text: # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
  from collections import defaultdict
  from collections import deque
  
  import torch
  
  
  class SmoothedValue(object):
      """Track a series of values and provide access to smoothed values over a
      window or the global series average.
      """
      def __init__(self, window_size=20):
          self.deque = deque(maxlen=window_size)
          self.series = []
          self.total = 0.0
          self.count = 0
  
      def update(self, value):
          self.deque.append(value)
          self.series.append(value)
          self.count += 1
          self.total += value
  
      @property
      def median(self):
          d = torch.tensor(list(self.deque))
          return d.median().item()
  
      @property
      def avg(self):
          d = torch.tensor(list(self.deque))
          return d.mean().item()
  
      @property
      def global_avg(self):
          return self.total / self.count
  
      @property
      def max(self):
          d = torch.tensor(list(self.deque))
          return d.max().item()
  
  
  class MetricLogger(object):
      def __init__(self, delimiter="\t"):
          self.meters = defaultdict(SmoothedValue)
          self.delimiter = delimiter
  
      def update(self, **kwargs):
          for k, v in kwargs.items():
              if isinstance(v, torch.Tensor):
                  v = v.item()
              assert isinstance(v, (float, int))
              self.meters[k].update(v)
  
      def __getattr__(self, attr):
          if attr in self.meters:
              return self.meters[attr]
          if attr in self.__dict__:
              return self.__dict__[attr]
          raise AttributeError("'{}' object has no attribute '{}'".format(
              type(self).__name__, attr))
  
      def __str__(self):
          loss_str = []
          for name, meter in self.meters.items():
              loss_str.append("{}: {:.4f} ({:.4f})".format(
                  name, meter.median, meter.global_avg))
          return self.delimiter.join(loss_str)
  
      def to_dict(self):
          res = {}
          for name, meter in self.meters.items():
              if 'loss' in name:
                  res[name] = meter.avg
  
          return res