code: from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding
  
  
  
  
  class    __lowerCAmelCase  (       a_						):
  
  
  
   '''simple docstring'''
   _lowerCamelCase						:	Any				    = ['image_processor', 'tokenizer']
   _lowerCamelCase						:	int				    = 'EfficientNetImageProcessor'
   _lowerCamelCase						:	int				    = ('BertTokenizer', 'BertTokenizerFast')
  
   def __init__(			self       :		Optional[Any]       ,			lowerCamelCase       :		str       ,			lowerCamelCase       :		Tuple  ) ->							Tuple:
          super().__init__(lowerCamelCase       ,			lowerCamelCase  )
  
   def __call__(			self       :		Optional[Any]       ,			lowerCamelCase       :		Tuple=None       ,			lowerCamelCase       :		Dict=None       ,			lowerCamelCase       :		int="max_length"       ,			lowerCamelCase       :		List[str]=6_4       ,			lowerCamelCase       :		str=None       ,			**lowerCamelCase       :		Tuple  ) ->							List[Any]:
          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     :       int  						=  self.tokenizer(
                     lowerCamelCase       ,			padding=lowerCamelCase       ,			max_length=lowerCamelCase       ,			return_tensors=lowerCamelCase       ,			**lowerCamelCase  )
  
          if images is not None:
                 _UpperCamelCase     :       Union[str, Any]  						=  self.image_processor(lowerCamelCase       ,			return_tensors=lowerCamelCase       ,			**lowerCamelCase  )
  
          if text is not None and images is not None:
                 _UpperCamelCase     :       Dict  						=  image_features.pixel_values
                 return encoding
          elif text is not None:
                 return encoding
          else:
                 return BatchEncoding(data=dict(**lowerCamelCase  )       ,			tensor_type=lowerCamelCase  )
  
   def 					__snake_case					(			self       :		Tuple       ,			*lowerCamelCase       :		Dict       ,			**lowerCamelCase       :		Optional[Any]  ) ->							List[str]:
          return self.tokenizer.batch_decode(*lowerCamelCase       ,			**lowerCamelCase  )
  
   def 					__snake_case					(			self       :		Tuple       ,			*lowerCamelCase       :		int       ,			**lowerCamelCase       :		int  ) ->							Any:
          return self.tokenizer.decode(*lowerCamelCase       ,			**lowerCamelCase  )
  
   @property
   def 					__snake_case					(			self       :		Optional[Any]  ) ->							Optional[Any]:
          _UpperCamelCase     :       Optional[int]  						=  self.tokenizer.model_input_names
          _UpperCamelCase     :       str  						=  self.image_processor.model_input_names
          return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names  )  )
  
  
  
  
style_context: UpperCAmelCase					=				[chr(i) for i in range(32, 1_26)]
  UpperCAmelCase					=				list(range(len(alphabets)))
  UpperCAmelCase					=				list(range(len(alphabets)))
  UpperCAmelCase					=				list(range(len(alphabets)))
  UpperCAmelCase					=				list(reversed(range(len(alphabets))))
  UpperCAmelCase					=				[]
  UpperCAmelCase					=				UpperCAmelCase					=				UpperCAmelCase					=				0
  
  
  def SCREAMING_SNAKE_CASE				(     ):
         global gear_one_pos
         global gear_two_pos
         global gear_three_pos
         _UpperCamelCase     :       Any  						=  gear_one[0]
         gear_one.append(lowercase_				)
         del gear_one[0]
         gear_one_pos += 1
         if gear_one_pos % int(len(lowercase_				)				) == 0:
                _UpperCamelCase     :       str  						=  gear_two[0]
                gear_two.append(lowercase_				)
                del gear_two[0]
                gear_two_pos += 1
                if gear_two_pos % int(len(lowercase_				)				) == 0:
                       _UpperCamelCase     :       int  						=  gear_three[0]
                       gear_three.append(lowercase_				)
                       del gear_three[0]
                       gear_three_pos += 1
  
  
  def SCREAMING_SNAKE_CASE				(     lowercase_:	List[Any]				):
         _UpperCamelCase     :       Dict  						=  alphabets.index(lowercase_				)
         _UpperCamelCase     :       Union[str, Any]  						=  gear_one[target]
         _UpperCamelCase     :       Any  						=  gear_two[target]
         _UpperCamelCase     :       Tuple  						=  gear_three[target]
         _UpperCamelCase     :       Tuple  						=  reflector[target]
         _UpperCamelCase     :       Any  						=  gear_three.index(lowercase_				)
         _UpperCamelCase     :       Any  						=  gear_two.index(lowercase_				)
         _UpperCamelCase     :       str  						=  gear_one.index(lowercase_				)
         code.append(alphabets[target]				)
         rotator()
  
  
  if __name__ == "__main__":
   UpperCAmelCase					=				list(input('''Type your message:\n'''))
   while True:
    try:
     UpperCAmelCase					=				int(input('''Please set token:(must be only digits)\n'''))
     break
    except Exception as error:
     print(error)
   for _ in range(token):
    rotator()
   for j in decode:
    engine(j)
   print('''\n''' + ''''''.join(code))
   print(
       f'''\nYour Token is {token} please write it down.\nIf you want to decode '''
       '''this message again you should input same digits as token!'''
   )
  
  
  
  