message: Enabled and fixed custom layer training arg test.
  This test did not run due to its method name.
diff: @@ -699,10 +699,11 @@ class BaseLayerTest(keras_parameterized.TestCase):
  self.assertEqual([None, 3], layer._build_input_shape.as_list())
  @combinations.generate(combinations.combine(mode=['eager']))
  - def custom_layer_training_arg(self):
  + def test_custom_layer_training_arg(self):
  class CustomLayerNoTrainingArg(base_layer.Layer):
  def __init__(self, nested_layer=None):
  + super(CustomLayerNoTrainingArg, self).__init__()
  self._nested_layer = nested_layer or array_ops.identity
  def call(self, inputs):
  @@ -711,6 +712,7 @@ class BaseLayerTest(keras_parameterized.TestCase):
  class CustomLayerDefaultTrainingMissing(base_layer.Layer):
  def __init__(self, nested_layer=None):
  + super(CustomLayerDefaultTrainingMissing, self).__init__()
  self._nested_layer = nested_layer or array_ops.identity
  def call(self, inputs, training):
  @@ -722,6 +724,7 @@ class BaseLayerTest(keras_parameterized.TestCase):
  class CustomLayerDefaultTrainingNone(base_layer.Layer):
  def __init__(self, nested_layer=None):
  + super(CustomLayerDefaultTrainingNone, self).__init__()
  self._nested_layer = nested_layer or array_ops.identity
  def call(self, inputs, training=None):
  @@ -733,6 +736,7 @@ class BaseLayerTest(keras_parameterized.TestCase):
  class CustomLayerDefaultTrainingFalse(base_layer.Layer):
  def __init__(self, nested_layer=None):
  + super(CustomLayerDefaultTrainingFalse, self).__init__()
  self._nested_layer = nested_layer or array_ops.identity
  def call(self, inputs, training=False):
  @@ -744,6 +748,7 @@ class BaseLayerTest(keras_parameterized.TestCase):
  class CustomLayerDefaultTrainingTrue(base_layer.Layer):
  def __init__(self, nested_layer=None):
  + super(CustomLayerDefaultTrainingTrue, self).__init__()
  self._nested_layer = nested_layer or array_ops.identity
  def call(self, inputs, training=True):
  @@ -782,14 +787,14 @@ class BaseLayerTest(keras_parameterized.TestCase):
  # nested layers, respecting whatever mode the outer layer was run with.
  layer = CustomLayerDefaultTrainingTrue(CustomLayerDefaultTrainingFalse())
  # No outer value passed: use local defaults
  - self.assertAllEqual(layer(x), x * 0.25) # Use local default False
  + self.assertAllEqual(layer(x), x) # Use outer default True
  # Outer value passed: override local defaults
  self.assertAllEqual(layer(x, training=False), x * 0.25)
  self.assertAllEqual(layer(x, training=True), x)
  layer = CustomLayerDefaultTrainingFalse(CustomLayerDefaultTrainingTrue())
  # No outer value passed: use local defaults
  - self.assertAllEqual(layer(x), x) # Use local default True
  + self.assertAllEqual(layer(x), x * 0.25) # Use outer default False
  # Outer value passed: override local defaults
  self.assertAllEqual(layer(x, training=False), x * 0.25)
  self.assertAllEqual(layer(x, training=True), x)
  @@ -804,8 +809,8 @@ class BaseLayerTest(keras_parameterized.TestCase):
  self.assertAllEqual(layer(x, training=True), x)
  layer = CustomLayerDefaultTrainingNone(CustomLayerDefaultTrainingTrue())
  - self.assertAllEqual(layer(x), x) # Use local default True
  - self.assertAllEqual(layer(x, training=False), x * 0.5)
  + self.assertAllEqual(layer(x), x * 0.5) # Nested use local default True
  + self.assertAllEqual(layer(x, training=False), x * 0.25)
  self.assertAllEqual(layer(x, training=True), x)
  def test_activity_regularizer_string(self):
  