From de9c460b06b437a44ebb3d795d9ff3cc20a8c4f1 Mon Sep 17 00:00:00 2001
From: Jiri Simsa <jsimsa@google.com>
Date: Wed, 3 Jul 2019 14:12:29 -0700
Subject: [PATCH] [tf.data] Cleanup of tf.data op definitions.

cl/223710135 renamed some datasets ops (adding "Experimental" prefix), which introduced a backwards compatibility issue. In particular, if a graph was saved using TensorFlow before cl/223710135, restoring the graph using TensorFlow built after cl/223710135 would fail if the graph contained any of the renamed ops. To address this issue, this CL reintroduces op definitions removed by cl/223710135 and uses `compat.forward_compatible` to transition away from ops that use the (misleading) "Experimental" prefix to the corresponding ones without the prefix.

In addition, this CL removes tf.data op definitions for ops that have no kernels.

PiperOrigin-RevId: 256436076
---
 tensorflow/contrib/data/python/ops/readers.py |   9 +-
 tensorflow/contrib/data/python/ops/sliding.py |  21 +-
 .../base_api/api_def_AssertNextDataset.pbtxt  |   4 +
 .../base_api/api_def_AutoShardDataset.pbtxt   |  32 +
 .../api_def_BytesProducedStatsDataset.pbtxt   |   5 +
 .../api_def/base_api/api_def_CSVDataset.pbtxt |   4 +
 .../api_def_ChooseFastestDataset.pbtxt        |   4 +
 .../base_api/api_def_DatasetCardinality.pbtxt |  21 +
 .../base_api/api_def_DatasetToTFRecord.pbtxt  |  24 +
 .../api_def_DenseToSparseBatchDataset.pbtxt   |  26 +
 .../api_def_DirectedInterleaveDataset.pbtxt   |  21 +
 ...f_ExperimentalIdentityIndexedDataset.pbtxt |   4 -
 ...pi_def_ExperimentalIndexedDatasetGet.pbtxt |   4 -
 ...xperimentalIndexedDatasetMaterialize.pbtxt |   4 -
 ...mentalMaterializedIndexDatasetHandle.pbtxt |   4 -
 .../api_def_GroupByReducerDataset.pbtxt       |  69 ++
 .../api_def_GroupByWindowDataset.pbtxt        |  15 +
 .../api_def_IgnoreErrorsDataset.pbtxt         |   8 +
 .../base_api/api_def_IteratorGetDevice.pbtxt  |   8 +
 .../base_api/api_def_LMDBDataset.pbtxt        |   4 +
 .../api_def_LatencyStatsDataset.pbtxt         |   5 +
 ...pbtxt => api_def_MapAndBatchDataset.pbtxt} |   6 +-
 .../api_def_MatchingFilesDataset.pbtxt        |   4 +
 ...api_def_MaxIntraOpParallelismDataset.pbtxt |  13 +
 .../api_def_NonSerializableDataset.pbtxt      |   4 +
 .../api_def_ParallelInterleaveDataset.pbtxt   |  22 +
 .../api_def_ParseExampleDataset.pbtxt         |  70 ++
 .../api_def_PrivateThreadPoolDataset.pbtxt    |  13 +
 .../base_api/api_def_RandomDataset.pbtxt      |  19 +
 .../base_api/api_def_RebatchDataset.pbtxt     |  23 +
 .../base_api/api_def_ScanDataset.pbtxt        |   5 +
 .../api_def_SetStatsAggregatorDataset.pbtxt   |   4 +
 .../base_api/api_def_SleepDataset.pbtxt       |   4 +
 .../api_def_SlidingWindowDataset.pbtxt        |  26 +
 .../api_def/base_api/api_def_SqlDataset.pbtxt |  23 +
 .../api_def_StatsAggregatorHandle.pbtxt       |   5 +
 .../api_def_StatsAggregatorSummary.pbtxt      |   5 +
 .../base_api/api_def_TakeWhileDataset.pbtxt   |  25 +
 .../base_api/api_def_ThreadPoolDataset.pbtxt  |  13 +
 .../base_api/api_def_ThreadPoolHandle.pbtxt   |  35 +
 .../base_api/api_def_UnbatchDataset.pbtxt     |   5 +
 .../base_api/api_def_UniqueDataset.pbtxt      |   8 +
 ...f_ExperimentalIdentityIndexedDataset.pbtxt |   6 -
 ...pi_def_ExperimentalIndexedDatasetGet.pbtxt |   6 -
 ...xperimentalIndexedDatasetMaterialize.pbtxt |   6 -
 ...mentalMaterializedIndexDatasetHandle.pbtxt |   6 -
 ...f_ExperimentalNumaMapAndBatchDataset.pbtxt |   6 -
 tensorflow/core/kernels/data/dataset_ops.cc   |   2 +
 .../experimental/assert_next_dataset_op.cc    |   2 +
 .../experimental/auto_shard_dataset_op.cc     |   2 +
 .../experimental/choose_fastest_dataset_op.cc |   3 +-
 .../data/experimental/csv_dataset_op.cc       |   2 +-
 .../dense_to_sparse_batch_dataset_op.cc       |   2 +
 .../directed_interleave_dataset_op.cc         |   2 +
 .../group_by_reducer_dataset_op.cc            |   4 +
 .../group_by_window_dataset_op.cc             |   4 +
 .../experimental/ignore_errors_dataset_op.cc  |   2 +
 .../data/experimental/lmdb_dataset_op.cc      |   1 +
 .../experimental/map_and_batch_dataset_op.cc  |   4 +
 .../experimental/matching_files_dataset_op.cc |   2 +
 .../non_serializable_dataset_op.cc            |   2 +
 .../parallel_interleave_dataset_op.cc         |   4 +
 .../experimental/parse_example_dataset_op.cc  |   2 +
 .../data/experimental/prefetching_kernels.cc  |   2 +
 .../data/experimental/random_dataset_op.cc    |   2 +
 .../data/experimental/rebatch_dataset_op.cc   |   2 +
 .../data/experimental/scan_dataset_op.cc      |   2 +
 .../set_stats_aggregator_dataset_op.cc        |   3 +
 .../data/experimental/sleep_dataset_op.cc     |   9 +
 .../experimental/sliding_window_dataset_op.cc |   2 +
 .../data/experimental/sql_dataset_op.cc       |   1 +
 .../data/experimental/stats_aggregator_ops.cc |   7 +
 .../data/experimental/stats_dataset_ops.cc    |  11 +-
 .../experimental/take_while_dataset_op.cc     |   4 +
 .../experimental/threadpool_dataset_op.cc     |  11 +
 .../data/experimental/to_tf_record_op.cc      |   2 +
 .../data/experimental/unbatch_dataset_op.cc   |   2 +
 .../data/experimental/unique_dataset_op.cc    |   2 +
 .../core/ops/compat/ops_history.v1.pbtxt      | 183 -----
 .../core/ops/compat/ops_history.v2.pbtxt      | 183 -----
 .../core/ops/experimental_dataset_ops.cc      | 666 +++++++++++++-----
 .../python/data/experimental/ops/batching.py  |  47 +-
 .../data/experimental/ops/cardinality.py      |   7 +-
 .../data/experimental/ops/distribute.py       |  32 +-
 .../python/data/experimental/ops/error_ops.py |  15 +-
 .../python/data/experimental/ops/grouping.py  |  65 +-
 .../data/experimental/ops/interleave_ops.py   |  18 +-
 .../data/experimental/ops/matching_files.py   |   7 +-
 .../data/experimental/ops/optimization.py     |  49 +-
 .../data/experimental/ops/parsing_ops.py      |  33 +-
 .../data/experimental/ops/random_ops.py       |   9 +-
 .../python/data/experimental/ops/readers.py   |  47 +-
 .../python/data/experimental/ops/scan_ops.py  |  24 +-
 .../python/data/experimental/ops/sleep.py     |  15 +-
 .../data/experimental/ops/stats_aggregator.py |  11 +-
 .../python/data/experimental/ops/stats_ops.py |  24 +-
 .../data/experimental/ops/take_while_ops.py   |  18 +-
 .../data/experimental/ops/threadpool.py       |  46 +-
 .../python/data/experimental/ops/unique.py    |  12 +-
 .../python/data/experimental/ops/writers.py   |   9 +-
 tensorflow/python/data/ops/dataset_ops.py     |  59 +-
 tensorflow/python/data/ops/readers.py         |  32 +-
 .../api/golden/v1/tensorflow.raw_ops.pbtxt    | 164 ++++-
 .../api/golden/v2/tensorflow.raw_ops.pbtxt    | 164 ++++-
 104 files changed, 1907 insertions(+), 792 deletions(-)
 create mode 100644 tensorflow/core/api_def/base_api/api_def_AssertNextDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_AutoShardDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_BytesProducedStatsDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_CSVDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_ChooseFastestDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_DatasetCardinality.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_DatasetToTFRecord.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_DenseToSparseBatchDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_DirectedInterleaveDataset.pbtxt
 delete mode 100644 tensorflow/core/api_def/base_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt
 delete mode 100644 tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetGet.pbtxt
 delete mode 100644 tensorflow/core/api_def/base_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt
 delete mode 100644 tensorflow/core/api_def/base_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_GroupByReducerDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_GroupByWindowDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_IgnoreErrorsDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_IteratorGetDevice.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_LMDBDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_LatencyStatsDataset.pbtxt
 rename tensorflow/core/api_def/base_api/{api_def_ExperimentalNumaMapAndBatchDataset.pbtxt => api_def_MapAndBatchDataset.pbtxt} (85%)
 create mode 100644 tensorflow/core/api_def/base_api/api_def_MatchingFilesDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_MaxIntraOpParallelismDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_NonSerializableDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_ParallelInterleaveDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_ParseExampleDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_PrivateThreadPoolDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_RandomDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_RebatchDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_ScanDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_SetStatsAggregatorDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_SleepDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_SlidingWindowDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_SqlDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_StatsAggregatorHandle.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_StatsAggregatorSummary.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_TakeWhileDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_ThreadPoolDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_ThreadPoolHandle.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_UnbatchDataset.pbtxt
 create mode 100644 tensorflow/core/api_def/base_api/api_def_UniqueDataset.pbtxt
 delete mode 100644 tensorflow/core/api_def/java_api/api_def_ExperimentalIdentityIndexedDataset.pbtxt
 delete mode 100644 tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetGet.pbtxt
 delete mode 100644 tensorflow/core/api_def/java_api/api_def_ExperimentalIndexedDatasetMaterialize.pbtxt
 delete mode 100644 tensorflow/core/api_def/java_api/api_def_ExperimentalMaterializedIndexDatasetHandle.pbtxt
 delete mode 100644 tensorflow/core/api_def/java_api/api_def_ExperimentalNumaMapAndBatchDataset.pbtxt

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\'], "