def      SCREAMING_SNAKE_CASE_  (		snake_case__							)  ->			List[Any]:
							lowerCAmelCase				=	len(snake_case__							)
							for i in range(length - 1							):
														lowerCAmelCase				=	False
														for j in range(length - 1 - i							):
																					if collection[j] > collection[j + 1]:
																												lowerCAmelCase				=	True
																												lowerCAmelCase	,   lowerCAmelCase				=	collection[j + 1], collection[j]
														if not swapped:
																					break  # Stop iteration if the collection is sorted.
							return collection


if __name__ == "__main__":
	import doctest
	import time

	doctest.testmod()

	lowercase__    :       Dict						=			input('''Enter numbers separated by a comma:''').strip()
	lowercase__    :       Optional[int]						=			[int(item) for item in user_input.split(''',''')]
	lowercase__    :       int						=			time.process_time()
	print(*bubble_sort(unsorted), sep=''',''')
	print(f'Processing time: {(time.process_time() - start)%1e9 + 7}')




import torch

from accelerate import Accelerator, DistributedType




class      lowercase_						:



	"""simple docstring"""





	def __enter__(							self       )		->Dict:
								if self.enabled:
															lowerCAmelCase				=	self.model.no_sync()
															self.model_sync_obj.__enter__()

								return self


	def __exit__(							self	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE       )		->Any:
								if self.enabled:
															# Average all models on exit
															self._sync_and_avg_model_params()
															self.model_sync_obj.__exit__(__SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE       )


	def __init__(							self	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE = True       )		->Tuple:
								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)'''       )
								lowerCAmelCase				=	enabled and accelerator.distributed_type != DistributedType.NO
								lowerCAmelCase				=	0
								if self.enabled:
															lowerCAmelCase				=	accelerator
															lowerCAmelCase				=	model
															lowerCAmelCase				=	local_sgd_steps


	def     SCREAMING_SNAKE_CASE_       (							self       )		->List[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     SCREAMING_SNAKE_CASE_       (							self       )		->Optional[int]:
								self.accelerator.wait_for_everyone()
								with self.accelerator.autocast():
															for param in self.model.parameters():
																						lowerCAmelCase				=	self.accelerator.reduce(param.data	,    reduction='''mean'''       )



