code: def _get_tokens(s: str) -> List[str]:
      """Split a sentence into separate tokens."""
      return [] if not s else _normalize_text(s).split()
  
file_path: torchmetrics/src/torchmetrics/functional/text/squad.py
imports: import re
  import string
  from collections import Counter
  from typing import Any, Callable, Dict, List, Tuple, Union
  from torch import Tensor, tensor
  from torchmetrics.utilities import rank_zero_warn
label_desc: Use image node_id 2 for calling a global function with example usage: _get_tokens(s) and returns: unknown