class_docstr: Abstract class for meters used in metric stats.
  Every subclass has cached values for some metric
  
  Parameters
  ----------
  min_mode: bool or None
      if set to true, the smaller value is considered better and vice versa;
      if set to None, no optimality is defined.
code: def __repr__(self) -> str:
      main_str = (
          f"{self.__class__.__name__}: "
          f"current_value = {self.value:.4f}"
      )
      if self.best is not None:
          main_str += f", best_value = {self.best:.4f}"
      return main_str
  
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 9 for calling the Meter obj's underlying member method code with example usage: obj.__repr__() and returns: main_str