code: def _match_numbers_if_present(self, gold_bag, predicted_bag):
      gold_numbers = set()
      predicted_numbers = set()
      for word in gold_bag:
          if self._is_number(word):
              gold_numbers.add(word)
      for word in predicted_bag:
          if self._is_number(word):
              predicted_numbers.add(word)
      if (not gold_numbers) or gold_numbers.intersection(
          predicted_numbers
      ):
          return True
      return False
  
imports: import inspect
  import numpy
  import re
  import string
  import lm_eval.datasets.drop.drop
  from scipy.optimize import linear_sum_assignment
  from lm_eval.base import Task, rf
  from lm_eval.metrics import mean
label_desc: Use image node_id 19 for calling the DROP obj's underlying member method code with example usage: obj._match_numbers_if_present(gold_bag, predicted_bag) and returns: False, True