



"""simple docstring"""







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


lowerCAmelCase_  		=  logging.get_logger(__name__)

lowerCAmelCase_  		=  {
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}
class 			__A			(      lowerCamelCase__       ):







		'''simple docstring'''





		lowerCAmelCase     :   Tuple        =							"""lilt"""







		def __init__(      self		:    int     ,_snake_case		:    Optional[Any]=30_522     ,_snake_case		:    str=768     ,_snake_case		:    int=12     ,_snake_case		:    Optional[Any]=12     ,_snake_case		:    Optional[int]=3_072     ,_snake_case		:    Tuple="gelu"     ,_snake_case		:    Dict=0.1     ,_snake_case		:    int=0.1     ,_snake_case		:    List[Any]=512     ,_snake_case		:    str=2     ,_snake_case		:    Optional[Any]=0.02     ,_snake_case		:    Optional[Any]=1e-12     ,_snake_case		:    Dict=0     ,_snake_case		:    Optional[int]="absolute"     ,_snake_case		:    int=None     ,_snake_case		:    Optional[Any]=4     ,_snake_case		:    List[Any]=1_024     ,**_snake_case		:    Dict     ,)   ->						Dict:






				"""simple docstring"""



				super().__init__(pad_token_id=snake_case__     ,**snake_case__		)

				lowercase__  :       str												=     vocab_size
				lowercase__  :       str												=     hidden_size
				lowercase__  :       List[str]												=     num_hidden_layers
				lowercase__  :       str												=     num_attention_heads
				lowercase__  :       Union[str, Any]												=     hidden_act
				lowercase__  :       Union[str, Any]												=     intermediate_size
				lowercase__  :       int												=     hidden_dropout_prob
				lowercase__  :       Optional[int]												=     attention_probs_dropout_prob
				lowercase__  :       Union[str, Any]												=     max_position_embeddings
				lowercase__  :       str												=     type_vocab_size
				lowercase__  :       List[str]												=     initializer_range
				lowercase__  :       Tuple												=     layer_norm_eps
				lowercase__  :       List[Any]												=     position_embedding_type
				lowercase__  :       str												=     classifier_dropout
				lowercase__  :       Dict												=     channel_shrink_ratio
				lowercase__  :       str												=     max_ad_position_embeddings







from __future__ import annotations

import numpy as np





def  __magic_name__  (				lowercase				)				-> Tuple:

							"""simple docstring"""



							return np.maximum(0				,       lowercase				)


if __name__ == "__main__":
							print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]