text: # coding=utf-8
  # Copyright 2021 The TensorFlow Datasets Authors.
  #
  # 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 tensorflow_datasets.core.utils.tf_utils."""
  
  import tensorflow.compat.v2 as tf
  from tensorflow_datasets import testing
  from tensorflow_datasets.core.utils import tf_utils
  
  
  class TfUtilsTest(testing.TestCase):
  
    @testing.run_in_graph_and_eager_modes()
    def test_graph_runner(self):
      graph_runner = tf_utils.TFGraphRunner()
  
      output = graph_runner.run(tf.nn.relu, [1, 1, -1, -1, 1])
      self.assertAllEqual(output, [1, 1, 0, 0, 1])
  
      output = graph_runner.run(tf.nn.relu, [-1, -1, -1, 1, 1])
      self.assertAllEqual(output, [0, 0, 0, 1, 1])
  
      # Cache should have been re-used, so should only contains one GraphRun
      # Ideally there should be two separate @tf.eager.run_test_in_graph() and
      # @tf.eager.run_test_in_eager() to avoid logic on the test. But haven't
      # found it.
      if not tf.executing_eagerly():
        self.assertEqual(len(graph_runner._graph_run_cache), 1)
      else:
        self.assertEqual(len(graph_runner._graph_run_cache), 0)
  
      # Different signature (different shape), so new GraphRun created
      output = graph_runner.run(tf.nn.relu, [-1, 1, 1])
      self.assertAllEqual(output, [0, 1, 1])
      if not tf.executing_eagerly():
        self.assertEqual(len(graph_runner._graph_run_cache), 2)
      else:
        self.assertEqual(len(graph_runner._graph_run_cache), 0)
  
  
  def test_shapes_are_compatible():
    assert tf_utils.shapes_are_compatible(
        {'a': {
            'b': (28, 28, 3)
        }},
        {'a': {
            'b': (None, None, 3)
        }},
    )
    assert not tf_utils.shapes_are_compatible(
        {'a': {
            'b': (28, 28, 3)
        }},
        {'a': {
            'b': (None, 27, 3)
        }},
    )
  
  
  if __name__ == '__main__':
    testing.test_main()
  