diff --git a/tensorflow/python/profiler/overview_page_proto_to_gviz.py b/tensorflow/python/profiler/overview_page_proto_to_gviz.py
new file mode 100644
index 00000000000..84b01277c4e
--- /dev/null
+++ b/tensorflow/python/profiler/overview_page_proto_to_gviz.py
@@ -0,0 +1,142 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""For conversion of TF Overview Page protos to GViz DataTables.
+
+Usage:
+    gviz_data_table = generate_chart_table(overview_page)
+"""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import google_type_annotations
+from __future__ import print_function
+
+import datetime
+import gviz_api
+
+
+def get_run_environment_table_args(run_environment):
+  """Creates a gviz DataTable object from a RunEnvironment proto.
+
+  Args:
+    run_environment: An op_stats_pb2.RunEnvironment.
+
+  Returns:
+    Returns a gviz_api.DataTable
+  """
+
+  table_description = [
+      ("host_id", "string", "host_id"),
+      ("command_line", "string", "command_line"),
+      ("start_time", "string", "start_time"),
+      ("bns_address", "string", "bns_address"),
+  ]
+
+  data = []
+  for job in run_environment.host_dependent_job_info:
+    row = [
+        str(job.host_id),
+        str(job.command_line),
+        str(datetime.datetime.utcfromtimestamp(job.start_time)),
+        str(job.bns_address),
+    ]
+    data.append(row)
+
+  return (table_description, data, [])
+
+
+def generate_run_environment_table(run_environment):
+  (table_description, data,
+   custom_properties) = get_run_environment_table_args(run_environment)
+  return gviz_api.DataTable(table_description, data, custom_properties)
+
+
+def get_overview_page_analysis_table_args(overview_page_analysis):
+  """Creates a gviz DataTable object from an OverviewPageAnalysis proto.
+
+  Args:
+    overview_page_analysis: An overview_page_pb2.OverviewPageAnalysis.
+
+  Returns:
+    Returns a gviz_api.DataTable
+  """
+
+  table_description = [
+      ("selfTimePercent", "number", "Time (%)"),
+      ("cumulativeTimePercent", "number", "Cumulative time (%)"),
+      ("category", "string", "Category"),
+      ("operation", "string", "Operation"),
+      ("flopRate", "number", "GFLOPs/Sec"),
+  ]
+
+  data = []
+  for op in overview_page_analysis.top_device_ops:
+    row = [
+        op.self_time_fraction,
+        op.cumulative_time_fraction,
+        str(op.category),
+        str(op.name),
+        op.flop_rate,
+    ]
+    data.append(row)
+
+  return (table_description, data, [])
+
+
+def generate_overview_page_analysis_table(overview_page_analysis):
+  (table_description, data, custom_properties) = \
+      get_overview_page_analysis_table_args(overview_page_analysis)
+  return gviz_api.DataTable(table_description, data, custom_properties)
+
+
+def get_recommendation_table_args(overview_page_recommendation):
+  """Creates a gviz DataTable object from an OverviewPageRecommendation proto.
+
+  Args:
+    overview_page_recommendation: An
+      overview_page_pb2.OverviewPageRecommendation.
+
+  Returns:
+    Returns a gviz_api.DataTable
+  """
+
+  table_description = [
+      ("tip_type", "string", "tip_type"),
+      ("link", "string", "link"),
+  ]
+
+  data = []
+  for faq_tip in overview_page_recommendation.faq_tips:
+    data.append(["faq", faq_tip.link])
+
+  for host_tip in overview_page_recommendation.host_tips:
+    data.append(["host", host_tip.link])
+
+  for device_tip in overview_page_recommendation.device_tips:
+    data.append(["device", device_tip.link])
+
+  for doc_tip in overview_page_recommendation.documentation_tips:
+    data.append(["doc", doc_tip.link])
+
+  for inference_tip in overview_page_recommendation.inference_tips:
+    data.append(["inference", inference_tip.link])
+
+  return (table_description, data, [])
+
+
+def generate_recommendation_table(overview_page_recommendation):
+  (table_description, data, custom_properties) = \
+      get_recommendation_table_args(overview_page_recommendation)
+  return gviz_api.DataTable(table_description, data, custom_properties)
diff --git a/tensorflow/python/profiler/overview_page_proto_to_gviz_test.py b/tensorflow/python/profiler/overview_page_proto_to_gviz_test.py
new file mode 100644
index 00000000000..0faf3739f23
--- /dev/null
+++ b/tensorflow/python/profiler/overview_page_proto_to_gviz_test.py
@@ -0,0 +1,285 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+# Lint as: python3
+"""Tests for overview_page_proto_to_gviz."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import collections
+import csv
+import io
+
+import gviz_api
+
+# pylint: disable=g-direct-tensorflow-import
+from tensorflow.core.profiler.protobuf import op_stats_pb2
+from tensorflow.core.profiler.protobuf import overview_page_pb2
+from tensorflow.python.platform import test
+from tensorflow.python.profiler import overview_page_proto_to_gviz
+# pylint: enable=g-direct-tensorflow-import
+
+
+class ProtoToGvizTest(test.TestCase):
+
+  @classmethod
+  def setUpClass(cls):
+    super(ProtoToGvizTest, cls).setUpClass()
+    MockRunEnvironment = collections.namedtuple(  # pylint: disable=invalid-name
+        "MockRunEnvironment",
+        ["host_id", "command_line", "start_time", "bns_address"])
+
+    ProtoToGvizTest.mock_run_env = MockRunEnvironment(
+        host_id="1",
+        command_line="2",
+        start_time=1582202096,
+        bns_address="4",
+    )
+
+    MockOverviewTfOp = collections.namedtuple(  # pylint: disable=invalid-name
+        "MockOverviewTfOp", [
+            "self_time_fraction",
+            "cumulative_time_fraction",
+            "category",
+            "name",
+            "flop_rate",
+        ])
+
+    ProtoToGvizTest.mock_tf_op = MockOverviewTfOp(
+        self_time_fraction=3.0,
+        cumulative_time_fraction=4.0,
+        category="2",
+        name="1",
+        flop_rate=5.0,
+    )
+
+    MockTip = collections.namedtuple(  # pylint: disable=invalid-name
+        "MockTip", [
+            "tip_type",
+            "link",
+        ])
+
+    ProtoToGvizTest.mock_tips = []
+    for tip in ["faq", "host", "device", "doc"]:
+      for idx in range(0, 3):
+        ProtoToGvizTest.mock_tips.append(MockTip(tip, tip + "_link" + str(idx)))
+
+  # Checks that DataTable columns match schema defined in table_description.
+  def check_header_row(self, data, table_description, row_values):
+    for (cc, column_header) in enumerate(row_values):
+      self.assertEqual(table_description[cc][2], column_header)
+
+  # Checks that DataTable row value representation matches number or string.
+  def check_row_types(self, data, table_description, row_values, row_idx):
+    for (cc, cell_str) in enumerate(row_values):
+      raw_value = data[row_idx - 1][cc]
+      value_type = table_description[cc][1]
+
+      # Only number and strings are used in our DataTable schema.
+      self.assertIn(value_type, ["number", "string"])
+
+      # Encode in similar fashion as DataTable.ToCsv().
+      expected_value = gviz_api.DataTable.CoerceValue(raw_value, value_type)
+      self.assertNotIsInstance(expected_value, tuple)
+      self.assertEqual(expected_value, raw_value)
+      self.assertEqual(str(expected_value), cell_str)
+
+  def create_empty_run_environment(self):
+    return op_stats_pb2.RunEnvironment()
+
+  def create_empty_overview_page_analysis(self):
+    return overview_page_pb2.OverviewPageAnalysis()
+
+  def create_empty_recommendation(self):
+    return overview_page_pb2.OverviewPageRecommendation()
+
+  def create_mock_run_environment(self):
+    run_env = op_stats_pb2.RunEnvironment()
+
+    # Add 3 rows
+    for _ in range(0, 3):
+      job = op_stats_pb2.HostDependentJobInfoResult()
+      job.host_id = self.mock_run_env.host_id
+      job.command_line = self.mock_run_env.command_line
+      job.start_time = self.mock_run_env.start_time
+      job.bns_address = self.mock_run_env.bns_address
+      run_env.host_dependent_job_info.append(job)
+
+    return run_env
+
+  def test_run_environment_empty(self):
+    run_env = self.create_empty_run_environment()
+    data_table = overview_page_proto_to_gviz.generate_run_environment_table(
+        run_env)
+
+    self.assertEqual(0, data_table.NumberOfRows(),
+                     "Empty table should have 0 rows.")
+    # Check the number of columns in Run environment data table.
+    self.assertLen(data_table.columns, len(list(self.mock_run_env)))
+
+  def test_run_environment_simple(self):
+    run_env = self.create_mock_run_environment()
+    (table_description, data, custom_properties) = \
+        overview_page_proto_to_gviz.get_run_environment_table_args(run_env)
+    data_table = gviz_api.DataTable(table_description, data, custom_properties)
+
+    # Data is a list of 3 rows.
+    self.assertLen(data, 3)
+    self.assertEqual(3, data_table.NumberOfRows(), "Simple table has 3 rows.")
+    # Check the number of columns in table descriptor and data table.
+    self.assertLen(table_description, len(list(self.mock_run_env)))
+    self.assertLen(data_table.columns, len(list(self.mock_run_env)))
+
+    # Prepare expectation to check against.
+    # get_run_environment_table_args() formats ns to RFC3339_full format.
+    mock_data_run_env = self.mock_run_env._replace(
+        start_time="2020-02-20 12:34:56")
+    # Check data against mock values.
+    for row in data:
+      self.assertEqual(list(mock_data_run_env), row)
+
+    # Check DataTable against mock values.
+    # Only way to access DataTable contents is by CSV
+    csv_file = io.StringIO(data_table.ToCsv())
+    reader = csv.reader(csv_file)
+
+    for (rr, row_values) in enumerate(reader):
+      if rr == 0:
+        self.check_header_row(data, table_description, row_values)
+      else:
+        self.check_row_types(data, table_description, row_values, rr)
+
+        self.assertEqual(list(mock_data_run_env), row_values)
+
+  def create_mock_overview_page_analysis(self):
+    analysis = overview_page_pb2.OverviewPageAnalysis()
+
+    # Add 3 rows
+    for _ in range(0, 3):
+      op = overview_page_pb2.OverviewTfOp()
+      op.self_time_fraction = self.mock_tf_op.self_time_fraction
+      op.cumulative_time_fraction = self.mock_tf_op.cumulative_time_fraction
+      op.category = self.mock_tf_op.category
+      op.name = self.mock_tf_op.name
+      op.flop_rate = self.mock_tf_op.flop_rate
+      analysis.top_device_ops.append(op)
+
+    return analysis
+
+  def test_overview_page_analysis_empty(self):
+    analysis = self.create_empty_overview_page_analysis()
+    data_table = \
+        overview_page_proto_to_gviz.generate_overview_page_analysis_table(
+            analysis)
+
+    self.assertEqual(0, data_table.NumberOfRows(),
+                     "Empty table should have 0 rows.")
+    # Check the number of Overview Page Analysis data table columns.
+    self.assertLen(data_table.columns, len(list(self.mock_tf_op)))
+
+  def test_overview_page_analysis_simple(self):
+    analysis = self.create_mock_overview_page_analysis()
+    (table_description, data, custom_properties) = \
+        overview_page_proto_to_gviz.get_overview_page_analysis_table_args(
+            analysis)
+    data_table = gviz_api.DataTable(table_description, data, custom_properties)
+
+    # Data is a list of 3 rows.
+    self.assertLen(data, 3)
+    self.assertEqual(3, data_table.NumberOfRows(), "Simple table has 3 rows.")
+    # Check the number of columns in table descriptor and data table.
+    self.assertLen(table_description, len(list(self.mock_tf_op)))
+    self.assertLen(data_table.columns, len(list(self.mock_tf_op)))
+
+    # Prepare expectation to check against.
+    mock_csv_tf_op = [str(x) for x in list(self.mock_tf_op)]
+
+    # Check data against mock values.
+    for row in data:
+      self.assertEqual(list(self.mock_tf_op), row)
+
+    # Check DataTable against mock values.
+    # Only way to access DataTable contents is by CSV
+    csv_file = io.StringIO(data_table.ToCsv())
+    reader = csv.reader(csv_file)
+
+    for (rr, row_values) in enumerate(reader):
+      if rr == 0:
+        self.check_header_row(data, table_description, row_values)
+      else:
+        self.check_row_types(data, table_description, row_values, rr)
+
+        self.assertEqual(mock_csv_tf_op, row_values)
+
+  def create_mock_recommendation(self):
+    recommendation = overview_page_pb2.OverviewPageRecommendation()
+
+    for idx in range(0, 3):
+      recommendation.faq_tips.add().link = "faq_link" + str(idx)
+      recommendation.host_tips.add().link = "host_link" + str(idx)
+      recommendation.device_tips.add().link = "device_link" + str(idx)
+      recommendation.documentation_tips.add().link = "doc_link" + str(idx)
+
+    return recommendation
+
+  def test_recommendation_empty(self):
+    recommendation = self.create_empty_recommendation()
+    data_table = overview_page_proto_to_gviz.generate_recommendation_table(
+        recommendation)
+
+    self.assertEqual(0, data_table.NumberOfRows(),
+                     "Empty table should have 0 rows.")
+    # Check the number of Overview Page Recommendation data table columns.
+    # One for tip_type, and one for link
+    self.assertLen(data_table.columns, 2)
+
+  def test_recommendation_simple(self):
+    recommendation = self.create_mock_recommendation()
+    (table_description, data, custom_properties) = \
+        overview_page_proto_to_gviz.get_recommendation_table_args(
+            recommendation)
+    data_table = gviz_api.DataTable(table_description, data, custom_properties)
+
+    # Data is a list of 12 rows: 3 rows for each tip type.
+    self.assertLen(data, len(list(self.mock_tips)))
+    self.assertLen(
+        list(self.mock_tips), data_table.NumberOfRows(),
+        "Simple table has 12 rows.")
+    # Check the number of columns in table descriptor and data table.
+    self.assertLen(table_description, 2)
+    self.assertLen(data_table.columns, 2)
+
+    # Check data against mock values.
+    for idx, row in enumerate(data):
+      self.assertEqual(list(self.mock_tips[idx]), row)
+
+    # Check DataTable against mock values.
+    # Only way to access DataTable contents is by CSV
+    csv_file = io.StringIO(data_table.ToCsv())
+    reader = csv.reader(csv_file)
+
+    for (rr, row_values) in enumerate(reader):
+      if rr == 0:
+        self.check_header_row(data, table_description, row_values)
+      else:
+        self.check_row_types(data, table_description, row_values, rr)
+
+        self.assertEqual(list(self.mock_tips[rr - 1]), row_values)
+
+
+if __name__ == "__main__":
+  test.main()