code: 
  
  
  
  
  
  
  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
  
  
  SCREAMING_SNAKE_CASE__		:       str   							=							logging.get_logger(__name__)
  
  SCREAMING_SNAKE_CASE__		:       str   							=							{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}
  
  SCREAMING_SNAKE_CASE__		:       Union[str, Any]   							=							{
      """vocab_file""": {
          """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json""",
      },
      """merges_file""": {
          """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt""",
      },
      """tokenizer_file""": {
          """openai/clip-vit-base-patch32""": (
              """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json"""
          ),
      },
  }
  
  SCREAMING_SNAKE_CASE__		:       Optional[int]   							=							{
      """openai/clip-vit-base-patch32""": 77,
  }
  
  
  
  
  
  
  
  class 							UpperCAmelCase_     (		__lowerCamelCase		):
       __lowerCamelCase										=     VOCAB_FILES_NAMES
       __lowerCamelCase										=     PRETRAINED_VOCAB_FILES_MAP
       __lowerCamelCase										=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __lowerCamelCase										=     ['input_ids', 'attention_mask']
       __lowerCamelCase										=     CLIPTokenizer
  
  
  
  
       def __init__(							self  ,	_lowerCAmelCase=None  ,	_lowerCAmelCase=None  ,	_lowerCAmelCase=None  ,	_lowerCAmelCase="<|endoftext|>"  ,	_lowerCAmelCase="<|startoftext|>"  ,	_lowerCAmelCase="<|endoftext|>"  ,	_lowerCAmelCase="<|endoftext|>"  ,	**_lowerCAmelCase  ,	):
            super().__init__(
                _lowerCAmelCase  ,	_lowerCAmelCase  ,	tokenizer_file=_lowerCAmelCase  ,	unk_token=_lowerCAmelCase  ,	bos_token=_lowerCAmelCase  ,	eos_token=_lowerCAmelCase  ,	pad_token=_lowerCAmelCase  ,	**_lowerCAmelCase  ,	)
  
            if not isinstance(self.backend_tokenizer.pre_tokenizer  ,	pre_tokenizers.Sequence		):
                 raise ValueError(
                     """The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"""
                     """ heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"""
                     """ to be compatible with this version.The easiest way to do so is"""
                     """ `CLIPTokenizerFast.from_pretrained(\"path_to_local_folder_or_hub_repo, from_slow=True)`. If you want"""
                     """ to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"""
                     """ transformers."""		)
  
            self._wrap_decode_method_backend_tokenizer()
  
  
  
  
       def      __UpperCAmelCase     (							self		):
            UpperCAmelCase__			:     List[str]										= self.backend_tokenizer.decode
  
            def new_decode_method(*_lowerCAmelCase  ,	**_lowerCAmelCase		):
                 UpperCAmelCase__			:     Tuple										= orig_decode_method(*_lowerCAmelCase  ,	**_lowerCAmelCase		)
                 UpperCAmelCase__			:     int										= text.replace(self.backend_tokenizer.model.end_of_word_suffix  ,	""" """		).strip()
                 return text
  
            UpperCAmelCase__			:     Optional[int]										= new_decode_method
  
  
  
  
       def      __UpperCAmelCase     (							self  ,	_lowerCAmelCase  ,	_lowerCAmelCase = None		):
            UpperCAmelCase__			:     List[str]										= [self.bos_token_id]
            UpperCAmelCase__			:     List[str]										= [self.eos_token_id]
  
            if token_ids_a is None:
                 return bos_token + token_ids_a + eos_token
            return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token
  
  
  
  
       def      __UpperCAmelCase     (							self  ,	_lowerCAmelCase  ,	_lowerCAmelCase = None		):
            UpperCAmelCase__			:     Optional[Any]										= [self.bos_token_id]
            UpperCAmelCase__			:     int										= [self.eos_token_id]
  
            if token_ids_a is None:
                 return len(bos_token + token_ids_a + eos_token		) * [0]
            return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token		) * [0]
  
  
  
  
       def      __UpperCAmelCase     (							self  ,	_lowerCAmelCase  ,	_lowerCAmelCase = None		):
            UpperCAmelCase__			:     Any										= self._tokenizer.model.save(_lowerCAmelCase  ,	name=_lowerCAmelCase		)
            return tuple(_lowerCAmelCase		)
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  import warnings
  
  from ...utils import logging
  from .image_processing_vilt import ViltImageProcessor
  
  
  SCREAMING_SNAKE_CASE__		:       Optional[int]   							=							logging.get_logger(__name__)
  
  
  
  
  
  
  
  class 							UpperCAmelCase_     (		__lowerCamelCase		):
  
  
  
  
       def __init__(							self  ,	*_lowerCAmelCase  ,	**_lowerCAmelCase		):
            warnings.warn(
                """The class ViltFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
                """ use ViltImageProcessor instead."""  ,	_lowerCAmelCase  ,	)
            super().__init__(*_lowerCAmelCase  ,	**_lowerCAmelCase		)
  
  
  
  
  
  
  