



from torch import nn



class  lowerCamelCase__    (							nn.Module):




		'''simple docstring'''



		def __init__(self	,__lowerCamelCase	,__lowerCamelCase				)  ->    Dict:

						"""simple docstring"""






						super().__init__()
						lowerCAmelCase__  :       Any				=  class_size
						lowerCAmelCase__  :       Optional[int]				=  embed_size
						# self.mlp1 = nn.Linear(embed_size, embed_size)
						# self.mlp2 = (nn.Linear(embed_size, class_size))
						lowerCAmelCase__  :       List[str]				=  nn.Linear(__lowerCamelCase	,__lowerCamelCase				)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    Any:

						"""simple docstring"""






						lowerCAmelCase__  :       Any				=  self.mlp(__lowerCamelCase				)
						return logits






from bisect import bisect
from itertools import accumulate






def 			lowerCAmelCase__	(					lowerCamelCase_	:	List[str] ,lowerCamelCase_	:	Optional[Any] ,lowerCamelCase_	:	List[str] ,lowerCamelCase_	:	Optional[int]):





				'''simple docstring'''

				lowerCAmelCase__  :       Any				=  sorted(zip(lowerCamelCase_ ,lowerCamelCase_) ,key=lambda lowerCamelCase_: x[0] / x[1] ,reverse=lowerCamelCase_)
				lowerCAmelCase__		,	lowerCAmelCase__  :       List[str]				=  [i[0] for i in r], [i[1] for i in r]
				lowerCAmelCase__  :       Tuple				=  list(accumulate(lowerCamelCase_))
				lowerCAmelCase__  :       str				=  bisect(lowerCamelCase_ ,lowerCamelCase_)
				return (
				    0
				    if k == 0
				    else sum(vl[:k]) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
				    if k != n
				    else sum(vl[:k])
				)


if __name__ == "__main__":
							import doctest

							doctest.testmod()

