'''simple docstring'''

import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class 				lowercase_     (  _A    ):
    a_   							= ["""image_processor""", """tokenizer"""]
    a_   							= """CLIPImageProcessor"""
    a_   							= ("""CLIPTokenizer""", """CLIPTokenizerFast""")







    def __init__(						self							,  UpperCamelCase__=None							,  UpperCamelCase__=None							,  **UpperCamelCase__					)					->							Tuple:





     """simple docstring"""

     UpperCAmelCase_												=       None
     if "feature_extractor" in kwargs:
      warnings.warn(
          "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
          " instead."							,  _UpperCamelCase							,  )
      UpperCAmelCase_												=       kwargs.pop("feature_extractor"					)

     UpperCAmelCase_												=       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__(_UpperCamelCase							,  _UpperCamelCase					)







    def __call__(						self							,  UpperCamelCase__=None							,  UpperCamelCase__=None							,  UpperCamelCase__=None							,  **UpperCamelCase__					)					->							List[Any]:





     """simple docstring"""

     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:
      UpperCAmelCase_												=       self.tokenizer(_UpperCamelCase							,  return_tensors=_UpperCamelCase							,  **_UpperCamelCase					)

     if images is not None:
      UpperCAmelCase_												=       self.image_processor(_UpperCamelCase							,  return_tensors=_UpperCamelCase							,  **_UpperCamelCase					)

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







    def 	lowerCamelCase_     (						self							,  *UpperCamelCase__							,  **UpperCamelCase__					)					->							Tuple:





     """simple docstring"""

     return self.tokenizer.batch_decode(*_UpperCamelCase							,  **_UpperCamelCase					)







    def 	lowerCamelCase_     (						self							,  *UpperCamelCase__							,  **UpperCamelCase__					)					->							List[str]:





     """simple docstring"""

     return self.tokenizer.decode(*_UpperCamelCase							,  **_UpperCamelCase					)







    @property
    def 	lowerCamelCase_     (						self					)					->							Optional[Any]:





     """simple docstring"""

     UpperCAmelCase_												=       self.tokenizer.model_input_names
     UpperCAmelCase_												=       self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names					)					)







    @property
    def 	lowerCamelCase_     (						self					)					->							str:





     """simple docstring"""

     warnings.warn(
         "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."							,  _UpperCamelCase							,  )
     return self.image_processor_class







    @property
    def 	lowerCamelCase_     (						self					)					->							str:





     """simple docstring"""

     warnings.warn(
         "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."							,  _UpperCamelCase							,  )
     return self.image_processor




'''simple docstring'''
def 					lowerCamelCase_ ( __UpperCamelCase					:       int		)					->	bool:







     """simple docstring"""
     return str(__UpperCamelCase		) == str(__UpperCamelCase		)[::-1]

def 					lowerCamelCase_ ( __UpperCamelCase					:       int		)					->	int:







     """simple docstring"""
     return int(__UpperCamelCase		) + int(str(__UpperCamelCase		)[::-1]		)

def 					lowerCamelCase_ ( __UpperCamelCase					:       int = 1_0_0_0_0		)					->	int:







     """simple docstring"""
     _A				=							[]
     for num in range(1							,    __UpperCamelCase		):
          _A				=							0
          _A				=							num
          while iterations < 5_0:
               _A				=							sum_reverse(__UpperCamelCase		)
               iterations += 1
               if is_palindrome(__UpperCamelCase		):
                    break
          else:
               lychrel_nums.append(__UpperCamelCase		)
     return len(__UpperCamelCase		)


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





