code: def update(
      self,
      predicted,
      gold,
      mention_to_predicted,
      mention_to_gold,
      **kwargs,
  ):
      for e in self.evaluators:
          e.update(
              predicted, gold, mention_to_predicted, mention_to_gold
          )
  
      c_tuple, n_tuple = blanc(gold, predicted)
      for i in range(3):
          self.c_tuple[i] += c_tuple[i]
      for i in range(3):
          self.n_tuple[i] += n_tuple[i]
  
imports: import logging
  import numpy
  from collections import Counter, defaultdict
  from scipy.optimize import linear_sum_assignment
  from .blanc import blanc, tuple_to_metric
label_desc: Use image node_id 2 for calling the CorefEvaluator obj's underlying member method code with example usage: obj.update(predicted, gold, mention_to_predicted, mention_to_gold) without return types