

"""simple docstring"""





import torch

from accelerate import Accelerator, DistributedType




class    _lowerCAmelCase    :







 """simple docstring"""







 def __enter__(     self				:     Dict      ):
    if self.enabled:
       __lowercase								=		self.model.no_sync()
       self.model_sync_obj.__enter__()

    return self


 def __exit__(     self				:     Union[str, Any],   UpperCAmelCase__				:     Dict,   UpperCAmelCase__				:     Any,   UpperCAmelCase__				:     List[Any]      ):
    if self.enabled:
       # Average all models on exit
       self._sync_and_avg_model_params()
       self.model_sync_obj.__exit__(UpperCAmelCase__,   UpperCAmelCase__,   UpperCAmelCase__      )


 def __init__(     self				:     str,   UpperCAmelCase__				:     Accelerator,   UpperCAmelCase__				:     torch.nn.Module,   UpperCAmelCase__				:     int,   UpperCAmelCase__				:     bool = True      ):
    if accelerator.distributed_type not in [
        DistributedType.NO,
        DistributedType.MULTI_CPU,
        DistributedType.MULTI_GPU,
    ]:
       raise NotImplementedError("LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)"      )
    __lowercase								=		enabled and accelerator.distributed_type != DistributedType.NO
    __lowercase								=		0
    if self.enabled:
       __lowercase								=		accelerator
       __lowercase								=		model
       __lowercase								=		local_sgd_steps


 def    _lowercase					(     self				:     Union[str, Any]      ):
    self.num_steps += 1
    if not self.enabled:
       return

    if self.num_steps % self.local_sgd_steps == 0:
       self._sync_and_avg_model_params()



 def    _lowercase					(     self				:     Union[str, Any]      ):
    self.accelerator.wait_for_everyone()
    with self.accelerator.autocast():
       for param in self.model.parameters():
          __lowercase								=		self.accelerator.reduce(param.data,   reduction="mean"      )







"""simple docstring"""





def     _A    (    UpperCamelCase_	:			list)      ->		list:
   '''simple docstring'''


   for i, _ in enumerate(UpperCamelCase_):
      if (i % 2 == 1) == (nums[i - 1] > nums[i]):
         __lowercase						,__lowercase								=		nums[i], nums[i - 1]

   return nums


if __name__ == "__main__":
   print('Enter the array elements:')
   _a					 =				list(map(int, input().split()))
   print('The unsorted array is:')
   print(array)
   print('Array after Wiggle sort:')
   print(wiggle_sort(array))




