


from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments





def 						_lowerCAmelCase							(     )    ->						str:


						'''simple docstring'''






						__snake_case				=		HfArgumentParser(_lowerCAmelCase			)
						__snake_case				=		parser.parse_args_into_dataclasses()[0]
						__snake_case				=		TensorFlowBenchmark(args=_lowerCAmelCase			)
						try:
												__snake_case				=		parser.parse_args_into_dataclasses()[0]
						except ValueError as e:
												__snake_case				=		"Arg --no_{0} is no longer used, please use --no-{0} instead."
												__snake_case				=		" ".join(str(_lowerCAmelCase			).split(" "			)[:-1]			)
												__snake_case				=		""
												__snake_case				=		eval(str(_lowerCAmelCase			).split(" "			)[-1]			)
												__snake_case				=		[]
												for arg in depreciated_args:
																		# arg[2:] removes '--'
																		if arg[2:] in TensorFlowBenchmark.deprecated_args:
																								# arg[5:] removes '--no_'
																								full_error_msg += arg_error_msg.format(arg[5:]			)
																		else:
																								wrong_args.append(_lowerCAmelCase			)
												if len(_lowerCAmelCase			) > 0:
																		__snake_case				=		full_error_msg + begin_error_msg + str(_lowerCAmelCase			)
												raise ValueError(_lowerCAmelCase			)
						benchmark.run()


if __name__ == "__main__":
	main()









from typing import TYPE_CHECKING

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


A				:       Optional[Any]      =  {'configuration_van': ['VAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VanConfig']}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A				:       Optional[Any]      =  [
	    'VAN_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'VanForImageClassification',
	    'VanModel',
	    'VanPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_van import (
		    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    VanForImageClassification,
		    VanModel,
		    VanPreTrainedModel,
		)

else:
	import sys

	A				:       Union[str, Any]      =  _LazyModule(__name__, globals()['__file__'], _import_structure)





