


import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding







class 				snake_case__(							UpperCAmelCase__							):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__      :  Any					=							["""image_processor""", """tokenizer"""]
						SCREAMING_SNAKE_CASE__      :  List[str]					=							"""CLIPImageProcessor"""
						SCREAMING_SNAKE_CASE__      :  Union[str, Any]					=							("""CLIPTokenizer""", """CLIPTokenizerFast""")




						def __init__(				self   ,						__lowercase=None   ,						__lowercase=None   ,						**__lowercase							)					->    Dict:
										lowerCAmelCase_ :      str    				=				None
										if "feature_extractor" in kwargs:
														warnings.warn(
														    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
														    ''' instead.'''   ,						__lowercase   ,						)
														lowerCAmelCase_ :      str    				=				kwargs.pop('''feature_extractor'''							)

										lowerCAmelCase_ :      str    				=				image_processor if image_processor is not None else feature_extractor
										if image_processor is None:
														raise ValueError('''You need to specify an `image_processor`.'''							)
										if tokenizer is None:
														raise ValueError('''You need to specify a `tokenizer`.'''							)

										super().__init__(__lowercase   ,						__lowercase							)




						def __call__(				self   ,						__lowercase=None   ,						__lowercase=None   ,						__lowercase=None   ,						**__lowercase							)					->    Tuple:

										if text is None and images is None:
														raise ValueError('''You have to specify either text or images. Both cannot be none.'''							)

										if text is not None:
														lowerCAmelCase_ :      List[str]    				=				self.tokenizer(__lowercase   ,						return_tensors=__lowercase   ,						**__lowercase							)

										if images is not None:
														lowerCAmelCase_ :      Any    				=				self.image_processor(__lowercase   ,						return_tensors=__lowercase   ,						**__lowercase							)

										if text is not None and images is not None:
														lowerCAmelCase_ :      List[Any]    				=				image_features.pixel_values
														return encoding
										elif text is not None:
														return encoding
										else:
														return BatchEncoding(data=dict(**__lowercase							)   ,						tensor_type=__lowercase							)




						def 						lowercase_ (				self   ,						*__lowercase   ,						**__lowercase							)					->    str:
										return self.tokenizer.batch_decode(*__lowercase   ,						**__lowercase							)




						def 						lowercase_ (				self   ,						*__lowercase   ,						**__lowercase							)					->    int:
										return self.tokenizer.decode(*__lowercase   ,						**__lowercase							)




						@property
						def 						lowercase_ (				self							)					->    int:
										lowerCAmelCase_ :      List[Any]    				=				self.tokenizer.model_input_names
										lowerCAmelCase_ :      Any    				=				self.image_processor.model_input_names
										return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)




						@property
						def 						lowercase_ (				self							)					->    str:
										warnings.warn(
										    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''   ,						__lowercase   ,						)
										return self.image_processor_class




						@property
						def 						lowercase_ (				self							)					->    str:
										warnings.warn(
										    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''   ,						__lowercase   ,						)
										return self.image_processor



_UpperCAmelCase			:  Dict     =[
    (1000, """M"""),
    (900, """CM"""),
    (500, """D"""),
    (400, """CD"""),
    (100, """C"""),
    (90, """XC"""),
    (50, """L"""),
    (40, """XL"""),
    (10, """X"""),
    (9, """IX"""),
    (5, """V"""),
    (4, """IV"""),
    (1, """I"""),
]



def 			lowerCAmelCase (		lowerCAmelCase_ )-> int:
				lowerCAmelCase_ :      Any    				=				{'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1_000}
				lowerCAmelCase_ :      Optional[int]    				=				0
				lowerCAmelCase_ :      List[str]    				=				0
				while place < len(lowerCAmelCase_ ):
								if (place + 1 < len(lowerCAmelCase_ )) and (vals[roman[place]] < vals[roman[place + 1]]):
												total += vals[roman[place + 1]] - vals[roman[place]]
												place += 2
								else:
												total += vals[roman[place]]
												place += 1
				return total



def 			lowerCAmelCase (		lowerCAmelCase_ )-> str:
				lowerCAmelCase_ :      List[Any]    				=				[]
				for arabic, roman in ROMAN:
								((lowerCAmelCase_)				,  (lowerCAmelCase_)) :      Optional[int]    				=				divmod(lowerCAmelCase_ ,   lowerCAmelCase_ )
								result.append(roman * factor )
								if number == 0:
												break
				return "".join(lowerCAmelCase_ )


if __name__ == "__main__":
						import doctest

						doctest.testmod()