code: def bytes2human(n):
      # http://code.activestate.com/recipes/578019
      # >>> bytes2human(10000)
      # '9.8K'
      # >>> bytes2human(100001221)
      # '95.4M'
      symbols = ("K", "M", "G", "T", "P", "E", "Z", "Y")
      prefix = {}
      for i, s in enumerate(symbols):
          prefix[s] = 1 << (i + 1) * 10
      for s in reversed(symbols):
          if n >= prefix[s]:
              value = float(n) / prefix[s]
              return "%.1f%s" % (value, s)
      return "%sB" % n
  
file_path: avalanche/avalanche/evaluation/metric_utils.py
imports: from typing import Dict, Optional, Union, Iterable, Sequence, Tuple, TYPE_CHECKING, List, Callable, Any
  import matplotlib.pyplot
  import numpy
  from matplotlib.axes import Axes
  from numpy import ndarray, arange
  from torch import Tensor
label_desc: Use image node_id 7 for calling a global function with example usage: bytes2human(n) and returns: unknown, unknown