docstr: Returns the average reward of each episode
  
  :return: (float)
docstr_tok: ["Returns","the","average","reward","of","each","episode",":","return",":","(","float",")"]
code: def mean_reward(self):
      """
      Returns the average reward of each episode
  
      :return: (float)
      """
      if self.rewbuffer:
          return np.mean(self.rewbuffer)
      else:
          return 0
  
imports: import time
  import warnings
  import numpy
  import tensorflow
  from gym.spaces import Discrete, Box
  from collections import deque
  from stable_baselines import logger
  from stable_baselines.common.schedules import Scheduler
  from stable_baselines.common.tf_util import batch_to_seq, seq_to_batch, check_shape, avg_norm, gradient_add, q_explained_variance, total_episode_reward_logger
  from stable_baselines.acer.buffer import Buffer
  from stable_baselines.common import ActorCriticRLModel, tf_util, SetVerbosity, TensorboardWriter
  from stable_baselines.common.runners import AbstractEnvRunner
  from stable_baselines.common.policies import ActorCriticPolicy, RecurrentActorCriticPolicy
label_desc: Use image node_id 4 for calling the EpisodeStats obj's underlying member method code with example usage: obj.mean_reward() and returns: np, int