message: Remove checks from keras base_layer tests that try to check the graph on the output keras tensor (because this is checking implementation details that are going to change)
diff: @@ -622,26 +622,22 @@ class SymbolicSupportTest(keras_parameterized.TestCase):
  def test_using_symbolic_tensors_with_tf_ops(self):
  # Single-input.
  x = input_layer.Input((3,))
  - y = math_ops.square(x)
  - self.assertEqual(y.graph, backend.get_graph())
  + math_ops.square(x)
  # Multi-inputs.
  x1, x2 = input_layer.Input((3,)), input_layer.Input((3,))
  - y = array_ops.concat([x1, x2], axis=1)
  - self.assertEqual(y.graph, backend.get_graph())
  + array_ops.concat([x1, x2], axis=1)
  # Mixing Keras symbolic tensors and graph tensors from the same graph works.
  with backend.get_graph().as_default():
  x1 = input_layer.Input((3,))
  x2 = input_layer.Input((3,))
  - y = math_ops.matmul(x1, x2)
  - self.assertEqual(y.graph, backend.get_graph())
  + math_ops.matmul(x1, x2)
  # Creating same op type (matmul) multiple times in the Keras graph works.
  x1 = input_layer.Input((3,))
  x2 = input_layer.Input((3,))
  - y = math_ops.matmul(x1, x2)
  - self.assertEqual(y.graph, backend.get_graph())
  + math_ops.matmul(x1, x2)
  def test_mixing_eager_and_graph_tensors(self):
  with ops.Graph().as_default():
  @@ -663,7 +659,7 @@ class SymbolicSupportTest(keras_parameterized.TestCase):
  x1 = input_layer.Input((3,))
  x2 = array_ops.ones((3, 3))
  y = math_ops.matmul(x1, x2)
  - self.assertEqual(y.graph, backend.get_graph())
  +
  fn = backend.function(inputs=[x1], outputs=[y])
  x_val = np.random.random((3, 3))
  y_val = np.ones((3, 3))
  @@ -676,7 +672,7 @@ class SymbolicSupportTest(keras_parameterized.TestCase):
  x1 = input_layer.Input((3,))
  x2 = np.ones((3, 3), dtype='float32')
  y = math_ops.matmul(x1, x2)
  - self.assertEqual(y.graph, backend.get_graph())
  +
  fn = backend.function(inputs=[x1], outputs=[y])
  x_val = np.random.random((3, 3))
  y_val = np.ones((3, 3))
  