class_docstr: Clean examples according to rules
code: def warm_up(self, vocabs=None):
      super().warm_up(None)
      self.src_eq_tgt_dict = self.get_opt_dict(
          self.opts, "src_eq_tgt", True
      )
      self.same_char_dict = self.get_opt_dict(
          self.opts, "same_char", True
      )
      self.same_word_dict = self.get_opt_dict(
          self.opts, "same_word", True
      )
      self.scripts_ok_dict = self.get_opt_dict(
          self.opts, "scripts_ok", ["Latin", "Common"]
      )
      self.scripts_nok_dict = self.get_opt_dict(
          self.opts, "scripts_nok", []
      )
      self.src_tgt_ratio_dict = self.get_opt_dict(
          self.opts, "src_tgt_ratio", 2
      )
      self.avg_tok_min_dict = self.get_opt_dict(
          self.opts, "avg_tok_min", 3
      )
      self.avg_tok_max_dict = self.get_opt_dict(
          self.opts, "avg_tok_max", 20
      )
      self.langid_dict = self.get_opt_dict(self.opts, "langid", [])
      fasttext_loc = (
          f"{os.path.dirname(os.path.abspath(__file__))}/lid.176.ftz"
      )
  
      if not os.path.exists(fasttext_loc):
          urllib.request.urlretrieve(
              "https://dl.fbaipublicfiles.com/"
              + "fasttext/supervised-models/lid.176.ftz",
              fasttext_loc,
          )
      self.id_func = fasttext.load_model(fasttext_loc)
  
file_path: OpenNMT-py/onmt/transforms/clean.py
imports: from onmt.transforms import register_transform
  from .transform import Transform
  from onmt.utils.logging import logger
  import fasttext
  import os
  import urllib.request
  import regex
label_desc: Use image node_id 6 for calling the CleanTransform obj's underlying member method code with example usage: obj.warm_up(vocabs) without return types