
import torch

from accelerate import Accelerator, DistributedType







class 			UpperCamelCase__		:







	'''simple docstring'''





	def __enter__(      self		):
					if self.enabled:
									A__	:						str								=				self.model.no_sync()
									self.model_sync_obj.__enter__()

					return self





	def __exit__(      self					,							UpperCamelCase__					,							UpperCamelCase__					,							UpperCamelCase__		):
					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					,							UpperCamelCase__					,							UpperCamelCase__					,							UpperCamelCase__					,							UpperCamelCase__ = 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)'''		)
					A__	:						Union[str, Any]								=				enabled and accelerator.distributed_type != DistributedType.NO
					A__	:						Dict								=				0
					if self.enabled:
									A__	:						Any								=				accelerator
									A__	:						List[str]								=				model
									A__	:						Dict								=				local_sgd_steps





	def 	__snake_case					(      self		):
					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 	__snake_case					(      self		):
					self.accelerator.wait_for_everyone()
					with self.accelerator.autocast():
									for param in self.model.parameters():
													A__	:						Optional[int]								=				self.accelerator.reduce(param.data					,							reduction='''mean'''		)

def 					SCREAMING_SNAKE_CASE  (   __UpperCamelCase			:    Dict				,    __UpperCamelCase			:    Dict							)			->							List[Any]:

				"""simple docstring"""







				if len(str(__UpperCamelCase							)							) == 1 or len(str(__UpperCamelCase							)							) == 1:
								return a * b

				A__	:						List[str]								=				max(len(str(__UpperCamelCase							)							)				,    len(str(__UpperCamelCase							)							)							)
				A__	:						Any								=				ma // 2

				A__							,				A__	:						Union[str, Any]								=				divmod(__UpperCamelCase				,    10**ma							)
				A__							,				A__	:						Tuple								=				divmod(__UpperCamelCase				,    10**ma							)

				A__	:						Optional[int]								=				karatsuba(__UpperCamelCase				,    __UpperCamelCase							)
				A__	:						Tuple								=				karatsuba((aa + aa)				,    (ba + ba)							)
				A__	:						Optional[int]								=				karatsuba(__UpperCamelCase				,    __UpperCamelCase							)

				return (z * 10 ** (2 * ma)) + ((y - z - x) * 10 ** (ma)) + (x)

def 					SCREAMING_SNAKE_CASE  (   )			->							Dict:

				"""simple docstring"""







				print(karatsuba(1_54_63				,    2_34_89							)							)


if __name__ == "__main__":
					main()