class_docstr: Construct a "fast" CLIP tokenizer (backed by HuggingFace's *tokenizers* library). Based on byte-level
  Byte-Pair-Encoding.
  
  This tokenizer inherits from [`PreTrainedTokenizerFast`] which contains most of the main methods. Users should
  refer to this superclass for more information regarding those methods.
  
  Args:
      vocab_file (`str`):
          Path to the vocabulary file.
      merges_file (`str`):
          Path to the merges file.
      unk_token (`str`, *optional*, defaults to `<|endoftext|>`):
          The unknown token. A token that is not in the vocabulary cannot be converted to an ID and is set to be this
          token instead.
      bos_token (`str`, *optional*, defaults to `<|endoftext|>`):
          The beginning of sequence token.
      eos_token (`str`, *optional*, defaults to `<|endoftext|>`):
          The end of sequence token.
docstr: Create a mask from the two sequences passed. CLIP does not make use of token type ids, therefore a list of
  zeros is returned.
  
  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 zeros.
code: def create_token_type_ids_from_sequences(
      self,
      token_ids_0: List[int],
      token_ids_1: Optional[List[int]] = None,
  ) -> List[int]:
      """
      Create a mask from the two sequences passed. CLIP does not make use of token type ids, therefore a list of
      zeros is returned.
  
      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 zeros.
      """
      bos_token = [self.bos_token_id]
      eos_token = [self.eos_token_id]
  
      if token_ids_1 is None:
          return len(bos_token + token_ids_0 + eos_token) * [0]
      return len(
          bos_token
          + token_ids_0
          + eos_token
          + eos_token
          + token_ids_1
          + eos_token
      ) * [0]
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/clip/tokenization_clip_fast.py
imports: from typing import List, Optional, Tuple
  from tokenizers import pre_tokenizers
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_clip import CLIPTokenizer
label_desc: Use image node_id 4 for calling the CLIPTokenizerFast obj's underlying member method code with example usage: obj.create_token_type_ids_from_sequences(token_ids_0, token_ids_1) and returns: unknown, unknown