code: def __init__(self, return_reward_idx=0):
      self.action_space = gym.spaces.Discrete(2)
      self.observation_space = gym.spaces.Box(
          low=np.array([-1.0]), high=np.array([1.0]), dtype=np.float64
      )
      self.returned_rewards = [0, 1, 2, 3, 4]
      self.return_reward_idx = return_reward_idx
      self.t = self.return_reward_idx
  
file_path: gym/tests/wrappers/test_normalize.py
imports: from typing import Optional
  import numpy
  from numpy.testing import assert_almost_equal
  import gym
  from gym.wrappers.normalize import NormalizeObservation, NormalizeReward
label_desc: Use image node_id 1 to create a new DummyRewardEnv object from inherited base classes: gym with example: obj = DummyRewardEnv(return_reward_idx)