
import importlib.metadata
import subprocess
import sys
def 					lowerCAmelCase__     (    SCREAMING_SNAKE_CASE_ = False	)							->						Union[str, Any]:
			lowerCAmelCase__ : Optional[Any]   =						False
			if "IPython" in sys.modules:
						lowerCAmelCase__ : Optional[int]   =						'google.colab' in str(sys.modules['IPython'].get_ipython()	)

			if in_colab:
						if upgrade:
									lowerCAmelCase__ : Dict   =						['pip', 'install', '-U', 'torch']
									subprocess.run(SCREAMING_SNAKE_CASE_			,				check=SCREAMING_SNAKE_CASE_	)
						# get the current version of torch
						lowerCAmelCase__ : int   =						importlib.metadata.version('torch'	)
						lowerCAmelCase__ : Optional[int]   =						torch_version[: torch_version.rindex('.'	)]
						lowerCAmelCase__ : Any   =						F'''https://storage.googleapis.com/tpu-pytorch/wheels/colab/torch_xla-{torch_version_trunc}-cp37-cp37m-linux_x86_64.whl'''
						lowerCAmelCase__ : List[Any]   =						['pip', 'install', xla_wheel]
						subprocess.run(SCREAMING_SNAKE_CASE_			,				check=SCREAMING_SNAKE_CASE_	)
			else:
						raise RuntimeError('`install_xla` utility works only on google colab.'	)

import torch

from accelerate import Accelerator, DistributedType







class 	A__				:






				def __enter__(		self   : Optional[Any]  ):






							'''simple docstring'''







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

							return self






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






							'''simple docstring'''







							if self.enabled:
										# Average all models on exit
										self._sync_and_avg_model_params()
										self.model_sync_obj.__exit__(a       ,	a       ,	a  )






				def __init__(		self   : List[str]       ,	a   : Accelerator       ,	a   : torch.nn.Module       ,	a   : int       ,	a   : 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)'  )
							lowerCAmelCase__ : Union[str, Any]   =						enabled and accelerator.distributed_type != DistributedType.NO
							lowerCAmelCase__ : str   =						0
							if self.enabled:
										lowerCAmelCase__ : Dict   =						accelerator
										lowerCAmelCase__ : Dict   =						model
										lowerCAmelCase__ : Optional[int]   =						local_sgd_steps






				def 				_lowerCamelCase						(		self   : Optional[Any]  ):






							'''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 				_lowerCamelCase						(		self   : int  ):






							'''simple docstring'''







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