



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


_snake_case	=						logging.get_logger(__name__)

_snake_case	=						{
    "studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
    "studio-ousia/luke-large": "https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json",
}



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	'luke'







							def __init__(     self,    __a=5_0267,    __a=50_0000,    __a=768,    __a=256,    __a=12,    __a=12,    __a=3072,    __a="gelu",    __a=0.1,    __a=0.1,    __a=512,    __a=2,    __a=0.02,    __a=1E-12,    __a=True,    __a=None,    __a=1,    __a=0,    __a=2,    **__a,    ):

														'''simple docstring'''

														super().__init__(pad_token_id=__a,    bos_token_id=__a,    eos_token_id=__a,    **__a)

														_lowerCAmelCase  :							Optional[Any]				     =					vocab_size
														_lowerCAmelCase  :							List[Any]				     =					entity_vocab_size
														_lowerCAmelCase  :							int				     =					hidden_size
														_lowerCAmelCase  :							Optional[Any]				     =					entity_emb_size
														_lowerCAmelCase  :							List[str]				     =					num_hidden_layers
														_lowerCAmelCase  :							Dict				     =					num_attention_heads
														_lowerCAmelCase  :							str				     =					hidden_act
														_lowerCAmelCase  :							Dict				     =					intermediate_size
														_lowerCAmelCase  :							Optional[int]				     =					hidden_dropout_prob
														_lowerCAmelCase  :							List[Any]				     =					attention_probs_dropout_prob
														_lowerCAmelCase  :							Optional[Any]				     =					max_position_embeddings
														_lowerCAmelCase  :							Any				     =					type_vocab_size
														_lowerCAmelCase  :							List[Any]				     =					initializer_range
														_lowerCAmelCase  :							Tuple				     =					layer_norm_eps
														_lowerCAmelCase  :							str				     =					use_entity_aware_attention
														_lowerCAmelCase  :							Dict				     =					classifier_dropout





import string






def        A       (      _lowerCamelCase						):





							'''simple docstring'''




							for key in range(len(string.ascii_uppercase						)						):
														_lowerCAmelCase  :							str				     =					""
														for symbol in message:
																					if symbol in string.ascii_uppercase:
																												_lowerCAmelCase  :							List[str]				     =					string.ascii_uppercase.find(_lowerCamelCase						)
																												_lowerCAmelCase  :							Dict				     =					num - key
																												if num < 0:
																																			_lowerCAmelCase  :							Dict				     =					num + len(string.ascii_uppercase						)
																												_lowerCAmelCase  :							Optional[Any]				     =					translated + string.ascii_uppercase[num]
																					else:
																												_lowerCAmelCase  :							int				     =					translated + symbol
														print(F"Decryption using Key #{key}: {translated}"						)






def        A       (      ):





							'''simple docstring'''




							_lowerCAmelCase  :							Tuple				     =					input("Encrypted message: "						)
							_lowerCAmelCase  :							Dict				     =					message.upper()
							decrypt(_lowerCamelCase						)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()
