old_contents: # Copyright 2019 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.
  # ==============================================================================
  """Tests for `tf.data.experimental.{from,to}_variant()`."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  from tensorflow.python.data.experimental.ops import cardinality
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.platform import test
  
  
  @test_util.run_all_in_graph_and_eager_modes
  class VariantTest(test_base.DatasetTestBase):
  
    def testRoundtripRange(self):
      dataset = dataset_ops.Dataset.range(10)
      variant = dataset_ops.to_variant(dataset)
      dataset = dataset_ops.from_variant(variant,
                                         dataset_ops.get_structure(dataset))
      self.assertDatasetProduces(dataset, range(10))
      self.assertEqual(self.evaluate(cardinality.cardinality(dataset)), 10)
  
    def testRoundtripMap(self):
      dataset = dataset_ops.Dataset.range(10).map(lambda x: x*x)
      variant = dataset_ops.to_variant(dataset)
      dataset = dataset_ops.from_variant(variant,
                                         dataset_ops.get_structure(dataset))
      self.assertDatasetProduces(dataset, [x * x for x in range(10)])
      self.assertEqual(self.evaluate(cardinality.cardinality(dataset)), 10)
  
  
  if __name__ == "__main__":
    test.main()
  
new_contents: # Copyright 2019 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.
  # ==============================================================================
  """Tests for `tf.data.experimental.{from,to}_variant()`."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  from absl.testing import parameterized
  
  from tensorflow.python.data.experimental.ops import cardinality
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import combinations
  from tensorflow.python.platform import test
  
  
  class VariantTest(test_base.DatasetTestBase, parameterized.TestCase):
  
    @combinations.generate(test_base.default_test_combinations())
    def testRoundtripRange(self):
      dataset = dataset_ops.Dataset.range(10)
      variant = dataset_ops.to_variant(dataset)
      dataset = dataset_ops.from_variant(variant,
                                         dataset_ops.get_structure(dataset))
      self.assertDatasetProduces(dataset, range(10))
      self.assertEqual(self.evaluate(cardinality.cardinality(dataset)), 10)
  
    @combinations.generate(test_base.default_test_combinations())
    def testRoundtripMap(self):
      dataset = dataset_ops.Dataset.range(10).map(lambda x: x*x)
      variant = dataset_ops.to_variant(dataset)
      dataset = dataset_ops.from_variant(variant,
                                         dataset_ops.get_structure(dataset))
      self.assertDatasetProduces(dataset, [x * x for x in range(10)])
      self.assertEqual(self.evaluate(cardinality.cardinality(dataset)), 10)
  
  
  if __name__ == "__main__":
    test.main()
  
subject: Switch VariantTest to use TF combinations