class_docstr: Tokenizer transform abstract class.
code: def _parse_opts(self):
      self.share_vocab = self.opts.share_vocab
      self.src_subword_model = self.opts.src_subword_model
      self.tgt_subword_model = self.opts.tgt_subword_model
      self.src_subword_nbest = self.opts.src_subword_nbest
      self.tgt_subword_nbest = self.opts.tgt_subword_nbest
      self.src_subword_alpha = self.opts.src_subword_alpha
      self.tgt_subword_alpha = self.opts.tgt_subword_alpha
      self.src_subword_vocab = self.opts.src_subword_vocab
      self.tgt_subword_vocab = self.opts.tgt_subword_vocab
      self.src_vocab_threshold = self.opts.src_vocab_threshold
      self.tgt_vocab_threshold = self.opts.tgt_vocab_threshold
  
imports: import re
  from onmt.utils.logging import logger
  from onmt.transforms import register_transform
  from .transform import Transform, ObservableStats
  from onmt.constants import DefaultTokens
label_desc: Use image node_id 4 for calling the TokenizerTransform obj's underlying member method code with example usage: obj._parse_opts() without return types