



import warnings

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



class      _UpperCAmelCase      (							A__  ):
     UpperCamelCase__		     =					['''image_processor''', '''tokenizer''']
     UpperCamelCase__		     =					'''ChineseCLIPImageProcessor'''
     UpperCamelCase__		     =					('''BertTokenizer''', '''BertTokenizerFast''')




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

         A__					=       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__(a__			,    a__)
         A__					=       self.image_processor




     def __call__(					self			,    a__=None			,    a__=None			,    a__=None			,    **a__):

         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:
             A__					=       self.tokenizer(a__			,    return_tensors=a__			,    **a__)

         if images is not None:
             A__					=       self.image_processor(a__			,    return_tensors=a__			,    **a__)

         if text is not None and images is not None:
             A__					=       image_features.pixel_values
             return encoding
         elif text is not None:
             return encoding
         else:
             return BatchEncoding(data=dict(**a__)			,    tensor_type=a__)




     def 		snake_case_		(					self			,    *a__			,    **a__):
         return self.tokenizer.batch_decode(*a__			,    **a__)




     def 		snake_case_		(					self			,    *a__			,    **a__):
         return self.tokenizer.decode(*a__			,    **a__)




     @property
     def 		snake_case_		(					self):
         A__					=       self.tokenizer.model_input_names
         A__					=       self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))




     @property
     def 		snake_case_		(					self):
         warnings.warn(
             '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''			,    a__			,    )
         return self.image_processor_class





_lowercase    	=		[0, 2, 4, 6, 8]
_lowercase    	=		[1, 3, 5, 7, 9]



def 		lowerCAmelCase__     (       UpperCamelCase_					:							int			,							UpperCamelCase_					:							int			,							UpperCamelCase_					:							list[int]			,							UpperCamelCase_					:							int						)->	int:
    if remaining_length == 0:
        if digits[0] == 0 or digits[-1] == 0:
            return 0

        for i in range(length // 2 - 1			,							-1			,							-1						):
            remainder += digits[i] + digits[length - i - 1]

            if remainder % 2 == 0:
                return 0

            remainder //= 1_0

        return 1

    if remaining_length == 1:
        if remainder % 2 == 0:
            return 0

        A__					=       0
        for digit in range(1_0						):
            A__					=       digit
            result += reversible_numbers(
                0			,							(remainder + 2 * digit) // 1_0			,							UpperCamelCase_			,							UpperCamelCase_						)
        return result

    A__					=       0
    for digita in range(1_0						):
        A__					=       digita

        if (remainder + digita) % 2 == 0:
            A__					=       ODD_DIGITS
        else:
            A__					=       EVEN_DIGITS

        for digita in other_parity_digits:
            A__					=       digita
            result += reversible_numbers(
                remaining_length - 2			,							(remainder + digita + digita) // 1_0			,							UpperCamelCase_			,							UpperCamelCase_			,							)
    return result



def 		lowerCAmelCase__     (       UpperCamelCase_					:							int = 9						)->	int:
    A__					=       0
    for length in range(1			,							max_power + 1						):
        result += reversible_numbers(UpperCamelCase_			,							0			,							[0] * length			,							UpperCamelCase_						)
    return result


if __name__ == "__main__":
   print(F"{solution() = }")
