class_docstr: A moving average, normalizing wrapper for vectorized environment.
  
  It is pickleable which will save moving averages and configuration parameters.
  The wrapped environment `venv` is not saved, and must be restored manually with
  `set_venv` after being unpickled.
  
  :param venv: (VecEnv) the vectorized environment to wrap
  :param training: (bool) Whether to update or not the moving average
  :param norm_obs: (bool) Whether to normalize observation or not (default: True)
  :param norm_reward: (bool) Whether to normalize rewards or not (default: True)
  :param clip_obs: (float) Max absolute value for observation
  :param clip_reward: (float) Max value absolute for discounted reward
  :param gamma: (float) discount factor
  :param epsilon: (float) To avoid division by zero
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docstr: Returns an unnormalized version of the rewards from the most recent step.
docstr_tok: ["Returns","an","unnormalized","version","of","the","rewards","from","the","most","recent","step","."]
code: def get_original_reward(self) -> np.ndarray:
      """
      Returns an unnormalized version of the rewards from the most recent step.
      """
      return self.old_rews.copy()
  
imports: import pickle
  import warnings
  import numpy
  from stable_baselines.common.vec_env.base_vec_env import VecEnvWrapper
  from stable_baselines.common.running_mean_std import RunningMeanStd
label_desc: Use image node_id 10 for calling the VecNormalize obj's underlying member method code with example usage: obj.get_original_reward() and returns: self