docstr: calulates the running mean and std of a data stream
  https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
  
  :param epsilon: (float) helps with arithmetic issues
  :param shape: (tuple) the shape of the data stream's output
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code: def __init__(self, epsilon=1e-4, shape=()):
      """
      calulates the running mean and std of a data stream
      https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
  
      :param epsilon: (float) helps with arithmetic issues
      :param shape: (tuple) the shape of the data stream's output
      """
      self.mean = np.zeros(shape, "float64")
      self.var = np.ones(shape, "float64")
      self.count = epsilon
  
imports: import numpy
label_desc: Use image node_id 1 to create a new RunningMeanStd object from inherited base classes: object with example: obj = RunningMeanStd(epsilon, shape)