message: Fix: Divergent test layers
diff: @@ -474,12 +474,15 @@ class TimeDistributedTest(keras_parameterized.TestCase):
  @keras_parameterized.run_all_keras_modes
  def test_TimeDistributed_with_mimo(self):
  + dense_1 = keras.layers.Dense(8)
  + dense_2 = keras.layers.Dense(16)
  +
  class TestLayer(keras.layers.Layer):
  def __init__(self):
  super(TestLayer, self).__init__()
  - self.dense_1 = keras.layers.Dense(8)
  - self.dense_2 = keras.layers.Dense(16)
  + self.dense_1 = dense_1
  + self.dense_2 = dense_2
  def build(self, input_shape):
  super(TestLayer, self).build(input_shape)
  @@ -512,19 +515,20 @@ class TimeDistributedTest(keras_parameterized.TestCase):
  model_1.compile(optimizer='rmsprop', loss='mse',
  run_eagerly=testing_utils.should_run_eagerly())
  output_1 = model_1.predict((data_1, data_2), steps=1)
  - model_1.fit(
  - x=[np.random.random((10, 2, 2, 1)), np.random.random((10, 2, 2, 1))],
  - y=[np.random.random((10, 2, 2, 8)), np.random.random((10, 2, 2, 16))],
  - epochs=1,
  - batch_size=3)
  - y1 = keras.layers.Dense(8)(x1)
  - y2 = keras.layers.Dense(16)(x2)
  + y1 = dense_1(x1)
  + y2 = dense_2(x2)
  model_2 = keras.models.Model([x1, x2], [y1, y2])
  output_2 = model_2.predict((data_1, data_2), steps=1)
  self.assertAllClose(output_1, output_2)
  + model_1.fit(
  + x=[np.random.random((10, 2, 2, 1)), np.random.random((10, 2, 2, 1))],
  + y=[np.random.random((10, 2, 2, 8)), np.random.random((10, 2, 2, 16))],
  + epochs=1,
  + batch_size=3)
  +
  @combinations.generate(combinations.combine(mode=['graph', 'eager']))
  class BidirectionalTest(test.TestCase, parameterized.TestCase):
  