





import math






def 	_SCREAMING_SNAKE_CASE		(				)      ->   None:
 __lowerCAmelCase					:	Optional[Any]      =       input("""Enter message: """   )
 __lowerCAmelCase					:	Tuple      =       int(input(F'''Enter key [2-{len(SCREAMING_SNAKE_CASE_   ) - 1}]: '''   )   )
 __lowerCAmelCase					:	Union[str, Any]      =       input("""Encryption/Decryption [e/d]: """   )

 if mode.lower().startswith("""e"""   ):
  __lowerCAmelCase					:	Dict      =       encrypt_message(SCREAMING_SNAKE_CASE_   ,   SCREAMING_SNAKE_CASE_   )
 elif mode.lower().startswith("""d"""   ):
  __lowerCAmelCase					:	Union[str, Any]      =       decrypt_message(SCREAMING_SNAKE_CASE_   ,   SCREAMING_SNAKE_CASE_   )

 # Append pipe symbol (vertical bar) to identify spaces at the end.
 print(F'''Output:\n{text + "|"}'''   )






def 	_SCREAMING_SNAKE_CASE		(				SCREAMING_SNAKE_CASE		:Optional[Any]   ,   SCREAMING_SNAKE_CASE		:Any   )      ->   str:
 __lowerCAmelCase					:	Tuple      =       [""""""] * key
 for col in range(SCREAMING_SNAKE_CASE_   ):
  __lowerCAmelCase					:	int      =       col
  while pointer < len(SCREAMING_SNAKE_CASE_   ):
   cipher_text[col] += message[pointer]
   pointer += key
 return "".join(SCREAMING_SNAKE_CASE_   )






def 	_SCREAMING_SNAKE_CASE		(				SCREAMING_SNAKE_CASE		:Optional[Any]   ,   SCREAMING_SNAKE_CASE		:List[str]   )      ->   str:
 __lowerCAmelCase					:	Any      =       math.ceil(len(SCREAMING_SNAKE_CASE_   ) / key   )
 __lowerCAmelCase					:	Optional[int]      =       key
 __lowerCAmelCase					:	Optional[Any]      =       (num_cols * num_rows) - len(SCREAMING_SNAKE_CASE_   )
 __lowerCAmelCase					:	Dict      =       [""""""] * num_cols
 __lowerCAmelCase					:	Tuple      =       0
 __lowerCAmelCase					:	str      =       0

 for symbol in message:
  plain_text[col] += symbol
  col += 1

  if (
      (col == num_cols)
      or (col == num_cols - 1)
      and (row >= num_rows - num_shaded_boxes)
  ):
   __lowerCAmelCase					:	Union[str, Any]      =       0
   row += 1

 return "".join(SCREAMING_SNAKE_CASE_   )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()






from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCAmelCase             =							logging.get_logger(__name__)

_UpperCAmelCase             =							{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class        snake_case_    (		__lowercase						):
  A_      							=   'biogpt'






  def __init__(							self			:					int       ,  _snake_case			:					Any=42384       ,  _snake_case			:					Any=1024       ,  _snake_case			:					List[Any]=24       ,  _snake_case			:					Any=16       ,  _snake_case			:					List[str]=4096       ,  _snake_case			:					Dict="gelu"       ,  _snake_case			:					Tuple=0.1       ,  _snake_case			:					str=0.1       ,  _snake_case			:					Tuple=1024       ,  _snake_case			:					Tuple=0.02       ,  _snake_case			:					Tuple=1E-12       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Any=0.0       ,  _snake_case			:					Tuple=0.0       ,  _snake_case			:					str=1       ,  _snake_case			:					Dict=0       ,  _snake_case			:					str=2       ,  **_snake_case			:					Union[str, Any]       ,  )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       vocab_size
   __lowerCAmelCase					:	Dict      =       max_position_embeddings
   __lowerCAmelCase					:	str      =       hidden_size
   __lowerCAmelCase					:	Dict      =       num_hidden_layers
   __lowerCAmelCase					:	List[Any]      =       num_attention_heads
   __lowerCAmelCase					:	Optional[Any]      =       intermediate_size
   __lowerCAmelCase					:	int      =       hidden_act
   __lowerCAmelCase					:	Any      =       hidden_dropout_prob
   __lowerCAmelCase					:	Any      =       attention_probs_dropout_prob
   __lowerCAmelCase					:	Any      =       initializer_range
   __lowerCAmelCase					:	int      =       layer_norm_eps
   __lowerCAmelCase					:	Optional[int]      =       scale_embedding
   __lowerCAmelCase					:	List[Any]      =       use_cache
   __lowerCAmelCase					:	str      =       layerdrop
   __lowerCAmelCase					:	Dict      =       activation_dropout
   super().__init__(pad_token_id=_snake_case       ,  bos_token_id=_snake_case       ,  eos_token_id=_snake_case       ,  **_snake_case      )