



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


snake_case_			:     Union[str, Any]  	=  logging.get_logger(__name__)

snake_case_			:     Dict  	=  {
    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class 							lowercase__     (							lowercase       ):
	lowercase__      =      """biogpt"""





	def __init__(			self :    Optional[Any]			,lowerCamelCase__ :    Optional[int]=42384			,lowerCamelCase__ :    List[Any]=1024			,lowerCamelCase__ :    List[str]=24			,lowerCamelCase__ :    Any=16			,lowerCamelCase__ :    List[Any]=4096			,lowerCamelCase__ :    Tuple="gelu"			,lowerCamelCase__ :    Optional[int]=0.1			,lowerCamelCase__ :    Dict=0.1			,lowerCamelCase__ :    Union[str, Any]=1024			,lowerCamelCase__ :    Optional[Any]=0.0_2			,lowerCamelCase__ :    Dict=1E-12			,lowerCamelCase__ :    str=True			,lowerCamelCase__ :    Dict=True			,lowerCamelCase__ :    Union[str, Any]=0.0			,lowerCamelCase__ :    Optional[Any]=0.0			,lowerCamelCase__ :    Optional[int]=1			,lowerCamelCase__ :    int=0			,lowerCamelCase__ :    Dict=2			,**lowerCamelCase__ :    Tuple			,):







							'''simple docstring'''
							_UpperCamelCase :		List[str]			    =       vocab_size
							_UpperCamelCase :		List[Any]			    =       max_position_embeddings
							_UpperCamelCase :		Dict			    =       hidden_size
							_UpperCamelCase :		Optional[Any]			    =       num_hidden_layers
							_UpperCamelCase :		Optional[Any]			    =       num_attention_heads
							_UpperCamelCase :		List[str]			    =       intermediate_size
							_UpperCamelCase :		str			    =       hidden_act
							_UpperCamelCase :		Union[str, Any]			    =       hidden_dropout_prob
							_UpperCamelCase :		Optional[Any]			    =       attention_probs_dropout_prob
							_UpperCamelCase :		str			    =       initializer_range
							_UpperCamelCase :		int			    =       layer_norm_eps
							_UpperCamelCase :		Any			    =       scale_embedding
							_UpperCamelCase :		List[str]			    =       use_cache
							_UpperCamelCase :		int			    =       layerdrop
							_UpperCamelCase :		List[str]			    =       activation_dropout
							super().__init__(pad_token_id=_a			,bos_token_id=_a			,eos_token_id=_a			,**_a			)







'''simple docstring'''
from __future__ import annotations






def A__   (					UpperCAmelCase_							):
						if not nums:
												return 0
						_UpperCamelCase :		Any			    =       nums[0]
						_UpperCamelCase :		Optional[int]			    =       0
						for num in nums[1:]:
												_UpperCamelCase    ,      _UpperCamelCase :		Optional[Any]			    =       (
												    max_excluding + num,
												    max(UpperCAmelCase_  ,  UpperCAmelCase_							),
												)
						return max(UpperCAmelCase_  ,  UpperCAmelCase_							)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


