
'''simple docstring'''
import warnings

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







class  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       =['''image_processor''', '''tokenizer''']
 lowerCamelCase				       ='''CLIPImageProcessor'''
 lowerCamelCase				       =('''XLMRobertaTokenizer''', '''XLMRobertaTokenizerFast''')
 def __init__(   self			:    List[str]				,   lowerCamelCase			:    Union[str, Any]=None				,   lowerCamelCase			:    List[Any]=None				,   **lowerCamelCase			:    Optional[Any]       ):



   """simple docstring"""





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

   __A		:     List[Any]												=		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__(lowerCamelCase				,   lowerCamelCase       )
 def __call__(   self			:    List[str]				,   lowerCamelCase			:    Optional[Any]=None				,   lowerCamelCase			:    Optional[int]=None				,   lowerCamelCase			:    Union[str, Any]=None				,   **lowerCamelCase			:    Union[str, 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:
     __A		:     Optional[int]												=		self.tokenizer(lowerCamelCase				,   return_tensors=lowerCamelCase				,   **lowerCamelCase       )

   if images is not None:
     __A		:     List[str]												=		self.image_processor(lowerCamelCase				,   return_tensors=lowerCamelCase				,   **lowerCamelCase       )

   if text is not None and images is not None:
     __A		:     List[Any]												=		image_features.pixel_values
     return encoding
   elif text is not None:
     return encoding
   else:
     return BatchEncoding(data=dict(**lowerCamelCase       )				,   tensor_type=lowerCamelCase       )
 def 		lowercase_(   self			:    Dict				,   *lowerCamelCase			:    Union[str, Any]				,   **lowerCamelCase			:    Any       ):



   """simple docstring"""





   return self.tokenizer.batch_decode(*lowerCamelCase				,   **lowerCamelCase       )
 def 		lowercase_(   self			:    List[str]				,   *lowerCamelCase			:    Optional[int]				,   **lowerCamelCase			:    Any       ):



   """simple docstring"""





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






 @property
 def 		lowercase_(   self			:    int       ):



   """simple docstring"""





   __A		:     Tuple												=		self.tokenizer.model_input_names
   __A		:     Tuple												=		self.image_processor.model_input_names
   return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names       )       )





'''simple docstring'''
def        A_     (						__SCREAMING_SNAKE_CASE						:  int )				->       int:





  """simple docstring"""

  __A		:     Optional[int]												=		1
  for i in range(1			,     num + 1 ):
    fact *= i
  return fact







def        A_     (						__SCREAMING_SNAKE_CASE						:  int )				->       int:





  """simple docstring"""

  __A		:     List[str]												=		0
  while number > 0:
    __A		:     Union[str, Any]												=		number % 10
    sum_of_digits += last_digit
    __A		:     int												=		number // 10  # Removing the last_digit from the given number
  return sum_of_digits







def        A_     (						__SCREAMING_SNAKE_CASE						:  int = 100 )				->       int:





  """simple docstring"""

  __A		:     Union[str, Any]												=		factorial(__SCREAMING_SNAKE_CASE )
  __A		:     Any												=		split_and_add(__SCREAMING_SNAKE_CASE )
  return result


if __name__ == "__main__":
     print(solution(int(input('Enter the Number: ').strip())))



