class_docstr: Construct a BaiChuan tokenizer. Based on byte-level Byte-Pair-Encoding.
  
  Args:
      vocab_file (`str`):
          Path to the vocabulary file.
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docstr: Creates a mask from the two sequences passed to
  be used in a sequence-pair classification task. An ALBERT
  sequence pair mask has the following format:
  
  ```
  0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1
  | first sequence    | second sequence |
  ```
  
  if token_ids_1 is None, only returns the first portion of the mask (0s).
  
  Args:
      token_ids_0 (`List[int]`):
          List of ids.
      token_ids_1 (`List[int]`, *optional*):
          Optional second list of IDs for sequence pairs.
  
  Returns:
      `List[int]`: List of [token type IDs](../glossary#token-type-ids)
       according to the given sequence(s).
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code: def create_token_type_ids_from_sequences(
      self,
      token_ids_0: List[int],
      token_ids_1: Optional[List[int]] = None,
  ) -> List[int]:
      """
      Creates a mask from the two sequences passed to
      be used in a sequence-pair classification task. An ALBERT
      sequence pair mask has the following format:
  
      ```
      0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1
      | first sequence    | second sequence |
      ```
  
      if token_ids_1 is None, only returns the first portion of the mask (0s).
  
      Args:
          token_ids_0 (`List[int]`):
              List of ids.
          token_ids_1 (`List[int]`, *optional*):
              Optional second list of IDs for sequence pairs.
  
      Returns:
          `List[int]`: List of [token type IDs](../glossary#token-type-ids)
           according to the given sequence(s).
      """
      bos_token_id = [self.bos_token_id] if self.add_bos_token else []
      eos_token_id = [self.eos_token_id] if self.add_eos_token else []
  
      output = [0] * len(bos_token_id + token_ids_0 + eos_token_id)
  
      if token_ids_1 is not None:
          output += [1] * len(bos_token_id + token_ids_1 + eos_token_id)
  
      return output
  
imports: import os
  from shutil import copyfile
  from typing import Any, Dict, List, Optional, Tuple
  import sentencepiece
  from transformers.tokenization_utils import AddedToken, PreTrainedTokenizer
  from transformers.utils import logging
label_desc: Use image node_id 13 for calling the BaiChuanTokenizer obj's underlying member method code with example usage: obj.create_token_type_ids_from_sequences(token_ids_0, token_ids_1) and returns: output