docstr: Performs regex logic for string cleansing and attaches start and end tokens to the text. 
docstr_tok: ["Performs","regex","logic","for","string","cleansing","and","attaches","start","and","end","tokens","to","the","text","."]
code: def __call__(self, data: Tuple[str, str]) -> Tuple[str, str]:
      """Performs regex logic for string cleansing and attaches start and end tokens to the text."""
      text_encoder, text_decoder = self._normalize_string(
          data[0]
      ), self._normalize_string(data[1])
      if self.add_input_start_end:
          text_encoder = (
              self.start_token
              + " "
              + text_encoder
              + " "
              + self.end_token
          )
      text_decoder = (
          self.start_token + " " + text_decoder + " " + self.end_token
      )
      return text_encoder, text_decoder
  
imports: import re
  from typing import Tuple
label_desc: Use image node_id 2 for calling the Preprocessor obj's underlying member method code with example usage: obj.__call__(data) and returns: text_encoder,  text_decoder