from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase__    :       List[Any]						=			{
    '''configuration_nystromformer''': ['''NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NystromformerConfig'''],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__    :       Any						=			[
	    '''NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''NystromformerForMaskedLM''',
	    '''NystromformerForMultipleChoice''',
	    '''NystromformerForQuestionAnswering''',
	    '''NystromformerForSequenceClassification''',
	    '''NystromformerForTokenClassification''',
	    '''NystromformerLayer''',
	    '''NystromformerModel''',
	    '''NystromformerPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_nystromformer import (
		    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    NystromformerForMaskedLM,
		    NystromformerForMultipleChoice,
		    NystromformerForQuestionAnswering,
		    NystromformerForSequenceClassification,
		    NystromformerForTokenClassification,
		    NystromformerLayer,
		    NystromformerModel,
		    NystromformerPreTrainedModel,
		)


else:
	import sys

	lowercase__    :       Tuple						=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




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'''       )



