message: Skip the metrics as suggested in review feedback
diff: @@ -27,6 +27,7 @@ from tensorflow.python.data.ops import readers
  from tensorflow.python.eager import context
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.keras import keras_parameterized
  +from tensorflow.python.keras import testing_utils
  from tensorflow.python.keras.engine import training_utils
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.platform import test
  @@ -225,13 +226,9 @@ class StandardizeWeightsTest(keras_parameterized.TestCase):
  expected = sample_weights * np.array([0.5, 1., 0.5, 0.5, 1.5])
  self.assertAllClose(weights, expected)
  - @tf_test_util.run_in_graph_and_eager_modes
  def test_dataset_with_class_weight(self):
  model = testing_utils.get_small_functional_mlp(1, 4, input_dim=3)
  - optimizer = RMSPropOptimizer(learning_rate=0.001)
  - loss = 'mse'
  - metrics = ['mae', metrics_module.CategoricalAccuracy()]
  - model.compile(optimizer, loss, metrics=metrics)
  + model.compile('rmsprop', 'mse')
  inputs = np.zeros((10, 3), np.float32)
  targets = np.zeros((10, 4), np.float32)
  