




from __future__ import annotations

import numpy as np




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				return np.maximum(0	,     lowerCamelCase   )


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










from ... import PretrainedConfig


UpperCAmelCase_		:				List[str]									=     {
    "sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}




class 		__A      (			UpperCamelCase__			):
						UpperCamelCase     						=					NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
						UpperCamelCase     						=					"""nezha"""

						def __init__(		self   :List[Any]    , __snake_case   :Optional[int]=2_11_28    , __snake_case   :Dict=7_68    , __snake_case   :str=12    , __snake_case   :List[Any]=12    , __snake_case   :Optional[int]=30_72    , __snake_case   :Any="gelu"    , __snake_case   :List[str]=0.1    , __snake_case   :Optional[int]=0.1    , __snake_case   :Dict=5_12    , __snake_case   :Optional[int]=64    , __snake_case   :Any=2    , __snake_case   :List[Any]=0.02    , __snake_case   :List[str]=1E-12    , __snake_case   :Any=0.1    , __snake_case   :str=0    , __snake_case   :int=2    , __snake_case   :str=3    , __snake_case   :Any=True    , **__snake_case   :Any    , ):
										'''simple docstring'''

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

										__magic_name__	:	Tuple								=vocab_size
										__magic_name__	:	str								=hidden_size
										__magic_name__	:	Dict								=num_hidden_layers
										__magic_name__	:	str								=num_attention_heads
										__magic_name__	:	int								=hidden_act
										__magic_name__	:	Optional[int]								=intermediate_size
										__magic_name__	:	Union[str, Any]								=hidden_dropout_prob
										__magic_name__	:	Any								=attention_probs_dropout_prob
										__magic_name__	:	Union[str, Any]								=max_position_embeddings
										__magic_name__	:	str								=max_relative_position
										__magic_name__	:	Tuple								=type_vocab_size
										__magic_name__	:	str								=initializer_range
										__magic_name__	:	Tuple								=layer_norm_eps
										__magic_name__	:	Optional[int]								=classifier_dropout
										__magic_name__	:	List[str]								=use_cache




