


'''simple docstring'''




from bisect import bisect
from itertools import accumulate





def 	a_					( lowerCamelCase	:     Union[str, Any]	, lowerCamelCase	:     Optional[int]	, lowerCamelCase	:     List[Any]	, lowerCamelCase	:     Dict				):
   lowerCAmelCase     =			sorted(zip(lowerCamelCase	, lowerCamelCase				)	, key=lambda lowerCamelCase				: x[0] / x[1]	, reverse=lowerCamelCase				)
   lowerCAmelCase     ,  lowerCAmelCase     =			[i[0] for i in r], [i[1] for i in r]
   lowerCAmelCase     =			list(accumulate(lowerCamelCase				)				)
   lowerCAmelCase     =			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()









'''simple docstring'''




import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu

@require_cpu
class 		UpperCAmelCase_      (  unittest.TestCase		):





     def 							__UpperCAmelCase      ( self       :      str    )				->  List[Any]:
        lowerCAmelCase     =			torch.nn.Linear(1_0    ,      1_0    )
        lowerCAmelCase     =			torch.optim.SGD(model.parameters()    ,      0.1    )
        lowerCAmelCase     =			Accelerator()
        lowerCAmelCase     =			accelerator.prepare(UpperCAmelCase__    )
        try:
           pickle.loads(pickle.dumps(UpperCAmelCase__    )    )
        except Exception as e:
           self.fail(F'''Accelerated optimizer pickling failed with {e}'''    )
        AcceleratorState._reset_state()





