code: 
  
  UpperCAmelCase_       :				Optional[Any]		   =      {
      '''A''': ('''ABCDEFGHIJKLM''', '''NOPQRSTUVWXYZ'''),
      '''B''': ('''ABCDEFGHIJKLM''', '''NOPQRSTUVWXYZ'''),
      '''C''': ('''ABCDEFGHIJKLM''', '''ZNOPQRSTUVWXY'''),
      '''D''': ('''ABCDEFGHIJKLM''', '''ZNOPQRSTUVWXY'''),
      '''E''': ('''ABCDEFGHIJKLM''', '''YZNOPQRSTUVWX'''),
      '''F''': ('''ABCDEFGHIJKLM''', '''YZNOPQRSTUVWX'''),
      '''G''': ('''ABCDEFGHIJKLM''', '''XYZNOPQRSTUVW'''),
      '''H''': ('''ABCDEFGHIJKLM''', '''XYZNOPQRSTUVW'''),
      '''I''': ('''ABCDEFGHIJKLM''', '''WXYZNOPQRSTUV'''),
      '''J''': ('''ABCDEFGHIJKLM''', '''WXYZNOPQRSTUV'''),
      '''K''': ('''ABCDEFGHIJKLM''', '''VWXYZNOPQRSTU'''),
      '''L''': ('''ABCDEFGHIJKLM''', '''VWXYZNOPQRSTU'''),
      '''M''': ('''ABCDEFGHIJKLM''', '''UVWXYZNOPQRST'''),
      '''N''': ('''ABCDEFGHIJKLM''', '''UVWXYZNOPQRST'''),
      '''O''': ('''ABCDEFGHIJKLM''', '''TUVWXYZNOPQRS'''),
      '''P''': ('''ABCDEFGHIJKLM''', '''TUVWXYZNOPQRS'''),
      '''Q''': ('''ABCDEFGHIJKLM''', '''STUVWXYZNOPQR'''),
      '''R''': ('''ABCDEFGHIJKLM''', '''STUVWXYZNOPQR'''),
      '''S''': ('''ABCDEFGHIJKLM''', '''RSTUVWXYZNOPQ'''),
      '''T''': ('''ABCDEFGHIJKLM''', '''RSTUVWXYZNOPQ'''),
      '''U''': ('''ABCDEFGHIJKLM''', '''QRSTUVWXYZNOP'''),
      '''V''': ('''ABCDEFGHIJKLM''', '''QRSTUVWXYZNOP'''),
      '''W''': ('''ABCDEFGHIJKLM''', '''PQRSTUVWXYZNO'''),
      '''X''': ('''ABCDEFGHIJKLM''', '''PQRSTUVWXYZNO'''),
      '''Y''': ('''ABCDEFGHIJKLM''', '''OPQRSTUVWXYZN'''),
      '''Z''': ('''ABCDEFGHIJKLM''', '''OPQRSTUVWXYZN'''),
  }
  def        __SCREAMING_SNAKE_CASE    (      a__						:      Optional[int]					)				->							list[tuple[str, str]]:
   return [alphabet[char] for char in key.upper()]
  def        __SCREAMING_SNAKE_CASE    (      a__						:      Tuple ,a__						:      List[Any]					)				->							str:
   __A   : Optional[Any]								= """"""
   __A   : str								= 0
   __A   : Any								= generate_table(__snake_case					)
   for char in words.upper():
    cipher += get_opponent(table[count] ,__snake_case					)
    __A   : Tuple								= (count + 1) % len(__snake_case					)
   return cipher
  def        __SCREAMING_SNAKE_CASE    (      a__						:      Optional[int] ,a__						:      Optional[Any]					)				->							str:
   return encrypt(__snake_case ,__snake_case					)
  def        __SCREAMING_SNAKE_CASE    (      a__						:      Optional[int] ,a__						:      Tuple					)				->							tuple[int, int]:
   __A   : str								= 0 if char in table[0] else 1
   __A   : List[str]								= table[row].index(__snake_case					)
   return row, col
  def        __SCREAMING_SNAKE_CASE    (      a__						:      Tuple ,a__						:      Union[str, Any]					)				->							str:
   __A						,							__A   : int								= get_position(__snake_case ,char.upper()					)
   if row == 1:
    return table[0][col]
   else:
    return table[1][col] if row == 0 else char
  
  
  if __name__ == "__main__":
     import doctest
  
     doctest.testmod()  # Fist ensure that all our tests are passing...
     UpperCAmelCase_       :				List[Any]		   =      input('''Enter key: ''').strip()
     UpperCAmelCase_       :				Any		   =      input('''Enter text to encrypt: ''').strip()
     UpperCAmelCase_       :				List[str]		   =      encrypt(key, text)
  
     print(f"""Encrypted: {cipher_text}""")
     print(f"""Decrypted with key: {decrypt(key, cipher_text)}""")
  
  
  
  
  
  
style_context: 
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  UpperCAmelCase_       :				Optional[Any]		   =      logging.get_logger(__name__)
  
  UpperCAmelCase_       :				List[str]		   =      {
      '''uw-madison/nystromformer-512''': '''https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json''',
      # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
  }
  
  
  
  
  
  
  class     lowerCamelCase_			(  _lowercase  ):
  	_lowercase		:      Optional[Any]    				=							'''nystromformer'''
  
  
  
  
  	def __init__(    self	:    Optional[Any]				,			__A	:    Optional[Any]=3_0000				,			__A	:    Optional[int]=768				,			__A	:    List[str]=12				,			__A	:    str=12				,			__A	:    Tuple=3072				,			__A	:    List[Any]="gelu_new"				,			__A	:    Dict=0.1				,			__A	:    Optional[int]=0.1				,			__A	:    int=510				,			__A	:    Union[str, Any]=2				,			__A	:    Optional[int]=64				,			__A	:    str=64				,			__A	:    List[str]=65				,			__A	:    Tuple=False				,			__A	:    List[str]=0.0_2				,			__A	:    Tuple=1e-5				,			__A	:    List[str]=1				,			__A	:    int=0				,			__A	:    Tuple=2				,			**__A	:    Dict				,			):
  		__A   : str								= vocab_size
  		__A   : Union[str, Any]								= max_position_embeddings
  		__A   : Optional[int]								= hidden_size
  		__A   : Optional[int]								= num_hidden_layers
  		__A   : List[Any]								= num_attention_heads
  		__A   : Dict								= intermediate_size
  		__A   : Union[str, Any]								= hidden_act
  		__A   : int								= hidden_dropout_prob
  		__A   : Tuple								= attention_probs_dropout_prob
  		__A   : Optional[Any]								= initializer_range
  		__A   : int								= type_vocab_size
  		__A   : Optional[int]								= segment_means_seq_len
  		__A   : List[str]								= num_landmarks
  		__A   : Dict								= conv_kernel_size
  		__A   : Union[str, Any]								= inv_coeff_init_option
  		__A   : Union[str, Any]								= layer_norm_eps
  		super().__init__(pad_token_id=__A				,			bos_token_id=__A				,			eos_token_id=__A				,			**__A       )
  
  
  
  
  
  