






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		)














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		)






