class_docstr: Sentencepiecetokenizer https://github.com/google/sentencepiece.
  
      Args:
      model_path: path to sentence piece tokenizer model. To create the model use create_spt_model()
      special_tokens: either list of special tokens or dictionary of token name to token value
      legacy: when set to True, the previous behavior of the SentecePiece wrapper will be restored,
          including the possibility to add special tokens inside wrapper.
class_docstr_tok: ["Sentencepiecetokenizer","https",":","\/\/github.com\/google\/sentencepiece",".","Args",":","model_path",":","path","to","sentence","piece","tokenizer","model",".","To","create","the","model","use","create_spt_model","(",")","special_tokens",":","either","list","of","special","tokens","or","dictionary","of","token","name","to","token","value","legacy",":","when","set","to","True",",","the","previous","behavior","of","the","SentecePiece","wrapper","will","be","restored",",","including","the","possibility","to","add","special","tokens","inside","wrapper","."]
code: def vocab(self):
      main_vocab = [
          self.tokenizer.id_to_piece(id)
          for id in range(self.tokenizer.get_piece_size())
      ]
      special_tokens = [
          self.id_to_special_token[self.original_vocab_size + i]
          for i in range(self.vocab_size - self.original_vocab_size)
      ]
      return main_vocab + special_tokens
  
imports: import os
  from typing import Dict, List, Optional, Union
  import numpy
  import sentencepiece
  from nemo.collections.common.parts.utils import if_exist
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.utils import logging
label_desc: Use image node_id 18 for calling the SentencePieceTokenizer obj's underlying member method code with example usage: obj.vocab() and returns: unknown