class_docstr: The `UserNormalizer` class is required to tokenize a non-alphabet language text input.
  
  The user's defined tokenizer is expected to return ``Sequence[str]`` that are fed into the rouge score.
docstr: Call method to tokenize user input.
  
  The `__call__` method must be defined for this class. To ensure the functionality, the `__call__` method
  should obey the input/output arguments structure described below.
  
  Args:
      text: Input text.
  
  Return:
      Tokenized sentence
code: def __call__(self, text: str) -> Sequence[str]:
      """Call method to tokenize user input.
  
      The `__call__` method must be defined for this class. To ensure the functionality, the `__call__` method
      should obey the input/output arguments structure described below.
  
      Args:
          text: Input text.
  
      Return:
          Tokenized sentence
  
      """
      return re.split(self.pattern, text)
  
file_path: torchmetrics/examples/rouge_score-own_normalizer_and_tokenizer.py
imports: import re
  from pprint import pprint
  from typing import Sequence
  from torchmetrics.text.rouge import ROUGEScore
label_desc: Use image node_id 1 for calling the UserTokenizer obj's underlying member method code with example usage: obj.__call__(text) and returns: re