class_docstr: Normalize source and target based on Moses script.
class_docstr_tok: ["Normalize","source","and","target","based","on","Moses","script","."]
docstr: Set options for each dataset.
docstr_tok: ["Set","options","for","each","dataset","."]
code: def warm_up(self, vocabs=None):
      """Set options for each dataset."""
      super().warm_up(None)
      self.src_lang_dict = self.get_opt_dict(self.opts, "src_lang", "")
      self.tgt_lang_dict = self.get_opt_dict(self.opts, "tgt_lang", "")
      self.penn_dict = self.get_opt_dict(self.opts, "penn", True)
      self.norm_quote_commas_dict = self.get_opt_dict(
          self.opts, "norm_quote_commas", True
      )
      self.norm_numbers_dict = self.get_opt_dict(
          self.opts, "norm_numbers", True
      )
      self.pre_dict = self.get_opt_dict(
          self.opts, "pre_replace_unicode_punct", False
      )
      self.post_dict = self.get_opt_dict(
          self.opts, "post_remove_control_chars", False
      )
      self.src_lang_dict["infer"] = self.src_lang
      self.tgt_lang_dict["infer"] = self.tgt_lang
      self.penn_dict["infer"] = self.penn
      self.norm_quote_commas_dict["infer"] = self.norm_quote_commas
      self.norm_numbers_dict["infer"] = self.norm_numbers
      self.pre_dict["infer"] = self.pre_replace_unicode_punct
      self.post_dict["infer"] = self.post_remove_control_chars
  
      self.mpn = MosesPunctNormalizer()
  
imports: from onmt.utils.logging import logger
  import re
  import regex
  from itertools import chain
  from onmt.transforms import register_transform
  from .transform import Transform
label_desc: Use image node_id 6 for calling the NormalizeTransform obj's underlying member method code with example usage: obj.warm_up(vocabs) without return types