"""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 		__A							(				unittest.TestCase	):






     def 					__A						(	self						):
       _lowerCAmelCase		: Any						    =  torch.nn.Linear(10       ,  10						)
       _lowerCAmelCase		: str						    =  torch.optim.SGD(model.parameters()       ,  0.1						)
       _lowerCAmelCase		: List[str]						    =  Accelerator()
       _lowerCAmelCase		: str						    =  accelerator.prepare(SCREAMING_SNAKE_CASE_						)
       try:
         pickle.loads(pickle.dumps(SCREAMING_SNAKE_CASE_						)						)
       except Exception as e:
         self.fail(F"Accelerated optimizer pickling failed with {e}"						)
       AcceleratorState._reset_state()





"""simple docstring"""




def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: int = 1000000			) ->   int:
  _lowerCAmelCase		: List[str]						    =  [i - 1 for i in range(limit + 1			)]

  for i in range(2    ,limit + 1			):
    if phi[i] == i - 1:
      for j in range(2 * i    ,limit + 1    ,_lowerCamelCase			):
        phi[j] -= phi[j] // i

  return sum(phi[2 : limit + 1]			)


if __name__ == "__main__":
     print(solution())




