code: def bucc_optimize(candidate2score, gold):
      # Adapted From: https://github.com/google-research/xtreme/blob/
      #               522434d1aece34131d997a97ce7e9242a51a688a/third_party/utils_retrieve.py
      items = sorted(candidate2score.items(), key=lambda x: -x[1])
      ngold = len(gold)
      nextract = ncorrect = 0
      threshold = 0
      best_f1 = 0
      for i in range(len(items)):
          nextract += 1
          if items[i][0] in gold:
              ncorrect += 1
          if ncorrect > 0:
              precision = ncorrect / nextract
              recall = ncorrect / ngold
              f1 = 2 * precision * recall / (precision + recall)
              if f1 > best_f1:
                  best_f1 = f1
                  threshold = (items[i][1] + items[i + 1][1]) / 2
      return threshold
  
imports: import hashlib
  import numpy
  import torch
  from dataclasses import dataclass
  from typing import List
  from jiant.tasks.core import BaseExample, BaseTokenizedExample, BaseDataRow, BatchMixin, Task, TaskTypes
  from jiant.tasks.lib.templates.shared import construct_single_input_tokens_and_segment_ids, create_input_set_from_tokens_and_segments
  from jiant.utils.python.io import read_file, read_file_lines
label_desc: Use image node_id 3 for calling a global function with example usage: bucc_optimize(candidate2score, gold) and returns: threshold