class_docstr: A Base class that every transform method should derived from.
class_docstr_tok: ["A","Base","class","that","every","transform","method","should","derived","from","."]
docstr: Procedure needed after initialize and before apply.
  
  This should be override if there exist any procedure necessary
  before `apply`, like setups based on parsed options or load models,
  etc.
docstr_tok: ["Procedure","needed","after","initialize","and","before","apply",".","This","should","be","override","if","there","exist","any","procedure","necessary","before","`","apply","`",",","like","setups","based","on","parsed","options","or","load","models",",","etc","."]
code: def warm_up(self, vocabs=None):
      """Procedure needed after initialize and before apply.
  
      This should be override if there exist any procedure necessary
      before `apply`, like setups based on parsed options or load models,
      etc.
      """
      if self.opts.seed > 0:
          self._set_seed(self.opts.seed)
      if self.require_vocab():
          if vocabs is None:
              raise ValueError(
                  f"{type(self).__name__} requires vocabs!"
              )
          self.vocabs = vocabs
  
imports: import torch
  from onmt.utils.logging import logger
  from onmt.utils.misc import check_path
label_desc: Use image node_id 4 for calling the Transform obj's underlying member method code with example usage: obj.warm_up(vocabs) without return types