self.var_arr = [variables.Variable(1.), variables.Variable(2.)]
    self.dict1 = {"a": 1.}
    self.var_dict = {"a": variables.Variable(1.), "b": variables.Variable(2.)}


class SimpleModel(module.Module):
  """A simple model used for exercising the C++ API."""

  @def_function.function(input_signature=[
      tensor_spec.TensorSpec(shape=(), dtype=dtypes.float32),
  ])
  def test_float(self, x):

    }

    @Managed
    interface Thing {}

    @Managed
    interface SpecialThing extends Thing {}

    @Managed
    interface SimpleModel {
        Thing getThing()
    }

    @Managed
    interface SpecialModel extends SimpleModel {
        SpecialThing getThing()

        void setThing(SpecialThing thing)
    }

    def "a subclass may specialize a property type"() {

  Run all tests cases in both the graph mode (default in TF1) and the eager mode
  (default in TF2) to ensure support for when TF2 is disabled.
  """

  class SimpleModel(module.Module):

    def __init__(self):
      self.filters = np.random.uniform(low=-1.0, high=1.0, size=(4, 3)).astype(
          'f4'
      )

    @def_function.function(
        input_signature=[