

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


lowerCAmelCase_       	=	logging.get_logger(__name__)

lowerCAmelCase_       	=	{
    '''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_   (		__A					):







			'''simple docstring'''

			SCREAMING_SNAKE_CASE     :   Optional[int]									=				"biogpt"







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



'''simple docstring'''


import unittest

from knapsack import greedy_knapsack as kp





class     lowercase__  (						unittest.TestCase					):





							'''simple docstring'''


							def UpperCAmelCase_	(    self  ):
											_SCREAMING_SNAKE_CASE :       str     		=      [10, 20, 30, 40, 50, 60]
											_SCREAMING_SNAKE_CASE :       List[str]     		=      [2, 4, 6, 8, 10, 12]
											_SCREAMING_SNAKE_CASE :       str     		=      100
											self.assertEqual(kp.calc_profit(__snake_case    ,					__snake_case    ,					__snake_case  )    ,					210  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""max_weight must greater than zero."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""Weight can not be negative."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""Profit can not be negative."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(__snake_case    ,					"""max_weight must greater than zero."""  )






							def UpperCAmelCase_	(    self  ):
											self.assertRaisesRegex(
											    __snake_case    ,					"""The length of profit and weight must be same."""  )


if __name__ == "__main__":
				unittest.main()




