



'''simple docstring'''







import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin




class 				__lowerCAmelCase(							lowerCAmelCase__      ):
			__snake_case  :		List[str]		=      ['image_processor', 'tokenizer']
			__snake_case  :		Tuple		=      'AutoImageProcessor'
			__snake_case  :		str		=      'AutoTokenizer'






			def __init__(   self  :							List[str]      ,       SCREAMING_SNAKE_CASE  :							Optional[Any]=None      ,       SCREAMING_SNAKE_CASE  :							List[str]=None      ,       **SCREAMING_SNAKE_CASE  :							str	):




					"""simple docstring"""







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

					SCREAMING_SNAKE_CASE_						:Optional[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__(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:Tuple										=      self.image_processor
					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      False






			def __call__(   self  :							Optional[Any]      ,       *SCREAMING_SNAKE_CASE  :							Union[str, Any]      ,       **SCREAMING_SNAKE_CASE  :							Tuple	):




					"""simple docstring"""







					if self._in_target_context_manager:
							return self.current_processor(*SCREAMING_SNAKE_CASE      ,       **SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:str										=      kwargs.pop('images'      ,       SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:str										=      kwargs.pop('text'      ,       SCREAMING_SNAKE_CASE	)
					if len(SCREAMING_SNAKE_CASE	) > 0:
							SCREAMING_SNAKE_CASE_						:Optional[Any]										=      args[0]
							SCREAMING_SNAKE_CASE_						:Optional[int]										=      args[1:]

					if images is None and text is None:
							raise ValueError('You need to specify either an `images` or `text` input to process.'	)

					if images is not None:
							SCREAMING_SNAKE_CASE_						:Tuple										=      self.image_processor(SCREAMING_SNAKE_CASE      ,       *SCREAMING_SNAKE_CASE      ,       **SCREAMING_SNAKE_CASE	)
					if text is not None:
							SCREAMING_SNAKE_CASE_						:int										=      self.tokenizer(SCREAMING_SNAKE_CASE      ,       **SCREAMING_SNAKE_CASE	)

					if text is None:
							return inputs
					elif images is None:
							return encodings
					else:
							SCREAMING_SNAKE_CASE_						:int										=      encodings['input_ids']
							return inputs






			def 				_lowercase	(   self  :							Dict      ,       *SCREAMING_SNAKE_CASE  :							Dict      ,       **SCREAMING_SNAKE_CASE  :							Any	):




					"""simple docstring"""







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






			def 				_lowercase	(   self  :							Optional[Any]      ,       *SCREAMING_SNAKE_CASE  :							str      ,       **SCREAMING_SNAKE_CASE  :							Optional[int]	):




					"""simple docstring"""







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






			@contextmanager
			def 				_lowercase	(   self  :							Optional[Any]	):




					"""simple docstring"""







					warnings.warn(
					    '`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '
					    'labels by using the argument `text` of the regular `__call__` method (either in the same call as '
					    'your images inputs, or in a separate call.'	)
					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      True
					SCREAMING_SNAKE_CASE_						:str										=      self.tokenizer
					yield
					SCREAMING_SNAKE_CASE_						:int										=      self.image_processor
					SCREAMING_SNAKE_CASE_						:int										=      False






			@property
			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







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






			@property
			def 				_lowercase	(   self  :							Dict	):




					"""simple docstring"""







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






from __future__ import annotations





def 							lowerCamelCase    (							UpperCAmelCase_	:      str   ,       UpperCAmelCase_	:      dict[str, str]      )->			str:

       """simple docstring"""




       a   ,      a   ,      a			   ="""""", """""", """"""
       a			   =[]

       for character in message_part:
              tmp.append(character_to_number[character]      )

       for each in tmp:
              one += each[0]
              two += each[1]
              three += each[2]

       return one + two + three





def 							lowerCamelCase    (							UpperCAmelCase_	:      str   ,       UpperCAmelCase_	:      dict[str, str]      )->			tuple[str, str, str]:

       """simple docstring"""




       a   ,      a			   ="""""", """"""
       a			   =[]

       for character in message_part:
              this_part += character_to_number[character]

       for digit in this_part:
              tmp += digit
              if len(UpperCAmelCase_      ) == len(UpperCAmelCase_      ):
                     result.append(UpperCAmelCase_      )
                     a			   =""""""

       return result[0], result[1], result[2]





def 							lowerCamelCase    (							UpperCAmelCase_	:      str   ,       UpperCAmelCase_	:      str      )->			tuple[str, str, dict[str, str], dict[str, str]]:

       """simple docstring"""




       a			   =alphabet.replace(""" """   ,       """"""      ).upper()
       a			   =message.replace(""" """   ,       """"""      ).upper()

       # Check length and characters
       if len(UpperCAmelCase_      ) != 27:
              raise KeyError("""Length of alphabet has to be 27."""      )
       for each in message:
              if each not in alphabet:
                     raise ValueError("""Each message character has to be included in alphabet!"""      )

    # Generate dictionares
       a			   =(
           """111""",
           """112""",
           """113""",
           """121""",
           """122""",
           """123""",
           """131""",
           """132""",
           """133""",
           """211""",
           """212""",
           """213""",
           """221""",
           """222""",
           """223""",
           """231""",
           """232""",
           """233""",
           """311""",
           """312""",
           """313""",
           """321""",
           """322""",
           """323""",
           """331""",
           """332""",
           """333""",
       )
       a			   ={}
       a			   ={}
       for letter, number in zip(UpperCAmelCase_   ,       UpperCAmelCase_      ):
              a			   =number
              a			   =letter

       return message, alphabet, character_to_number, number_to_character





def 							lowerCamelCase    (							UpperCAmelCase_	:      str   ,       UpperCAmelCase_	:      str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."   ,       UpperCAmelCase_	:      int = 5      )->			str:

       """simple docstring"""




       a   ,      a   ,      a   ,      a			   =__prepare(
           UpperCAmelCase_   ,       UpperCAmelCase_      )
       a   ,      a			   ="""""", """"""

       for i in range(0   ,       len(UpperCAmelCase_      ) + 1   ,       UpperCAmelCase_      ):
              encrypted_numeric += __encrypt_part(
                  message[i : i + period]   ,       UpperCAmelCase_      )

       for i in range(0   ,       len(UpperCAmelCase_      )   ,       3      ):
              encrypted += number_to_character[encrypted_numeric[i : i + 3]]

       return encrypted





def 							lowerCamelCase    (							UpperCAmelCase_	:      str   ,       UpperCAmelCase_	:      str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."   ,       UpperCAmelCase_	:      int = 5      )->			str:

       """simple docstring"""




       a   ,      a   ,      a   ,      a			   =__prepare(
           UpperCAmelCase_   ,       UpperCAmelCase_      )
       a			   =[]
       a			   =""""""

       for i in range(0   ,       len(UpperCAmelCase_      ) + 1   ,       UpperCAmelCase_      ):
              a   ,      a   ,      a			   =__decrypt_part(message[i : i + period]   ,       UpperCAmelCase_      )

              for j in range(0   ,       len(UpperCAmelCase_      )      ):
                     decrypted_numeric.append(a[j] + b[j] + c[j]      )

       for each in decrypted_numeric:
              decrypted += number_to_character[each]

       return decrypted


if __name__ == "__main__":
    _lowerCamelCase							=      '''DEFEND THE EAST WALL OF THE CASTLE.'''
    _lowerCamelCase							=      encrypt_message(msg, '''EPSDUCVWYM.ZLKXNBTFGORIJHAQ''')
    _lowerCamelCase							=      decrypt_message(encrypted, '''EPSDUCVWYM.ZLKXNBTFGORIJHAQ''')
    print(f"""Encrypted: {encrypted}\nDecrypted: {decrypted}""")
