"""simple docstring"""






from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments




def 						SCREAMING_SNAKE_CASE					(  ):
				SCREAMING_SNAKE_CASE__		  =				HfArgumentParser(_lowerCamelCase       )
				SCREAMING_SNAKE_CASE__		  =				parser.parse_args_into_dataclasses()[0]
				SCREAMING_SNAKE_CASE__		  =				TensorFlowBenchmark(args=_lowerCamelCase       )
				try:
								SCREAMING_SNAKE_CASE__		  =				parser.parse_args_into_dataclasses()[0]
				except ValueError as e:
								SCREAMING_SNAKE_CASE__		  =				"Arg --no_{0} is no longer used, please use --no-{0} instead."
								SCREAMING_SNAKE_CASE__		  =				" ".join(str(_lowerCamelCase       ).split(" "       )[:-1]       )
								SCREAMING_SNAKE_CASE__		  =				""
								SCREAMING_SNAKE_CASE__		  =				eval(str(_lowerCamelCase       ).split(" "       )[-1]       )
								SCREAMING_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:
												SCREAMING_SNAKE_CASE__		  =				full_error_msg + begin_error_msg + str(_lowerCamelCase       )
								raise ValueError(_lowerCamelCase       )
				benchmark.run()


if __name__ == "__main__":
						main()





"""simple docstring"""






from typing import TYPE_CHECKING

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


_A   					=    {'configuration_van': ['VAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VanConfig']}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_A   					=    [
						    '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   					=    _LazyModule(__name__, globals()['__file__'], _import_structure)




