





from ...configuration_utils import PretrainedConfig





class 				a			(      __lowercase			):
				SCREAMING_SNAKE_CASE__     :   int		      =     '''bert-generation'''






				def __init__(  self			, _lowerCAmelCase=50358			, _lowerCAmelCase=1024			, _lowerCAmelCase=24			, _lowerCAmelCase=16			, _lowerCAmelCase=4096			, _lowerCAmelCase="gelu"			, _lowerCAmelCase=0.1			, _lowerCAmelCase=0.1			, _lowerCAmelCase=512			, _lowerCAmelCase=0.02			, _lowerCAmelCase=1e-12			, _lowerCAmelCase=0			, _lowerCAmelCase=2			, _lowerCAmelCase=1			, _lowerCAmelCase="absolute"			, _lowerCAmelCase=True			, **_lowerCAmelCase			, ):

										"""simple docstring"""




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

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










def 		lowerCAmelCase  (	UpperCamelCase__   :   list       ,			UpperCamelCase__   :   list       ,			UpperCamelCase__   :   int					)      ->    list:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				Tuple           =   len(UpperCamelCase__					)
						__SCREAMING_SNAKE_CASE:				Optional[int]           =   [[0] * n for i in range(UpperCamelCase__					)]
						for i in range(UpperCamelCase__					):
												__SCREAMING_SNAKE_CASE:				str           =   y_points[i]

						for i in range(2       ,			UpperCamelCase__					):
												for j in range(UpperCamelCase__       ,			UpperCamelCase__					):
																		__SCREAMING_SNAKE_CASE:				Optional[int]           =   (
																		    (xa - x_points[j - i + 1]) * q[j][i - 1]
																		    - (xa - x_points[j]) * q[j - 1][i - 1]
																		) / (x_points[j] - x_points[j - i + 1])

						return [q[n - 1][n - 1], q]


if __name__ == "__main__":
							import doctest

							doctest.testmod()



