



"""simple docstring"""






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


__UpperCAmelCase   :   int        =       logging.get_logger(__name__)

__UpperCAmelCase   :   List[str]        =       {
    '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 						__lowerCAmelCase				(A__	):


					'''simple docstring'''


					a__          =  """luke"""







					def __init__(   self     ,							a=5_02_67     ,							a=50_00_00     ,							a=7_68     ,							a=2_56     ,							a=12     ,							a=12     ,							a=30_72     ,							a="gelu"     ,							a=0.1     ,							a=0.1     ,							a=5_12     ,							a=2     ,							a=0.02     ,							a=1e-1_2     ,							a=True     ,							a=None     ,							a=1     ,							a=0     ,							a=2     ,							**a     ,							):




										"""simple docstring"""





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

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








import numpy as np
def      A__       (    SCREAMING_SNAKE_CASE_   :      np.ndarray				,	SCREAMING_SNAKE_CASE_   :      float						)  ->  np.ndarray:






   """simple docstring"""







   return np.where(vector > 0				,	SCREAMING_SNAKE_CASE_				,	(alpha * (np.exp(SCREAMING_SNAKE_CASE_						) - 1))						)


if __name__ == "__main__":
   import doctest

   doctest.testmod()