


'''simple docstring'''

def _SCREAMING_SNAKE_CASE   (A ) -> list:






       """simple docstring"""







       lowercase__       =				len(snake_case__ )
       for cycle_start in range(0						,				array_len - 1 ):
              lowercase__       =				array[cycle_start]

              lowercase__       =				cycle_start
              for i in range(cycle_start + 1						,				snake_case__ ):
                     if array[i] < item:
                            pos += 1

              if pos == cycle_start:
                     continue

              while item == array[pos]:
                     pos += 1

              lowercase__       =				item, array[pos]
              while pos != cycle_start:
                     lowercase__       =				cycle_start
                     for i in range(cycle_start + 1						,				snake_case__ ):
                            if array[i] < item:
                                   pos += 1

                     while item == array[pos]:
                            pos += 1

                     lowercase__       =				item, array[pos]

       return array


if __name__ == "__main__":
 assert cycle_sort([4, 5, 3, 2, 1]) == [1, 2, 3, 4, 5]
 assert cycle_sort([0, 1, -10, 15, 2, -2]) == [-10, -2, 0, 1, 2, 15]








'''simple docstring'''

import torch

from accelerate import Accelerator, DistributedType
class 						__lowerCAmelCase		:





      '''simple docstring'''






      def __enter__(self					:					List[Any]				):

             '''simple docstring'''







             if self.enabled:
                    lowercase__       =				self.model.no_sync()
                    self.model_sync_obj.__enter__()

             return self



      def __exit__(self					:					List[str]     ,		UpperCamelCase					:					List[Any]     ,		UpperCamelCase					:					Optional[int]     ,		UpperCamelCase					:					Optional[int]				):

             '''simple docstring'''







             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					:					Dict     ,		UpperCamelCase					:					Accelerator     ,		UpperCamelCase					:					torch.nn.Module     ,		UpperCamelCase					:					int     ,		UpperCamelCase					:					bool = True				):

             '''simple docstring'''







             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    UpperCamelCase__	(self					:					List[str]				):

             '''simple docstring'''







             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    UpperCamelCase__	(self					:					Any				):

             '''simple docstring'''







             self.accelerator.wait_for_everyone()
             with self.accelerator.autocast():
                    for param in self.model.parameters():
                           lowercase__       =				self.accelerator.reduce(param.data     ,		reduction='''mean'''				)




