class_docstr: Args:
      average (bool): a way to output one single value for metrics
                      that are calculated in several trials.
class_docstr_tok: ["Args",":","average","(","bool",")",":","a","way","to","output","one","single","value","for","metrics","that","are","calculated","in","several","trials","."]
code: def update(self, output=None, target=None):
      self.loss.append(output)
  
imports: import dataclasses
  import math
  import warnings
  from collections import defaultdict
  import numpy
  import torch
  from sklearn.metrics import confusion_matrix, auc
  from baal.utils.array_utils import to_prob
label_desc: Use image node_id 3 for calling the Loss obj's underlying member method code with example usage: obj.update(output, target) without return types