code: def macro_f1(items):
      # this is different from f1-score which uses default binary avg
      unzipped_list = list(zip(*items))
      golds = unzipped_list[0]
      preds = unzipped_list[1]
      fscore = sklearn.metrics.f1_score(golds, preds, average="macro")
  
      return fscore
  
imports: import math
  from collections.abc import Iterable
  import numpy
  import sacrebleu
  import sklearn.metrics
  import random
  from collections import defaultdict
label_desc: Use image node_id 9 for calling a global function with example usage: macro_f1(items) and returns: fscore