message: Add stateful metrics to interleaved eval test
diff: @@ -602,7 +602,7 @@ class TestDistributionStrategyWithDatasets(test.TestCase,
  user_controlled_model.compile(
  gradient_descent.GradientDescentOptimizer(0.001),
  loss='mse',
  - metrics=['mae'],
  + metrics=['mae', keras.metrics.CategoricalAccuracy()],
  distribute=distribution)
  interleaved_model = get_model()
  @@ -610,7 +610,7 @@ class TestDistributionStrategyWithDatasets(test.TestCase,
  interleaved_model.compile(
  gradient_descent.GradientDescentOptimizer(0.001),
  loss='mse',
  - metrics=['mae'],
  + metrics=['mae', keras.metrics.CategoricalAccuracy()],
  distribute=distribution)
  dataset = get_dataset(distribution)
  @@ -632,7 +632,8 @@ class TestDistributionStrategyWithDatasets(test.TestCase,
  [x[0] for x in user_controlled_output])
  self.assertEqual(interleaved_output.history['val_mean_absolute_error'],
  [x[1] for x in user_controlled_output])
  - # TODO(sourabhbajaj): Add an stateful metric here and verify support.
  + self.assertEqual(interleaved_output.history['val_categorical_accuracy'],
  + [x[2] for x in user_controlled_output])
  # TODO(priyag): Enable this test for TPU. Currently tuples/dict don't work
  # as clone_model's input_tensors argument only seems to accept list and not
  