83..ce6ff8bd564 100644
--- a/tensorflow/python/data/experimental/ops/distribute.py
+++ b/tensorflow/python/data/experimental/ops/distribute.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
 from tensorflow.python.data.util import structure
@@ -47,11 +48,18 @@ class _AutoShardDataset(dataset_ops.UnaryDataset):
     self._input_dataset = input_dataset
 
     self._element_spec = input_dataset.element_spec
-    variant_tensor = ged_ops.experimental_auto_shard_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        num_workers=num_workers,
-        index=index,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.auto_shard_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          num_workers=num_workers,
+          index=index,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_auto_shard_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          num_workers=num_workers,
+          index=index,
+          **self._flat_structure)
     super(_AutoShardDataset, self).__init__(input_dataset, variant_tensor)
 
   @property
@@ -87,10 +95,16 @@ class _RebatchDataset(dataset_ops.UnaryDataset):
 
     self._element_spec = structure.convert_legacy_structure(
         input_types, output_shapes, input_classes)
-    variant_tensor = ged_ops.experimental_rebatch_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        num_workers=num_workers,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.rebatch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          num_workers=num_workers,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_rebatch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          num_workers=num_workers,
+          **self._flat_structure)
     super(_RebatchDataset, self).__init__(input_dataset, variant_tensor)
 
   @property
diff --git a/tensorflow/python/data/experimental/ops/error_ops.py b/tensorflow/python/data/experimental/ops/error_ops.py
index d5803d6ae88..1aa2ad7375a 100644
--- a/tensorflow/python/data/experimental/ops/error_ops.py
+++ b/tensorflow/python/data/experimental/ops/error_ops.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.ops import gen_experimental_dataset_ops
 from tensorflow.python.util.tf_export import tf_export
@@ -59,8 +60,14 @@ class _IgnoreErrorsDataset(dataset_ops.UnaryUnchangedStructureDataset):
   def __init__(self, input_dataset):
     """See `Dataset.ignore_errors()` for details."""
     self._input_dataset = input_dataset
-    variant_tensor = (
-        gen_experimental_dataset_ops.experimental_ignore_errors_dataset(
-            self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-            **self._flat_structure))
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = (
+          gen_experimental_dataset_ops.ignore_errors_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              **self._flat_structure))
+    else:
+      variant_tensor = (
+          gen_experimental_dataset_ops.experimental_ignore_errors_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              **self._flat_structure))
     super(_IgnoreErrorsDataset, self).__init__(input_dataset, variant_tensor)
diff --git a/tensorflow/python/data/experimental/ops/grouping.py b/tensorflow/python/data/experimental/ops/grouping.py
index 3018e36d763..1f99157ad78 100644
--- a/tensorflow/python/data/experimental/ops/grouping.py
+++ b/tensorflow/python/data/experimental/ops/grouping.py
@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import numpy as np
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
 from tensorflow.python.data.util import structure
@@ -253,17 +254,30 @@ class _GroupByReducerDataset(dataset_ops.UnaryDataset):
     self._make_init_func(reducer.init_func)
     self._make_reduce_func(reducer.reduce_func, input_dataset)
     self._make_finalize_func(reducer.finalize_func)
-    variant_tensor = ged_ops.experimental_group_by_reducer_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._key_func.function.captured_inputs,
-        self._init_func.function.captured_inputs,
-        self._reduce_func.function.captured_inputs,
-        self._finalize_func.function.captured_inputs,
-        key_func=self._key_func.function,
-        init_func=self._init_func.function,
-        reduce_func=self._reduce_func.function,
-        finalize_func=self._finalize_func.function,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.experimental_group_by_reducer_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._key_func.function.captured_inputs,
+          self._init_func.function.captured_inputs,
+          self._reduce_func.function.captured_inputs,
+          self._finalize_func.function.captured_inputs,
+          key_func=self._key_func.function,
+          init_func=self._init_func.function,
+          reduce_func=self._reduce_func.function,
+          finalize_func=self._finalize_func.function,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.group_by_reducer_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._key_func.function.captured_inputs,
+          self._init_func.function.captured_inputs,
+          self._reduce_func.function.captured_inputs,
+          self._finalize_func.function.captured_inputs,
+          key_func=self._key_func.function,
+          init_func=self._init_func.function,
+          reduce_func=self._reduce_func.function,
+          finalize_func=self._finalize_func.function,
+          **self._flat_structure)
     super(_GroupByReducerDataset, self).__init__(input_dataset, variant_tensor)
 
   def _make_key_func(self, key_func, input_dataset):
@@ -375,15 +389,26 @@ class _GroupByWindowDataset(dataset_ops.UnaryDataset):
     self._make_key_func(key_func, input_dataset)
     self._make_reduce_func(reduce_func, input_dataset)
     self._make_window_size_func(window_size_func)
-    variant_tensor = ged_ops.experimental_group_by_window_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._key_func.function.captured_inputs,
-        self._reduce_func.function.captured_inputs,
-        self._window_size_func.function.captured_inputs,
-        key_func=self._key_func.function,
-        reduce_func=self._reduce_func.function,
-        window_size_func=self._window_size_func.function,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.group_by_window_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._key_func.function.captured_inputs,
+          self._reduce_func.function.captured_inputs,
+          self._window_size_func.function.captured_inputs,
+          key_func=self._key_func.function,
+          reduce_func=self._reduce_func.function,
+          window_size_func=self._window_size_func.function,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_group_by_window_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._key_func.function.captured_inputs,
+          self._reduce_func.function.captured_inputs,
+          self._window_size_func.function.captured_inputs,
+          key_func=self._key_func.function,
+          reduce_func=self._reduce_func.function,
+          window_size_func=self._window_size_func.function,
+          **self._flat_structure)
     super(_GroupByWindowDataset, self).__init__(input_dataset, variant_tensor)
 
   def _make_window_size_func(self, window_size_func):
diff --git a/tensorflow/python/data/experimental/ops/interleave_ops.py b/tensorflow/python/data/experimental/ops/interleave_ops.py
index 257639a2560..bd47adb3d16 100644
--- a/tensorflow/python/data/experimental/ops/interleave_ops.py
+++ b/tensorflow/python/data/experimental/ops/interleave_ops.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.experimental.ops import random_ops
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.ops import readers
@@ -125,11 +126,18 @@ class _DirectedInterleaveDataset(dataset_ops.Dataset):
 
   def _as_variant_tensor(self):
     # pylint: disable=protected-access
-    return (
-        gen_experimental_dataset_ops.experimental_directed_interleave_dataset(
-            self._selector_input._variant_tensor,
-            [data_input._variant_tensor for data_input in self._data_inputs],
-            **self._flat_structure))
+    if compat.forward_compatible(2019, 8, 3):
+      return (
+          gen_experimental_dataset_ops.directed_interleave_dataset(
+              self._selector_input._variant_tensor,
+              [data_input._variant_tensor for data_input in self._data_inputs],
+              **self._flat_structure))
+    else:
+      return (
+          gen_experimental_dataset_ops.experimental_directed_interleave_dataset(
+              self._selector_input._variant_tensor,
+              [data_input._variant_tensor for data_input in self._data_inputs],
+              **self._flat_structure))
     # pylint: enable=protected-access
 
   def _inputs(self):
diff --git a/tensorflow/python/data/experimental/ops/matching_files.py b/tensorflow/python/data/experimental/ops/matching_files.py
index e2b5ff13fd6..56f4dd81e16 100644
--- a/tensorflow/python/data/experimental/ops/matching_files.py
+++ b/tensorflow/python/data/experimental/ops/matching_files.py
@@ -18,6 +18,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import structure
 from tensorflow.python.framework import dtypes
@@ -31,7 +32,11 @@ class MatchingFilesDataset(dataset_ops.DatasetSource):
   def __init__(self, patterns):
     self._patterns = ops.convert_to_tensor(
         patterns, dtype=dtypes.string, name="patterns")
-    variant_tensor = ged_ops.experimental_matching_files_dataset(self._patterns)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.matching_files_dataset(self._patterns)
+    else:
+      variant_tensor = ged_ops.experimental_matching_files_dataset(
+          self._patterns)
     super(MatchingFilesDataset, self).__init__(variant_tensor)
 
   @property
diff --git a/tensorflow/python/data/experimental/ops/optimization.py b/tensorflow/python/data/experimental/ops/optimization.py
index dc6c0a3b264..15a2bec9514 100644
--- a/tensorflow/python/data/experimental/ops/optimization.py
+++ b/tensorflow/python/data/experimental/ops/optimization.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -104,11 +105,18 @@ class _AssertNextDataset(dataset_ops.UnaryUnchangedStructureDataset):
       raise ValueError("At least one transformation should be specified")
     self._transformations = ops.convert_to_tensor(
         transformations, dtype=dtypes.string, name="transformations")
-    variant_tensor = (
-        gen_experimental_dataset_ops.experimental_assert_next_dataset(
-            self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-            self._transformations,
-            **self._flat_structure))
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = (
+          gen_experimental_dataset_ops.assert_next_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              self._transformations,
+              **self._flat_structure))
+    else:
+      variant_tensor = (
+          gen_experimental_dataset_ops.experimental_assert_next_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              self._transformations,
+              **self._flat_structure))
     super(_AssertNextDataset, self).__init__(input_dataset, variant_tensor)
 
 
@@ -118,10 +126,16 @@ class _NonSerializableDataset(dataset_ops.UnaryUnchangedStructureDataset):
   def __init__(self, input_dataset):
     """See `non_serializable()` for details."""
     self._input_dataset = input_dataset
-    variant_tensor = (
-        gen_experimental_dataset_ops.experimental_non_serializable_dataset(
-            self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-            **self._flat_structure))
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = (
+          gen_experimental_dataset_ops.non_serializable_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              **self._flat_structure))
+    else:
+      variant_tensor = (
+          gen_experimental_dataset_ops.experimental_non_serializable_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              **self._flat_structure))
     super(_NonSerializableDataset, self).__init__(input_dataset, variant_tensor)
 
 
@@ -157,11 +171,18 @@ class _ChooseFastestDataset(dataset_ops.DatasetV2):
     """
     self._datasets = list(datasets)
     self._element_spec = self._datasets[0].element_spec
-    variant_tensor = (
-        gen_experimental_dataset_ops.experimental_choose_fastest_dataset(
-            [dataset._variant_tensor for dataset in self._datasets],  # pylint: disable=protected-access
-            num_experiments=num_experiments,
-            **self._flat_structure))
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = (
+          gen_experimental_dataset_ops.choose_fastest_dataset(
+              [dataset._variant_tensor for dataset in self._datasets],  # pylint: disable=protected-access
+              num_experiments=num_experiments,
+              **self._flat_structure))
+    else:
+      variant_tensor = (
+          gen_experimental_dataset_ops.experimental_choose_fastest_dataset(
+              [dataset._variant_tensor for dataset in self._datasets],  # pylint: disable=protected-access
+              num_experiments=num_experiments,
+              **self._flat_structure))
     super(_ChooseFastestDataset, self).__init__(variant_tensor)
 
   def _inputs(self):
diff --git a/tensorflow/python/data/experimental/ops/parsing_ops.py b/tensorflow/python/data/experimental/ops/parsing_ops.py
index 4ce3bf5229e..e4ee6fa8809 100644
--- a/tensorflow/python/data/experimental/ops/parsing_ops.py
+++ b/tensorflow/python/data/experimental/ops/parsing_ops.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import structure
 from tensorflow.python.framework import dtypes
@@ -79,16 +80,28 @@ class _ParseExampleDataset(dataset_ops.UnaryDataset):
     self._element_spec = structure.convert_legacy_structure(
         output_types, output_shapes, output_classes)
 
-    variant_tensor = (
-        gen_experimental_dataset_ops.experimental_parse_example_dataset(
-            self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-            self._num_parallel_calls,
-            self._dense_defaults,
-            self._sparse_keys,
-            self._dense_keys,
-            self._sparse_types,
-            self._dense_shapes,
-            **self._flat_structure))
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = (
+          gen_experimental_dataset_ops.parse_example_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              self._num_parallel_calls,
+              self._dense_defaults,
+              self._sparse_keys,
+              self._dense_keys,
+              self._sparse_types,
+              self._dense_shapes,
+              **self._flat_structure))
+    else:
+      variant_tensor = (
+          gen_experimental_dataset_ops.experimental_parse_example_dataset(
+              self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+              self._num_parallel_calls,
+              self._dense_defaults,
+              self._sparse_keys,
+              self._dense_keys,
+              self._sparse_types,
+              self._dense_shapes,
+              **self._flat_structure))
     super(_ParseExampleDataset, self).__init__(input_dataset, variant_tensor)
 
   @property
diff --git a/tensorflow/python/data/experimental/ops/random_ops.py b/tensorflow/python/data/experimental/ops/random_ops.py
index ce72889077e..dc7e3bd3f8f 100644
--- a/tensorflow/python/data/experimental/ops/random_ops.py
+++ b/tensorflow/python/data/experimental/ops/random_ops.py
@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import functools
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import random_seed
 from tensorflow.python.data.util import structure
@@ -34,8 +35,12 @@ class RandomDatasetV2(dataset_ops.DatasetSource):
   def __init__(self, seed=None):
     """A `Dataset` of pseudorandom values."""
     self._seed, self._seed2 = random_seed.get_seed(seed)
-    variant_tensor = gen_experimental_dataset_ops.experimental_random_dataset(
-        seed=self._seed, seed2=self._seed2, **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = gen_experimental_dataset_ops.random_dataset(
+          seed=self._seed, seed2=self._seed2, **self._flat_structure)
+    else:
+      variant_tensor = gen_experimental_dataset_ops.experimental_random_dataset(
+          seed=self._seed, seed2=self._seed2, **self._flat_structure)
     super(RandomDatasetV2, self).__init__(variant_tensor)
 
   @property
diff --git a/tensorflow/python/data/experimental/ops/readers.py b/tensorflow/python/data/experimental/ops/readers.py
index 07295bfea90..bec98a977dd 100644
--- a/tensorflow/python/data/experimental/ops/readers.py
+++ b/tensorflow/python/data/experimental/ops/readers.py
@@ -23,6 +23,7 @@ import functools
 
 import numpy as np
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.experimental.ops import batching
 from tensorflow.python.data.experimental.ops import error_ops
 from tensorflow.python.data.experimental.ops import interleave_ops
@@ -664,17 +665,30 @@ class CsvDatasetV2(dataset_ops.DatasetSource):
     )
     self._element_spec = tuple(
         structure.TensorStructure(d.dtype, []) for d in self._record_defaults)
-    variant_tensor = gen_experimental_dataset_ops.experimental_csv_dataset(
-        filenames=self._filenames,
-        record_defaults=self._record_defaults,
-        buffer_size=self._buffer_size,
-        header=self._header,
-        output_shapes=self._flat_shapes,
-        field_delim=self._field_delim,
-        use_quote_delim=self._use_quote_delim,
-        na_value=self._na_value,
-        select_cols=self._select_cols,
-        compression_type=self._compression_type)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = gen_experimental_dataset_ops.csv_dataset(
+          filenames=self._filenames,
+          record_defaults=self._record_defaults,
+          buffer_size=self._buffer_size,
+          header=self._header,
+          output_shapes=self._flat_shapes,
+          field_delim=self._field_delim,
+          use_quote_delim=self._use_quote_delim,
+          na_value=self._na_value,
+          select_cols=self._select_cols,
+          compression_type=self._compression_type)
+    else:
+      variant_tensor = gen_experimental_dataset_ops.experimental_csv_dataset(
+          filenames=self._filenames,
+          record_defaults=self._record_defaults,
+          buffer_size=self._buffer_size,
+          header=self._header,
+          output_shapes=self._flat_shapes,
+          field_delim=self._field_delim,
+          use_quote_delim=self._use_quote_delim,
+          na_value=self._na_value,
+          select_cols=self._select_cols,
+          compression_type=self._compression_type)
     super(CsvDatasetV2, self).__init__(variant_tensor)
 
   @property
@@ -957,9 +971,14 @@ class SqlDatasetV2(dataset_ops.DatasetSource):
         query, dtype=dtypes.string, name="query")
     self._element_spec = nest.map_structure(
         lambda dtype: structure.TensorStructure(dtype, []), output_types)
-    variant_tensor = gen_experimental_dataset_ops.experimental_sql_dataset(
-        self._driver_name, self._data_source_name, self._query,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = gen_experimental_dataset_ops.sql_dataset(
+          self._driver_name, self._data_source_name, self._query,
+          **self._flat_structure)
+    else:
+      variant_tensor = gen_experimental_dataset_ops.experimental_sql_dataset(
+          self._driver_name, self._data_source_name, self._query,
+          **self._flat_structure)
     super(SqlDatasetV2, self).__init__(variant_tensor)
 
   @property
diff --git a/tensorflow/python/data/experimental/ops/scan_ops.py b/tensorflow/python/data/experimental/ops/scan_ops.py
index e1f671c39f7..a81f5e64fee 100644
--- a/tensorflow/python/data/experimental/ops/scan_ops.py
+++ b/tensorflow/python/data/experimental/ops/scan_ops.py
@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import collections
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
 from tensorflow.python.data.util import structure
@@ -122,13 +123,22 @@ class _ScanDataset(dataset_ops.UnaryDataset):
     self._scan_func = wrapped_func
     self._scan_func.function.add_to_graph(ops.get_default_graph())
     # pylint: disable=protected-access
-    variant_tensor = gen_experimental_dataset_ops.experimental_scan_dataset(
-        self._input_dataset._variant_tensor,
-        structure.to_tensor_list(self._state_structure, self._initial_state),
-        self._scan_func.function.captured_inputs,
-        f=self._scan_func.function,
-        preserve_cardinality=True,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = gen_experimental_dataset_ops.scan_dataset(
+          self._input_dataset._variant_tensor,
+          structure.to_tensor_list(self._state_structure, self._initial_state),
+          self._scan_func.function.captured_inputs,
+          f=self._scan_func.function,
+          preserve_cardinality=True,
+          **self._flat_structure)
+    else:
+      variant_tensor = gen_experimental_dataset_ops.experimental_scan_dataset(
+          self._input_dataset._variant_tensor,
+          structure.to_tensor_list(self._state_structure, self._initial_state),
+          self._scan_func.function.captured_inputs,
+          f=self._scan_func.function,
+          preserve_cardinality=True,
+          **self._flat_structure)
     super(_ScanDataset, self).__init__(input_dataset, variant_tensor)
 
   def _functions(self):
diff --git a/tensorflow/python/data/experimental/ops/sleep.py b/tensorflow/python/data/experimental/ops/sleep.py
index 9becceef2a2..837ec0038cf 100644
--- a/tensorflow/python/data/experimental/ops/sleep.py
+++ b/tensorflow/python/data/experimental/ops/sleep.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.ops import gen_experimental_dataset_ops
 
@@ -27,10 +28,16 @@ class _SleepDataset(dataset_ops.UnaryUnchangedStructureDataset):
   def __init__(self, input_dataset, sleep_microseconds):
     self._input_dataset = input_dataset
     self._sleep_microseconds = sleep_microseconds
-    variant_tensor = gen_experimental_dataset_ops.experimental_sleep_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._sleep_microseconds,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = gen_experimental_dataset_ops.sleep_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._sleep_microseconds,
+          **self._flat_structure)
+    else:
+      variant_tensor = gen_experimental_dataset_ops.experimental_sleep_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._sleep_microseconds,
+          **self._flat_structure)
     super(_SleepDataset, self).__init__(input_dataset, variant_tensor)
 
 
diff --git a/tensorflow/python/data/experimental/ops/stats_aggregator.py b/tensorflow/python/data/experimental/ops/stats_aggregator.py
index 2fc87b123c4..cb8239c5d55 100644
--- a/tensorflow/python/data/experimental/ops/stats_aggregator.py
+++ b/tensorflow/python/data/experimental/ops/stats_aggregator.py
@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import tempfile
 
+from tensorflow.python.compat import compat
 from tensorflow.python.ops import gen_experimental_dataset_ops as ged_ops
 from tensorflow.python.ops import summary_ops_v2
 from tensorflow.python.util.tf_export import tf_export
@@ -125,7 +126,10 @@ class StatsAggregatorV1(object):
 
   def __init__(self):
     """Creates a `StatsAggregator`."""
-    self._resource = ged_ops.experimental_stats_aggregator_handle()
+    if compat.forward_compatible(2019, 8, 3):
+      self._resource = ged_ops.stats_aggregator_handle()
+    else:
+      self._resource = ged_ops.experimental_stats_aggregator_handle()
 
   def get_summary(self):
     """Returns a string `tf.Tensor` that summarizes the aggregated statistics.
@@ -137,7 +141,10 @@ class StatsAggregatorV1(object):
     Returns:
       A scalar string `tf.Tensor` that summarizes the aggregated statistics.
     """
-    return ged_ops.experimental_stats_aggregator_summary(self._resource)
+    if compat.forward_compatible(2019, 8, 3):
+      return ged_ops.stats_aggregator_summary(self._resource)
+    else:
+      return ged_ops.experimental_stats_aggregator_summary(self._resource)
 
 
 # TODO(b/116314787): Change this to StatsAggregatorV2 when we have stable
diff --git a/tensorflow/python/data/experimental/ops/stats_ops.py b/tensorflow/python/data/experimental/ops/stats_ops.py
index 757e9234875..02d3f1e793a 100644
--- a/tensorflow/python/data/experimental/ops/stats_ops.py
+++ b/tensorflow/python/data/experimental/ops/stats_ops.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -65,10 +66,14 @@ def bytes_produced_stats(tag):
   """
 
   def _apply_fn(dataset):
-    return _StatsDataset(
-        dataset,
-        gen_experimental_dataset_ops.experimental_bytes_produced_stats_dataset,
-        tag)
+    if compat.forward_compatible(2019, 8, 3):
+      return _StatsDataset(
+          dataset, gen_experimental_dataset_ops.bytes_produced_stats_dataset,
+          tag)
+    else:
+      return _StatsDataset(
+          dataset, gen_experimental_dataset_ops
+          .experimental_bytes_produced_stats_dataset, tag)
 
   return _apply_fn
 
@@ -90,9 +95,14 @@ def latency_stats(tag):
   """
 
   def _apply_fn(dataset):
-    return _StatsDataset(
-        dataset,
-        gen_experimental_dataset_ops.experimental_latency_stats_dataset, tag)
+    if compat.forward_compatible(2019, 8, 3):
+      return _StatsDataset(
+          dataset,
+          gen_experimental_dataset_ops.latency_stats_dataset, tag)
+    else:
+      return _StatsDataset(
+          dataset,
+          gen_experimental_dataset_ops.experimental_latency_stats_dataset, tag)
 
   return _apply_fn
 
diff --git a/tensorflow/python/data/experimental/ops/take_while_ops.py b/tensorflow/python/data/experimental/ops/take_while_ops.py
index 7c8da158e3b..ab629d78226 100644
--- a/tensorflow/python/data/experimental/ops/take_while_ops.py
+++ b/tensorflow/python/data/experimental/ops/take_while_ops.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import structure as structure_lib
 from tensorflow.python.framework import dtypes
@@ -41,11 +42,18 @@ class _TakeWhileDataset(dataset_ops.UnaryUnchangedStructureDataset):
       raise ValueError("`predicate` must return a scalar boolean tensor.")
 
     self._predicate = wrapped_func
-    var_tensor = gen_experimental_dataset_ops.experimental_take_while_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        other_arguments=self._predicate.function.captured_inputs,
-        predicate=self._predicate.function,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      var_tensor = gen_experimental_dataset_ops.take_while_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          other_arguments=self._predicate.function.captured_inputs,
+          predicate=self._predicate.function,
+          **self._flat_structure)
+    else:
+      var_tensor = gen_experimental_dataset_ops.experimental_take_while_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          other_arguments=self._predicate.function.captured_inputs,
+          predicate=self._predicate.function,
+          **self._flat_structure)
     super(_TakeWhileDataset, self).__init__(input_dataset, var_tensor)
 
   def _functions(self):
diff --git a/tensorflow/python/data/experimental/ops/threadpool.py b/tensorflow/python/data/experimental/ops/threadpool.py
index 7a9ede96d2d..0997e46db25 100644
--- a/tensorflow/python/data/experimental/ops/threadpool.py
+++ b/tensorflow/python/data/experimental/ops/threadpool.py
@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import threading
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.eager import context
 from tensorflow.python.ops import gen_experimental_dataset_ops as ged_ops
@@ -46,18 +47,31 @@ class PrivateThreadPool(object):
     """Creates a `PrivateThreadPool` with the given number of threads."""
     if context.executing_eagerly():
       shared_name = _generate_shared_name("privatethreadpool")
-      self._resource = ged_ops.experimental_thread_pool_handle(
-          num_threads=num_threads,
-          max_intra_op_parallelism=max_intra_op_parallelism,
-          display_name=display_name,
-          shared_name=shared_name)
+      if compat.forward_compatible(2019, 8, 3):
+        self._resource = ged_ops.thread_pool_handle(
+            num_threads=num_threads,
+            max_intra_op_parallelism=max_intra_op_parallelism,
+            display_name=display_name,
+            shared_name=shared_name)
+      else:
+        self._resource = ged_ops.experimental_thread_pool_handle(
+            num_threads=num_threads,
+            max_intra_op_parallelism=max_intra_op_parallelism,
+            display_name=display_name,
+            shared_name=shared_name)
       self._resource_deleter = resource_variable_ops.EagerResourceDeleter(
           handle=self._resource, handle_device=context.context().device_name)
     else:
-      self._resource = ged_ops.experimental_thread_pool_handle(
-          num_threads=num_threads,
-          max_intra_op_parallelism=max_intra_op_parallelism,
-          display_name=display_name)
+      if compat.forward_compatible(2019, 8, 3):
+        self._resource = ged_ops.thread_pool_handle(
+            num_threads=num_threads,
+            max_intra_op_parallelism=max_intra_op_parallelism,
+            display_name=display_name)
+      else:
+        self._resource = ged_ops.experimental_thread_pool_handle(
+            num_threads=num_threads,
+            max_intra_op_parallelism=max_intra_op_parallelism,
+            display_name=display_name)
 
 
 class _ThreadPoolDataset(dataset_ops.UnaryUnchangedStructureDataset):
@@ -66,10 +80,16 @@ class _ThreadPoolDataset(dataset_ops.UnaryUnchangedStructureDataset):
   def __init__(self, input_dataset, thread_pool):
     self._input_dataset = input_dataset
     self._thread_pool = thread_pool
-    variant_tensor = ged_ops.experimental_thread_pool_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._thread_pool._resource,  # pylint: disable=protected-access
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.thread_pool_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._thread_pool._resource,  # pylint: disable=protected-access
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_thread_pool_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._thread_pool._resource,  # pylint: disable=protected-access
+          **self._flat_structure)
     super(_ThreadPoolDataset, self).__init__(input_dataset, variant_tensor)
 
 
diff --git a/tensorflow/python/data/experimental/ops/unique.py b/tensorflow/python/data/experimental/ops/unique.py
index be902869f94..396ec7a6e14 100644
--- a/tensorflow/python/data/experimental/ops/unique.py
+++ b/tensorflow/python/data/experimental/ops/unique.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.framework import dtypes
 from tensorflow.python.ops import gen_experimental_dataset_ops
@@ -59,7 +60,12 @@ class _UniqueDataset(dataset_ops.UnaryUnchangedStructureDataset):
       raise TypeError(
           "`tf.data.experimental.unique()` only supports inputs with a single "
           "`tf.int32`, `tf.int64`, or `tf.string` component.")
-    variant_tensor = gen_experimental_dataset_ops.experimental_unique_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = gen_experimental_dataset_ops.unique_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          **self._flat_structure)
+    else:
+      variant_tensor = gen_experimental_dataset_ops.experimental_unique_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          **self._flat_structure)
     super(_UniqueDataset, self).__init__(input_dataset, variant_tensor)
diff --git a/tensorflow/python/data/experimental/ops/writers.py b/tensorflow/python/data/experimental/ops/writers.py
index 756d79537f5..0c4d4b6ebd5 100644
--- a/tensorflow/python/data/experimental/ops/writers.py
+++ b/tensorflow/python/data/experimental/ops/writers.py
@@ -17,6 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import convert
 from tensorflow.python.data.util import structure
@@ -83,5 +84,9 @@ class TFRecordWriter(object):
           "produces shape {0} and types {1}".format(
               dataset_ops.get_legacy_output_shapes(dataset),
               dataset_ops.get_legacy_output_types(dataset)))
-    return gen_experimental_dataset_ops.experimental_dataset_to_tf_record(
-        dataset._variant_tensor, self._filename, self._compression_type)  # pylint: disable=protected-access
+    if compat.forward_compatible(2019, 8, 3):
+      return gen_experimental_dataset_ops.dataset_to_tf_record(
+          dataset._variant_tensor, self._filename, self._compression_type)  # pylint: disable=protected-access
+    else:
+      return gen_experimental_dataset_ops.experimental_dataset_to_tf_record(
+          dataset._variant_tensor, self._filename, self._compression_type)  # pylint: disable=protected-access
diff --git a/tensorflow/python/data/ops/dataset_ops.py b/tensorflow/python/data/ops/dataset_ops.py
index 25f208a1433..cb164d7fbee 100644
--- a/tensorflow/python/data/ops/dataset_ops.py
+++ b/tensorflow/python/data/ops/dataset_ops.py
@@ -3630,12 +3630,20 @@ class _SetStatsAggregatorDataset(UnaryUnchangedStructureDataset):
     self._stats_aggregator = aggregator
     self._prefix = prefix
     self._counter_prefix = counter_prefix
-    variant_tensor = ged_ops.experimental_set_stats_aggregator_dataset(
-        input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._stats_aggregator._resource,  # pylint: disable=protected-access
-        self._prefix,
-        self._counter_prefix,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.set_stats_aggregator_dataset(
+          input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._stats_aggregator._resource,  # pylint: disable=protected-access
+          self._prefix,
+          self._counter_prefix,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_set_stats_aggregator_dataset(
+          input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._stats_aggregator._resource,  # pylint: disable=protected-access
+          self._prefix,
+          self._counter_prefix,
+          **self._flat_structure)
     super(_SetStatsAggregatorDataset, self).__init__(input_dataset,
                                                      variant_tensor)
 
@@ -3649,10 +3657,16 @@ class _MaxIntraOpParallelismDataset(UnaryUnchangedStructureDataset):
         max_intra_op_parallelism,
         dtype=dtypes.int64,
         name="max_intra_op_parallelism")
-    variant_tensor = ged_ops.experimental_max_intra_op_parallelism_dataset(
-        input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._max_intra_op_parallelism,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.max_intra_op_parallelism_dataset(
+          input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._max_intra_op_parallelism,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_max_intra_op_parallelism_dataset(
+          input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._max_intra_op_parallelism,
+          **self._flat_structure)
     super(_MaxIntraOpParallelismDataset, self).__init__(input_dataset,
                                                         variant_tensor)
 
@@ -3664,10 +3678,16 @@ class _PrivateThreadPoolDataset(UnaryUnchangedStructureDataset):
     self._input_dataset = input_dataset
     self._num_threads = ops.convert_to_tensor(
         num_threads, dtype=dtypes.int64, name="num_threads")
-    variant_tensor = ged_ops.experimental_private_thread_pool_dataset(
-        input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._num_threads,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.private_thread_pool_dataset(
+          input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._num_threads,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_private_thread_pool_dataset(
+          input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._num_threads,
+          **self._flat_structure)
     super(_PrivateThreadPoolDataset, self).__init__(input_dataset,
                                                     variant_tensor)
 
@@ -3706,9 +3726,14 @@ class _UnbatchDataset(UnaryDataset):
     self._structure = nest.map_structure(
         lambda component_spec: component_spec._unbatch(),  # pylint: disable=protected-access
         get_structure(input_dataset))
-    variant_tensor = ged_ops.experimental_unbatch_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.unbatch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_unbatch_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          **self._flat_structure)
     super(_UnbatchDataset, self).__init__(input_dataset, variant_tensor)
 
   @property
diff --git a/tensorflow/python/data/ops/readers.py b/tensorflow/python/data/ops/readers.py
index b4298aad461..8108be024bc 100644
--- a/tensorflow/python/data/ops/readers.py
+++ b/tensorflow/python/data/ops/readers.py
@@ -240,16 +240,28 @@ class ParallelInterleaveDataset(dataset_ops.UnaryDataset):
         "prefetch_input_elements",
         prefetch_input_elements,
         argument_default=2 * cycle_length)
-    variant_tensor = ged_ops.experimental_parallel_interleave_dataset(
-        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
-        self._map_func.function.captured_inputs,
-        self._cycle_length,
-        self._block_length,
-        self._sloppy,
-        self._buffer_output_elements,
-        self._prefetch_input_elements,
-        f=self._map_func.function,
-        **self._flat_structure)
+    if compat.forward_compatible(2019, 8, 3):
+      variant_tensor = ged_ops.parallel_interleave_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._map_func.function.captured_inputs,
+          self._cycle_length,
+          self._block_length,
+          self._sloppy,
+          self._buffer_output_elements,
+          self._prefetch_input_elements,
+          f=self._map_func.function,
+          **self._flat_structure)
+    else:
+      variant_tensor = ged_ops.experimental_parallel_interleave_dataset(
+          self._input_dataset._variant_tensor,  # pylint: disable=protected-access
+          self._map_func.function.captured_inputs,
+          self._cycle_length,
+          self._block_length,
+          self._sloppy,
+          self._buffer_output_elements,
+          self._prefetch_input_elements,
+          f=self._map_func.function,
+          **self._flat_structure)
     super(ParallelInterleaveDataset, self).__init__(input_dataset,
                                                     variant_tensor)
 
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt
index 55e79243edd..024455f429c 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt
@@ -188,6 +188,10 @@ tf_module {
     name: "Assert"
     argspec: "args=[\'condition\', \'data\', \'summarize\', \'name\'], varargs=None, keywords=None, defaults=[\'3\', \'None\'], "
   }
+  member_method {
+    name: "AssertNextDataset"
+    argspec: "args=[\'input_dataset\', \'transformations\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Assign"
     argspec: "args=[\'ref\', \'value\', \'validate_shape\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'True\', \'None\'], "
@@ -236,6 +240,10 @@ tf_module {
     name: "AudioSummaryV2"
     argspec: "args=[\'tag\', \'tensor\', \'sample_rate\', \'max_outputs\', \'name\'], varargs=None, keywords=None, defaults=[\'3\', \'None\'], "
   }
+  member_method {
+    name: "AutoShardDataset"
+    argspec: "args=[\'input_dataset\', \'num_workers\', \'index\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "AvgPool"
     argspec: "args=[\'value\', \'ksize\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'NHWC\', \'None\'], "
@@ -560,6 +568,14 @@ tf_module {
     name: "Bucketize"
     argspec: "args=[\'input\', \'boundaries\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "BytesProducedStatsDataset"
+    argspec: "args=[\'input_dataset\', \'tag\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "CSVDataset"
+    argspec: "args=[\'filenames\', \'compression_type\', \'buffer_size\', \'header\', \'field_delim\', \'use_quote_delim\', \'na_value\', \'select_cols\', \'record_defaults\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "CTCBeamSearchDecoder"
     argspec: "args=[\'inputs\', \'sequence_length\', \'beam_width\', \'top_paths\', \'merge_repeated\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
@@ -604,6 +620,10 @@ tf_module {
     name: "ChooseFastestBranchDataset"
     argspec: "args=[\'input_dataset\', \'ratio_numerator\', \'ratio_denominator\', \'other_arguments\', \'num_elements_per_branch\', \'branches\', \'other_arguments_lengths\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ChooseFastestDataset"
+    argspec: "args=[\'input_datasets\', \'num_experiments\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "ClipByValue"
     argspec: "args=[\'t\', \'clip_value_min\', \'clip_value_max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -828,6 +848,10 @@ tf_module {
     name: "DataFormatVecPermute"
     argspec: "args=[\'x\', \'src_format\', \'dst_format\', \'name\'], varargs=None, keywords=None, defaults=[\'NHWC\', \'NCHW\', \'None\'], "
   }
+  member_method {
+    name: "DatasetCardinality"
+    argspec: "args=[\'input_dataset\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "DatasetToGraph"
     argspec: "args=[\'input_dataset\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -836,6 +860,10 @@ tf_module {
     name: "DatasetToSingleElement"
     argspec: "args=[\'dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "DatasetToTFRecord"
+    argspec: "args=[\'input_dataset\', \'filename\', \'compression_type\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "DebugGradientIdentity"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -912,6 +940,10 @@ tf_module {
     name: "DenseToDenseSetOperation"
     argspec: "args=[\'set1\', \'set2\', \'set_operation\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
   }
+  member_method {
+    name: "DenseToSparseBatchDataset"
+    argspec: "args=[\'input_dataset\', \'batch_size\', \'row_shape\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "DenseToSparseSetOperation"
     argspec: "args=[\'set1\', \'set2_indices\', \'set2_values\', \'set2_shape\', \'set_operation\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
@@ -980,6 +1012,10 @@ tf_module {
     name: "Dilation2DBackpropInput"
     argspec: "args=[\'input\', \'filter\', \'out_backprop\', \'strides\', \'rates\', \'padding\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "DirectedInterleaveDataset"
+    argspec: "args=[\'selector_input_dataset\', \'data_input_datasets\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Div"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1148,22 +1184,10 @@ tf_module {
     name: "ExperimentalGroupByWindowDataset"
     argspec: "args=[\'input_dataset\', \'key_func_other_arguments\', \'reduce_func_other_arguments\', \'window_size_func_other_arguments\', \'key_func\', \'reduce_func\', \'window_size_func\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalIdentityIndexedDataset"
-    argspec: "args=[\'size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
   member_method {
     name: "ExperimentalIgnoreErrorsDataset"
     argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalIndexedDatasetGet"
-    argspec: "args=[\'materialized\', \'index\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
-  member_method {
-    name: "ExperimentalIndexedDatasetMaterialize"
-    argspec: "args=[\'dataset\', \'materialized\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
   member_method {
     name: "ExperimentalIteratorGetDevice"
     argspec: "args=[\'resource\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1188,10 +1212,6 @@ tf_module {
     name: "ExperimentalMatchingFilesDataset"
     argspec: "args=[\'patterns\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalMaterializedIndexDatasetHandle"
-    argspec: "args=[\'container\', \'shared_name\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
   member_method {
     name: "ExperimentalMaxIntraOpParallelismDataset"
     argspec: "args=[\'input_dataset\', \'max_intra_op_parallelism\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1200,10 +1220,6 @@ tf_module {
     name: "ExperimentalNonSerializableDataset"
     argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalNumaMapAndBatchDataset"
-    argspec: "args=[\'input_dataset\', \'other_arguments\', \'batch_size\', \'num_parallel_calls\', \'drop_remainder\', \'f\', \'output_types\', \'output_shapes\', \'preserve_cardinality\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
-  }
   member_method {
     name: "ExperimentalParallelInterleaveDataset"
     argspec: "args=[\'input_dataset\', \'other_arguments\', \'cycle_length\', \'block_length\', \'sloppy\', \'buffer_output_elements\', \'prefetch_input_elements\', \'f\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1504,6 +1520,14 @@ tf_module {
     name: "GreaterEqual"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "GroupByReducerDataset"
+    argspec: "args=[\'input_dataset\', \'key_func_other_arguments\', \'init_func_other_arguments\', \'reduce_func_other_arguments\', \'finalize_func_other_arguments\', \'key_func\', \'init_func\', \'reduce_func\', \'finalize_func\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "GroupByWindowDataset"
+    argspec: "args=[\'input_dataset\', \'key_func_other_arguments\', \'reduce_func_other_arguments\', \'window_size_func_other_arguments\', \'key_func\', \'reduce_func\', \'window_size_func\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "GuaranteeConst"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1584,6 +1608,10 @@ tf_module {
     name: "Igammac"
     argspec: "args=[\'a\', \'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "IgnoreErrorsDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Imag"
     argspec: "args=[\'input\', \'Tout\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\", \'None\'], "
@@ -1712,6 +1740,10 @@ tf_module {
     name: "IteratorFromStringHandleV2"
     argspec: "args=[\'string_handle\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'[]\', \'[]\', \'None\'], "
   }
+  member_method {
+    name: "IteratorGetDevice"
+    argspec: "args=[\'resource\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "IteratorGetNext"
     argspec: "args=[\'iterator\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1736,6 +1768,10 @@ tf_module {
     name: "L2Loss"
     argspec: "args=[\'t\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "LMDBDataset"
+    argspec: "args=[\'filenames\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "LMDBReader"
     argspec: "args=[\'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
@@ -1756,6 +1792,10 @@ tf_module {
     name: "LSTMBlockCellGrad"
     argspec: "args=[\'x\', \'cs_prev\', \'h_prev\', \'w\', \'wci\', \'wcf\', \'wco\', \'b\', \'i\', \'cs\', \'f\', \'o\', \'ci\', \'co\', \'cs_grad\', \'h_grad\', \'use_peephole\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "LatencyStatsDataset"
+    argspec: "args=[\'input_dataset\', \'tag\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "LeakyRelu"
     argspec: "args=[\'features\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'0.2\', \'None\'], "
@@ -1956,6 +1996,10 @@ tf_module {
     name: "MakeIterator"
     argspec: "args=[\'dataset\', \'iterator\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "MapAndBatchDataset"
+    argspec: "args=[\'input_dataset\', \'other_arguments\', \'batch_size\', \'num_parallel_calls\', \'drop_remainder\', \'f\', \'output_types\', \'output_shapes\', \'preserve_cardinality\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
   member_method {
     name: "MapClear"
     argspec: "args=[\'dtypes\', \'capacity\', \'memory_limit\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'\', \'\', \'None\'], "
@@ -2000,6 +2044,10 @@ tf_module {
     name: "MatchingFiles"
     argspec: "args=[\'pattern\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "MatchingFilesDataset"
+    argspec: "args=[\'patterns\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "MatrixBandPart"
     argspec: "args=[\'input\', \'num_lower\', \'num_upper\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -2064,6 +2112,10 @@ tf_module {
     name: "Max"
     argspec: "args=[\'input\', \'axis\', \'keep_dims\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
   }
+  member_method {
+    name: "MaxIntraOpParallelismDataset"
+    argspec: "args=[\'input_dataset\', \'max_intra_op_parallelism\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "MaxPool"
     argspec: "args=[\'input\', \'ksize\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'NHWC\', \'None\'], "
@@ -2280,6 +2332,10 @@ tf_module {
     name: "NonMaxSuppressionWithOverlaps"
     argspec: "args=[\'overlaps\', \'scores\', \'max_output_size\', \'overlap_threshold\', \'score_threshold\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "NonSerializableDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "NotEqual"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -2400,6 +2456,10 @@ tf_module {
     name: "ParallelDynamicStitch"
     argspec: "args=[\'indices\', \'data\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ParallelInterleaveDataset"
+    argspec: "args=[\'input_dataset\', \'other_arguments\', \'cycle_length\', \'block_length\', \'sloppy\', \'buffer_output_elements\', \'prefetch_input_elements\', \'f\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "ParallelInterleaveDatasetV2"
     argspec: "args=[\'input_dataset\', \'other_arguments\', \'cycle_length\', \'block_length\', \'num_parallel_calls\', \'f\', \'output_types\', \'output_shapes\', \'sloppy\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -2416,6 +2476,10 @@ tf_module {
     name: "ParseExample"
     argspec: "args=[\'serialized\', \'names\', \'sparse_keys\', \'dense_keys\', \'dense_defaults\', \'sparse_types\', \'dense_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ParseExampleDataset"
+    argspec: "args=[\'input_dataset\', \'num_parallel_calls\', \'dense_defaults\', \'sparse_keys\', \'dense_keys\', \'sparse_types\', \'dense_shapes\', \'output_types\', \'output_shapes\', \'sloppy\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
   member_method {
     name: "ParseSequenceExample"
     argspec: "args=[\'serialized\', \'debug_name\', \'context_dense_defaults\', \'feature_list_dense_missing_assumed_empty\', \'context_sparse_keys\', \'context_dense_keys\', \'feature_list_sparse_keys\', \'feature_list_dense_keys\', \'Ncontext_sparse\', \'Ncontext_dense\', \'Nfeature_list_sparse\', \'Nfeature_list_dense\', \'context_sparse_types\', \'feature_list_dense_types\', \'context_dense_shapes\', \'feature_list_sparse_types\', \'feature_list_dense_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'0\', \'0\', \'[]\', \'[]\', \'[]\', \'[]\', \'[]\', \'None\'], "
@@ -2492,6 +2556,10 @@ tf_module {
     name: "PriorityQueueV2"
     argspec: "args=[\'shapes\', \'component_types\', \'capacity\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'[]\', \'-1\', \'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "PrivateThreadPoolDataset"
+    argspec: "args=[\'input_dataset\', \'num_threads\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Prod"
     argspec: "args=[\'input\', \'axis\', \'keep_dims\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -2764,6 +2832,10 @@ tf_module {
     name: "RandomCrop"
     argspec: "args=[\'image\', \'size\', \'seed\', \'seed2\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'None\'], "
   }
+  member_method {
+    name: "RandomDataset"
+    argspec: "args=[\'seed\', \'seed2\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "RandomGamma"
     argspec: "args=[\'shape\', \'alpha\', \'seed\', \'seed2\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'None\'], "
@@ -2888,6 +2960,10 @@ tf_module {
     name: "RealDiv"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "RebatchDataset"
+    argspec: "args=[\'input_dataset\', \'num_workers\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Reciprocal"
     argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -3364,6 +3440,10 @@ tf_module {
     name: "ScaleAndTranslateGrad"
     argspec: "args=[\'grads\', \'original_image\', \'scale\', \'translation\', \'kernel_type\', \'antialias\', \'name\'], varargs=None, keywords=None, defaults=[\'lanczos3\', \'True\', \'None\'], "
   }
+  member_method {
+    name: "ScanDataset"
+    argspec: "args=[\'input_dataset\', \'initial_state\', \'other_arguments\', \'f\', \'output_types\', \'output_shapes\', \'preserve_cardinality\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
   member_method {
     name: "ScatterAdd"
     argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -3496,6 +3576,10 @@ tf_module {
     name: "SetSize"
     argspec: "args=[\'set_indices\', \'set_values\', \'set_shape\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
   }
+  member_method {
+    name: "SetStatsAggregatorDataset"
+    argspec: "args=[\'input_dataset\', \'stats_aggregator\', \'tag\', \'counter_prefix\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Shape"
     argspec: "args=[\'input\', \'out_type\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
@@ -3556,10 +3640,18 @@ tf_module {
     name: "SkipDataset"
     argspec: "args=[\'input_dataset\', \'count\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "SleepDataset"
+    argspec: "args=[\'input_dataset\', \'sleep_microseconds\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Slice"
     argspec: "args=[\'input\', \'begin\', \'size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "SlidingWindowDataset"
+    argspec: "args=[\'input_dataset\', \'window_size\', \'window_shift\', \'window_stride\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Snapshot"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -3808,6 +3900,10 @@ tf_module {
     name: "SplitV"
     argspec: "args=[\'value\', \'size_splits\', \'axis\', \'num_split\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "SqlDataset"
+    argspec: "args=[\'driver_name\', \'data_source_name\', \'query\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Sqrt"
     argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -3944,6 +4040,10 @@ tf_module {
     name: "StaticRegexReplace"
     argspec: "args=[\'input\', \'pattern\', \'rewrite\', \'replace_global\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
   }
+  member_method {
+    name: "StatsAggregatorHandle"
+    argspec: "args=[\'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
+  }
   member_method {
     name: "StatsAggregatorHandleV2"
     argspec: "args=[\'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
@@ -3952,6 +4052,10 @@ tf_module {
     name: "StatsAggregatorSetSummaryWriter"
     argspec: "args=[\'stats_aggregator\', \'summary\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "StatsAggregatorSummary"
+    argspec: "args=[\'iterator\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "StopGradient"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -4092,6 +4196,10 @@ tf_module {
     name: "TakeManySparseFromTensorsMap"
     argspec: "args=[\'sparse_handles\', \'dtype\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "TakeWhileDataset"
+    argspec: "args=[\'input_dataset\', \'other_arguments\', \'predicate\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Tan"
     argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -4360,6 +4468,14 @@ tf_module {
     name: "TextLineReaderV2"
     argspec: "args=[\'skip_header_lines\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "ThreadPoolDataset"
+    argspec: "args=[\'input_dataset\', \'thread_pool\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ThreadPoolHandle"
+    argspec: "args=[\'num_threads\', \'display_name\', \'max_intra_op_parallelism\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'\', \'\', \'None\'], "
+  }
   member_method {
     name: "ThreadUnsafeUnigramCandidateSampler"
     argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'seed\', \'seed2\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'None\'], "
@@ -4412,6 +4528,10 @@ tf_module {
     name: "Unbatch"
     argspec: "args=[\'batched_tensor\', \'batch_index\', \'id\', \'timeout_micros\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "UnbatchDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "UnbatchGrad"
     argspec: "args=[\'original_input\', \'batch_index\', \'grad\', \'id\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
@@ -4444,6 +4564,10 @@ tf_module {
     name: "Unique"
     argspec: "args=[\'x\', \'out_idx\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
   }
+  member_method {
+    name: "UniqueDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "UniqueV2"
     argspec: "args=[\'x\', \'axis\', \'out_idx\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt
index 55e79243edd..024455f429c 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt
@@ -188,6 +188,10 @@ tf_module {
     name: "Assert"
     argspec: "args=[\'condition\', \'data\', \'summarize\', \'name\'], varargs=None, keywords=None, defaults=[\'3\', \'None\'], "
   }
+  member_method {
+    name: "AssertNextDataset"
+    argspec: "args=[\'input_dataset\', \'transformations\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Assign"
     argspec: "args=[\'ref\', \'value\', \'validate_shape\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'True\', \'None\'], "
@@ -236,6 +240,10 @@ tf_module {
     name: "AudioSummaryV2"
     argspec: "args=[\'tag\', \'tensor\', \'sample_rate\', \'max_outputs\', \'name\'], varargs=None, keywords=None, defaults=[\'3\', \'None\'], "
   }
+  member_method {
+    name: "AutoShardDataset"
+    argspec: "args=[\'input_dataset\', \'num_workers\', \'index\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "AvgPool"
     argspec: "args=[\'value\', \'ksize\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'NHWC\', \'None\'], "
@@ -560,6 +568,14 @@ tf_module {
     name: "Bucketize"
     argspec: "args=[\'input\', \'boundaries\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "BytesProducedStatsDataset"
+    argspec: "args=[\'input_dataset\', \'tag\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "CSVDataset"
+    argspec: "args=[\'filenames\', \'compression_type\', \'buffer_size\', \'header\', \'field_delim\', \'use_quote_delim\', \'na_value\', \'select_cols\', \'record_defaults\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "CTCBeamSearchDecoder"
     argspec: "args=[\'inputs\', \'sequence_length\', \'beam_width\', \'top_paths\', \'merge_repeated\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
@@ -604,6 +620,10 @@ tf_module {
     name: "ChooseFastestBranchDataset"
     argspec: "args=[\'input_dataset\', \'ratio_numerator\', \'ratio_denominator\', \'other_arguments\', \'num_elements_per_branch\', \'branches\', \'other_arguments_lengths\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ChooseFastestDataset"
+    argspec: "args=[\'input_datasets\', \'num_experiments\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "ClipByValue"
     argspec: "args=[\'t\', \'clip_value_min\', \'clip_value_max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -828,6 +848,10 @@ tf_module {
     name: "DataFormatVecPermute"
     argspec: "args=[\'x\', \'src_format\', \'dst_format\', \'name\'], varargs=None, keywords=None, defaults=[\'NHWC\', \'NCHW\', \'None\'], "
   }
+  member_method {
+    name: "DatasetCardinality"
+    argspec: "args=[\'input_dataset\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "DatasetToGraph"
     argspec: "args=[\'input_dataset\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -836,6 +860,10 @@ tf_module {
     name: "DatasetToSingleElement"
     argspec: "args=[\'dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "DatasetToTFRecord"
+    argspec: "args=[\'input_dataset\', \'filename\', \'compression_type\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "DebugGradientIdentity"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -912,6 +940,10 @@ tf_module {
     name: "DenseToDenseSetOperation"
     argspec: "args=[\'set1\', \'set2\', \'set_operation\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
   }
+  member_method {
+    name: "DenseToSparseBatchDataset"
+    argspec: "args=[\'input_dataset\', \'batch_size\', \'row_shape\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "DenseToSparseSetOperation"
     argspec: "args=[\'set1\', \'set2_indices\', \'set2_values\', \'set2_shape\', \'set_operation\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
@@ -980,6 +1012,10 @@ tf_module {
     name: "Dilation2DBackpropInput"
     argspec: "args=[\'input\', \'filter\', \'out_backprop\', \'strides\', \'rates\', \'padding\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "DirectedInterleaveDataset"
+    argspec: "args=[\'selector_input_dataset\', \'data_input_datasets\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Div"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1148,22 +1184,10 @@ tf_module {
     name: "ExperimentalGroupByWindowDataset"
     argspec: "args=[\'input_dataset\', \'key_func_other_arguments\', \'reduce_func_other_arguments\', \'window_size_func_other_arguments\', \'key_func\', \'reduce_func\', \'window_size_func\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalIdentityIndexedDataset"
-    argspec: "args=[\'size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
   member_method {
     name: "ExperimentalIgnoreErrorsDataset"
     argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalIndexedDatasetGet"
-    argspec: "args=[\'materialized\', \'index\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
-  member_method {
-    name: "ExperimentalIndexedDatasetMaterialize"
-    argspec: "args=[\'dataset\', \'materialized\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
   member_method {
     name: "ExperimentalIteratorGetDevice"
     argspec: "args=[\'resource\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1188,10 +1212,6 @@ tf_module {
     name: "ExperimentalMatchingFilesDataset"
     argspec: "args=[\'patterns\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalMaterializedIndexDatasetHandle"
-    argspec: "args=[\'container\', \'shared_name\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
-  }
   member_method {
     name: "ExperimentalMaxIntraOpParallelismDataset"
     argspec: "args=[\'input_dataset\', \'max_intra_op_parallelism\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1200,10 +1220,6 @@ tf_module {
     name: "ExperimentalNonSerializableDataset"
     argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
-  member_method {
-    name: "ExperimentalNumaMapAndBatchDataset"
-    argspec: "args=[\'input_dataset\', \'other_arguments\', \'batch_size\', \'num_parallel_calls\', \'drop_remainder\', \'f\', \'output_types\', \'output_shapes\', \'preserve_cardinality\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
-  }
   member_method {
     name: "ExperimentalParallelInterleaveDataset"
     argspec: "args=[\'input_dataset\', \'other_arguments\', \'cycle_length\', \'block_length\', \'sloppy\', \'buffer_output_elements\', \'prefetch_input_elements\', \'f\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1504,6 +1520,14 @@ tf_module {
     name: "GreaterEqual"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "GroupByReducerDataset"
+    argspec: "args=[\'input_dataset\', \'key_func_other_arguments\', \'init_func_other_arguments\', \'reduce_func_other_arguments\', \'finalize_func_other_arguments\', \'key_func\', \'init_func\', \'reduce_func\', \'finalize_func\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "GroupByWindowDataset"
+    argspec: "args=[\'input_dataset\', \'key_func_other_arguments\', \'reduce_func_other_arguments\', \'window_size_func_other_arguments\', \'key_func\', \'reduce_func\', \'window_size_func\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "GuaranteeConst"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1584,6 +1608,10 @@ tf_module {
     name: "Igammac"
     argspec: "args=[\'a\', \'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "IgnoreErrorsDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Imag"
     argspec: "args=[\'input\', \'Tout\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\", \'None\'], "
@@ -1712,6 +1740,10 @@ tf_module {
     name: "IteratorFromStringHandleV2"
     argspec: "args=[\'string_handle\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'[]\', \'[]\', \'None\'], "
   }
+  member_method {
+    name: "IteratorGetDevice"
+    argspec: "args=[\'resource\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "IteratorGetNext"
     argspec: "args=[\'iterator\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -1736,6 +1768,10 @@ tf_module {
     name: "L2Loss"
     argspec: "args=[\'t\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "LMDBDataset"
+    argspec: "args=[\'filenames\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "LMDBReader"
     argspec: "args=[\'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
@@ -1756,6 +1792,10 @@ tf_module {
     name: "LSTMBlockCellGrad"
     argspec: "args=[\'x\', \'cs_prev\', \'h_prev\', \'w\', \'wci\', \'wcf\', \'wco\', \'b\', \'i\', \'cs\', \'f\', \'o\', \'ci\', \'co\', \'cs_grad\', \'h_grad\', \'use_peephole\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "LatencyStatsDataset"
+    argspec: "args=[\'input_dataset\', \'tag\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "LeakyRelu"
     argspec: "args=[\'features\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'0.2\', \'None\'], "
@@ -1956,6 +1996,10 @@ tf_module {
     name: "MakeIterator"
     argspec: "args=[\'dataset\', \'iterator\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "MapAndBatchDataset"
+    argspec: "args=[\'input_dataset\', \'other_arguments\', \'batch_size\', \'num_parallel_calls\', \'drop_remainder\', \'f\', \'output_types\', \'output_shapes\', \'preserve_cardinality\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
   member_method {
     name: "MapClear"
     argspec: "args=[\'dtypes\', \'capacity\', \'memory_limit\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'\', \'\', \'None\'], "
@@ -2000,6 +2044,10 @@ tf_module {
     name: "MatchingFiles"
     argspec: "args=[\'pattern\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "MatchingFilesDataset"
+    argspec: "args=[\'patterns\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "MatrixBandPart"
     argspec: "args=[\'input\', \'num_lower\', \'num_upper\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -2064,6 +2112,10 @@ tf_module {
     name: "Max"
     argspec: "args=[\'input\', \'axis\', \'keep_dims\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
   }
+  member_method {
+    name: "MaxIntraOpParallelismDataset"
+    argspec: "args=[\'input_dataset\', \'max_intra_op_parallelism\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "MaxPool"
     argspec: "args=[\'input\', \'ksize\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'NHWC\', \'None\'], "
@@ -2280,6 +2332,10 @@ tf_module {
     name: "NonMaxSuppressionWithOverlaps"
     argspec: "args=[\'overlaps\', \'scores\', \'max_output_size\', \'overlap_threshold\', \'score_threshold\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "NonSerializableDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "NotEqual"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -2400,6 +2456,10 @@ tf_module {
     name: "ParallelDynamicStitch"
     argspec: "args=[\'indices\', \'data\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ParallelInterleaveDataset"
+    argspec: "args=[\'input_dataset\', \'other_arguments\', \'cycle_length\', \'block_length\', \'sloppy\', \'buffer_output_elements\', \'prefetch_input_elements\', \'f\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "ParallelInterleaveDatasetV2"
     argspec: "args=[\'input_dataset\', \'other_arguments\', \'cycle_length\', \'block_length\', \'num_parallel_calls\', \'f\', \'output_types\', \'output_shapes\', \'sloppy\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -2416,6 +2476,10 @@ tf_module {
     name: "ParseExample"
     argspec: "args=[\'serialized\', \'names\', \'sparse_keys\', \'dense_keys\', \'dense_defaults\', \'sparse_types\', \'dense_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "ParseExampleDataset"
+    argspec: "args=[\'input_dataset\', \'num_parallel_calls\', \'dense_defaults\', \'sparse_keys\', \'dense_keys\', \'sparse_types\', \'dense_shapes\', \'output_types\', \'output_shapes\', \'sloppy\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
   member_method {
     name: "ParseSequenceExample"
     argspec: "args=[\'serialized\', \'debug_name\', \'context_dense_defaults\', \'feature_list_dense_missing_assumed_empty\', \'context_sparse_keys\', \'context_dense_keys\', \'feature_list_sparse_keys\', \'feature_list_dense_keys\', \'Ncontext_sparse\', \'Ncontext_dense\', \'Nfeature_list_sparse\', \'Nfeature_list_dense\', \'context_sparse_types\', \'feature_list_dense_types\', \'context_dense_shapes\', \'feature_list_sparse_types\', \'feature_list_dense_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'0\', \'0\', \'[]\', \'[]\', \'[]\', \'[]\', \'[]\', \'None\'], "
@@ -2492,6 +2556,10 @@ tf_module {
     name: "PriorityQueueV2"
     argspec: "args=[\'shapes\', \'component_types\', \'capacity\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'[]\', \'-1\', \'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "PrivateThreadPoolDataset"
+    argspec: "args=[\'input_dataset\', \'num_threads\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Prod"
     argspec: "args=[\'input\', \'axis\', \'keep_dims\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -2764,6 +2832,10 @@ tf_module {
     name: "RandomCrop"
     argspec: "args=[\'image\', \'size\', \'seed\', \'seed2\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'None\'], "
   }
+  member_method {
+    name: "RandomDataset"
+    argspec: "args=[\'seed\', \'seed2\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "RandomGamma"
     argspec: "args=[\'shape\', \'alpha\', \'seed\', \'seed2\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'None\'], "
@@ -2888,6 +2960,10 @@ tf_module {
     name: "RealDiv"
     argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "RebatchDataset"
+    argspec: "args=[\'input_dataset\', \'num_workers\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Reciprocal"
     argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -3364,6 +3440,10 @@ tf_module {
     name: "ScaleAndTranslateGrad"
     argspec: "args=[\'grads\', \'original_image\', \'scale\', \'translation\', \'kernel_type\', \'antialias\', \'name\'], varargs=None, keywords=None, defaults=[\'lanczos3\', \'True\', \'None\'], "
   }
+  member_method {
+    name: "ScanDataset"
+    argspec: "args=[\'input_dataset\', \'initial_state\', \'other_arguments\', \'f\', \'output_types\', \'output_shapes\', \'preserve_cardinality\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
   member_method {
     name: "ScatterAdd"
     argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -3496,6 +3576,10 @@ tf_module {
     name: "SetSize"
     argspec: "args=[\'set_indices\', \'set_values\', \'set_shape\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
   }
+  member_method {
+    name: "SetStatsAggregatorDataset"
+    argspec: "args=[\'input_dataset\', \'stats_aggregator\', \'tag\', \'counter_prefix\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Shape"
     argspec: "args=[\'input\', \'out_type\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
@@ -3556,10 +3640,18 @@ tf_module {
     name: "SkipDataset"
     argspec: "args=[\'input_dataset\', \'count\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "SleepDataset"
+    argspec: "args=[\'input_dataset\', \'sleep_microseconds\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Slice"
     argspec: "args=[\'input\', \'begin\', \'size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "SlidingWindowDataset"
+    argspec: "args=[\'input_dataset\', \'window_size\', \'window_shift\', \'window_stride\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Snapshot"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -3808,6 +3900,10 @@ tf_module {
     name: "SplitV"
     argspec: "args=[\'value\', \'size_splits\', \'axis\', \'num_split\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "SqlDataset"
+    argspec: "args=[\'driver_name\', \'data_source_name\', \'query\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Sqrt"
     argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -3944,6 +4040,10 @@ tf_module {
     name: "StaticRegexReplace"
     argspec: "args=[\'input\', \'pattern\', \'rewrite\', \'replace_global\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
   }
+  member_method {
+    name: "StatsAggregatorHandle"
+    argspec: "args=[\'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
+  }
   member_method {
     name: "StatsAggregatorHandleV2"
     argspec: "args=[\'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
@@ -3952,6 +4052,10 @@ tf_module {
     name: "StatsAggregatorSetSummaryWriter"
     argspec: "args=[\'stats_aggregator\', \'summary\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
+  member_method {
+    name: "StatsAggregatorSummary"
+    argspec: "args=[\'iterator\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "StopGradient"
     argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -4092,6 +4196,10 @@ tf_module {
     name: "TakeManySparseFromTensorsMap"
     argspec: "args=[\'sparse_handles\', \'dtype\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "TakeWhileDataset"
+    argspec: "args=[\'input_dataset\', \'other_arguments\', \'predicate\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "Tan"
     argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
@@ -4360,6 +4468,14 @@ tf_module {
     name: "TextLineReaderV2"
     argspec: "args=[\'skip_header_lines\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "ThreadPoolDataset"
+    argspec: "args=[\'input_dataset\', \'thread_pool\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ThreadPoolHandle"
+    argspec: "args=[\'num_threads\', \'display_name\', \'max_intra_op_parallelism\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'\', \'\', \'None\'], "
+  }
   member_method {
     name: "ThreadUnsafeUnigramCandidateSampler"
     argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'seed\', \'seed2\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'0\', \'None\'], "
@@ -4412,6 +4528,10 @@ tf_module {
     name: "Unbatch"
     argspec: "args=[\'batched_tensor\', \'batch_index\', \'id\', \'timeout_micros\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
   }
+  member_method {
+    name: "UnbatchDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "UnbatchGrad"
     argspec: "args=[\'original_input\', \'batch_index\', \'grad\', \'id\', \'container\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'\', \'\', \'None\'], "
@@ -4444,6 +4564,10 @@ tf_module {
     name: "Unique"
     argspec: "args=[\'x\', \'out_idx\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
   }
+  member_method {
+    name: "UniqueDataset"
+    argspec: "args=[\'input_dataset\', \'output_types\', \'output_shapes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
   member_method {
     name: "UniqueV2"
     argspec: "args=[\'x\', \'axis\', \'out_idx\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "