class_docstr: Construct a "fast" BlenderbotSmall tokenizer (backed by HuggingFace's *tokenizers* library).
  
  Args:
      vocab_file (`str`):
          Path to the vocabulary file.
class_docstr_tok: ["Construct","a","``","fast","''","BlenderbotSmall","tokenizer","(","backed","by","HuggingFace","'s","*","tokenizers","*","library",")",".","Args",":","vocab_file","(","`","str","`",")",":","Path","to","the","vocabulary","file","."]
code: def build_inputs_with_special_tokens(
      self, token_ids_0, token_ids_1=None
  ):
      output = [self.bos_token_id] + token_ids_0 + [self.eos_token_id]
      if token_ids_1 is None:
          return output
  
      return (
          output
          + [self.eos_token_id]
          + token_ids_1
          + [self.eos_token_id]
      )
  
file_path: transformers/src/transformers/models/blenderbot_small/tokenization_blenderbot_small_fast.py
imports: from typing import List, Optional
  from tokenizers import ByteLevelBPETokenizer
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
label_desc: Use image node_id 2 for calling the BlenderbotSmallTokenizerFast obj's underlying member method code with example usage: obj.build_inputs_with_special_tokens(token_ids_0, token_ids_1) and returns: unknown, output