class_docstr: Calculating running mean and variance
  https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
class_docstr_tok: ["Calculating","running","mean","and","variance","https",":","\/\/en.wikipedia.org\/wiki\/Algorithms_for_calculating_variance","#","Parallel_algorithm"]
code: def __init__(self, epsilon=1e-4, shape=()):
      self.mean = np.zeros(shape, "float64")
      self.var = np.ones(shape, "float64")
      self.count = epsilon
  
imports: import numpy
  import gym
  import time
  from parl.env.compat_wrappers import CompatWrapper
label_desc: Use image node_id 1 to create a new RunningMeanStd object from inherited base classes: object with example: obj = RunningMeanStd(epsilon, shape)