"""simple docstring"""







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


_a     :     Optional[Any]= logging.get_logger(__name__)

_a     :     Tuple= {
    '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__						):
				UpperCAmelCase				:      int    =		'''luke'''



				def __init__(self				:      Optional[int]	,  _A				:      Tuple=5_02_67	,  _A				:      List[Any]=50_00_00	,  _A				:      Optional[int]=7_68	,  _A				:      Dict=2_56	,  _A				:      Optional[int]=12	,  _A				:      Optional[Any]=12	,  _A				:      str=30_72	,  _A				:      int="gelu"	,  _A				:      Dict=0.1	,  _A				:      List[Any]=0.1	,  _A				:      List[Any]=5_12	,  _A				:      int=2	,  _A				:      str=0.02	,  _A				:      Dict=1E-12	,  _A				:      int=True	,  _A				:      Dict=None	,  _A				:      Union[str, Any]=1	,  _A				:      Tuple=0	,  _A				:      List[str]=2	,  **_A				:      Optional[int]	,  )    ->	Tuple:
					super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__	,  bos_token_id=SCREAMING_SNAKE_CASE__	,  eos_token_id=SCREAMING_SNAKE_CASE__	,  **SCREAMING_SNAKE_CASE__)

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







"""simple docstring"""




def lowercase_  (   _snake_case   ,_snake_case						):
							return 1 if input_a == input_a else 0

def lowercase_  (   ):
							assert xnor_gate(0   ,0						) == 1
							assert xnor_gate(0   ,1						) == 0
							assert xnor_gate(1   ,0						) == 0
							assert xnor_gate(1   ,1						) == 1


if __name__ == "__main__":
					print(xnor_gate(0, 0))
					print(xnor_gate(0, 1))
					print(xnor_gate(1, 0))
					print(xnor_gate(1, 1))




