class_docstr: Maintains a stream of deviation and base values, and compute the ratio of their sums
  e.g. WAPE in demand forecasting.
  
  MD = \sigma{deviation} / \sigma{base}
  
  Call .restart() to clear added values and to start a new round of averaging
code: def __init__(self):
      super(MeanDeviationMeter, self).__init__(min_mode=True)
  
imports: from __future__ import annotations
  import time
  import warnings
  from abc import ABC, abstractmethod
  from typing import Optional, Union
  from torch import Tensor
  from ..engine.distributed import reduce_value
label_desc: Use image node_id 1 to create a new MeanDeviationMeter object from inherited base classes: Meter with example: obj = MeanDeviationMeter()