code: def __init__(self, gamma: Optional[float] = 0.99):
      super(EMAMetric, self).__init__()
      self._val = 0.0
      self._gamma = gamma
  
imports: import argparse
  import logging
  import math
  import os
  import random
  from collections import namedtuple
  from typing import Optional, Union
  import matplotlib.pyplot
  import numpy
  import torch
  import tqdm
  from torch import distributions, nn, optim
  import torchsde
label_desc: Use image node_id 1 to create a new EMAMetric object from inherited base classes: object with example: obj = EMAMetric(gamma)