# CHECK-SAME:   tensor<2xf32> {tf_saved_model.index_path = [0, 1]})
  # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["f0004_list_2_elements"]
  @tf.function(input_signature=[])
  def f0004_list_2_elements(self):
    return [[tf.constant(1.0, shape=[1]), tf.constant(1.0, shape=[2])]]

  # Check index paths for dicts.
  # Keys are linearized in sorted order, matching `tf.nest.flatten`.

  # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["f0001_list_2_elements"]
  @tf.function(input_signature=[[
      tf.TensorSpec([], tf.float32),
      tf.TensorSpec([], tf.float32),
  ]])
  def f0001_list_2_elements(self, l):
    return

  # Check index paths for dicts.
  # Keys are linearized in sorted order, matching `tf.nest.flatten`.
  #