code: def compute_sari(sources, predictions, references):
      if not (len(sources) == len(predictions) == len(references)):
          raise ValueError(
              "Sources length must match predictions and references lengths."
          )
      sari_score = 0
      for src, pred, refs in zip(sources, predictions, references):
          sari_score += SARIsent(
              normalize(src),
              normalize(pred),
              [normalize(sent) for sent in refs],
          )
      sari_score = sari_score / len(predictions)
      return 100 * sari_score
  
file_path: evaluate/metrics/wiki_split/wiki_split.py
imports: import re
  import string
  from collections import Counter
  import datasets
  import sacrebleu
  import sacremoses
  from packaging import version
  import evaluate
label_desc: Use image node_id 7 for calling a global function with example usage: compute_sari(sources, predictions, references) and returns: unknown