code: def test_return_normalization_wrapper():
      """Unit tests"""
      observation_conversion = ObservationConversion()
  
      env = DummyEnvironment(
          core_env=DummyCoreEnvironment(observation_conversion.space()),
          action_conversion=[DictActionConversion()],
          observation_conversion=[observation_conversion],
      )
  
      env = ReturnNormalizationRewardWrapper(
          env, gamma=0.99, epsilon=1e-8
      )
      env.reset()
      reward = env.step(env.action_space.sample())[1]
      assert isinstance(reward, float)
      assert not hasattr(reward, "shape")
  
file_path: maze/maze/test/core/wrappers/test_return_normalization_reward_wrapper.py
imports: from maze.core.wrappers.maze_gym_env_wrapper import GymMazeEnv
  from maze.core.wrappers.return_normalization_reward_wrapper import ReturnNormalizationRewardWrapper
  from maze.test.shared_test_utils.dummy_env.dummy_core_env import DummyCoreEnvironment
  from maze.test.shared_test_utils.dummy_env.dummy_maze_env import DummyEnvironment
  from maze.test.shared_test_utils.dummy_env.space_interfaces.action_conversion.dict import DictActionConversion
  from maze.test.shared_test_utils.dummy_env.space_interfaces.observation_conversion.dict import ObservationConversion
  from maze.test.shared_test_utils.wrappers import assert_wrapper_clone_from
label_desc: Use image node_id 1 for calling a global function with example usage: test_return_normalization_wrapper() without return types