





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


UpperCAmelCase_							=				logging.get_logger(__name__)

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






		'''simple docstring'''






		__a       :       Tuple       =	"""lilt"""






		def __init__(							self,   snake_case__=3_05_22,   snake_case__=7_68,   snake_case__=12,   snake_case__=12,   snake_case__=30_72,   snake_case__="gelu",   snake_case__=0.1,   snake_case__=0.1,   snake_case__=5_12,   snake_case__=2,   snake_case__=0.02,   snake_case__=1E-12,   snake_case__=0,   snake_case__="absolute",   snake_case__=None,   snake_case__=4,   snake_case__=10_24,   **snake_case__,   )       -> 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]