code: def normalize(
      sentence,
      lowercase: bool = True,
      tokenizer: str = "13a",
      return_str: bool = True,
  ):
      # Normalization is requried for the ASSET dataset (one of the primary
      # datasets in sentence simplification) to allow using space
      # to split the sentence. Even though Wiki-Auto and TURK datasets,
      # do not require normalization, we do it for consistency.
      # Code adapted from the EASSE library [1] written by the authors of the ASSET dataset.
      # [1] https://github.com/feralvam/easse/blob/580bba7e1378fc8289c663f864e0487188fe8067/easse/utils/preprocessing.py#L7
  
      if lowercase:
          sentence = sentence.lower()
  
      if tokenizer in ["13a", "intl"]:
          if version.parse(sacrebleu.__version__).major >= 2:
              normalized_sent = sacrebleu.metrics.bleu._get_tokenizer(
                  tokenizer
              )()(sentence)
          else:
              normalized_sent = sacrebleu.TOKENIZERS[tokenizer]()(
                  sentence
              )
      elif tokenizer == "moses":
          normalized_sent = sacremoses.MosesTokenizer().tokenize(
              sentence, return_str=True, escape=False
          )
      elif tokenizer == "penn":
          normalized_sent = sacremoses.MosesTokenizer().penn_tokenize(
              sentence, return_str=True
          )
      else:
          normalized_sent = sentence
  
      if not return_str:
          normalized_sent = normalized_sent.split()
  
      return normalized_sent
  
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 6 for calling a global function with example usage: normalize(sentence, lowercase, tokenizer, return_str) and returns: normalized_sent