


"""simple docstring"""





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


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

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



class 		snake_case_(       UpperCAmelCase__			):
     __UpperCamelCase  =					"biogpt"






     def __init__(	self  :					Dict					,				UpperCamelCase_  :					Union[str, Any]=4_2_3_8_4					,				UpperCamelCase_  :					Any=1_0_2_4					,				UpperCamelCase_  :					List[str]=2_4					,				UpperCamelCase_  :					Dict=1_6					,				UpperCamelCase_  :					Optional[Any]=4_0_9_6					,				UpperCamelCase_  :					Optional[Any]="gelu"					,				UpperCamelCase_  :					Any=0.1					,				UpperCamelCase_  :					Union[str, Any]=0.1					,				UpperCamelCase_  :					List[str]=1_0_2_4					,				UpperCamelCase_  :					List[str]=0.02					,				UpperCamelCase_  :					Any=1E-12					,				UpperCamelCase_  :					Tuple=True					,				UpperCamelCase_  :					Optional[Any]=True					,				UpperCamelCase_  :					Union[str, Any]=0.0					,				UpperCamelCase_  :					Optional[Any]=0.0					,				UpperCamelCase_  :					str=1					,				UpperCamelCase_  :					Any=0					,				UpperCamelCase_  :					List[str]=2					,				**UpperCamelCase_  :					List[Any]					,				):
           lowerCAmelCase					:	Optional[Any]       =   vocab_size
           lowerCAmelCase					:	Optional[int]       =   max_position_embeddings
           lowerCAmelCase					:	List[str]       =   hidden_size
           lowerCAmelCase					:	List[str]       =   num_hidden_layers
           lowerCAmelCase					:	List[Any]       =   num_attention_heads
           lowerCAmelCase					:	int       =   intermediate_size
           lowerCAmelCase					:	Tuple       =   hidden_act
           lowerCAmelCase					:	str       =   hidden_dropout_prob
           lowerCAmelCase					:	Tuple       =   attention_probs_dropout_prob
           lowerCAmelCase					:	List[Any]       =   initializer_range
           lowerCAmelCase					:	Optional[int]       =   layer_norm_eps
           lowerCAmelCase					:	List[Any]       =   scale_embedding
           lowerCAmelCase					:	List[str]       =   use_cache
           lowerCAmelCase					:	Optional[int]       =   layerdrop
           lowerCAmelCase					:	Any       =   activation_dropout
           super().__init__(pad_token_id=lowerCamelCase__					,				bos_token_id=lowerCamelCase__					,				eos_token_id=lowerCamelCase__					,				**lowerCamelCase__				)






"""simple docstring"""





from __future__ import annotations


def      _snake_case						(						_snake_case				:			list[int] ,   _snake_case				:			int			):
      if len(_snake_case			) == 0:
            return False
      lowerCAmelCase					:	List[Any]       =   len(_snake_case			) // 2
      if a_list[midpoint] == item:
            return True
      if item < a_list[midpoint]:
            return binary_search(a_list[:midpoint] ,   _snake_case			)
      else:
            return binary_search(a_list[midpoint + 1 :] ,   _snake_case			)


if __name__ == "__main__":
 snake_case__		:     List[str]    				=				input('''Enter numbers separated by comma:\n''').strip()
 snake_case__		:     Optional[int]    				=				[int(item.strip()) for item in user_input.split(''',''')]
 snake_case__		:     Dict    				=				int(input('''Enter the number to be found in the list:\n''').strip())
 snake_case__		:     str    				=				'''''' if binary_search(sequence, target) else '''not '''
 print(f"""{target} was {not_str}found in {sequence}""")


