code: def _split_sentence(x: str) -> Sequence[str]:
      """Split sentence to get rougeLsum scores matching published rougeL scores for BART and PEGASUS."""
      if not _NLTK_AVAILABLE:
          raise ModuleNotFoundError(
              "ROUGE-Lsum calculation requires that `nltk` is installed. Use `pip install nltk`."
          )
      import nltk
  
      _ensure_nltk_punkt_is_downloaded()
  
      re.sub("<n>", "", x)  # remove pegasus newline char
      return nltk.sent_tokenize(x)
  
file_path: torchmetrics/src/torchmetrics/functional/text/rouge.py
imports: import re
  from collections import Counter
  from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
  import torch
  from torch import Tensor, tensor
  from typing_extensions import Literal
  from torchmetrics.utilities.imports import _NLTK_AVAILABLE
label_desc: Use image node_id 2 for calling a global function with example usage: _split_sentence(x) and returns: nltk