'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_a   :	Optional[int] 							=   {
    "configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	Any 							=   [
       "SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST",
       "Swinv2ForImageClassification",
       "Swinv2ForMaskedImageModeling",
       "Swinv2Model",
       "Swinv2PreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_swinva import (
          SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
          SwinvaForImageClassification,
          SwinvaForMaskedImageModeling,
          SwinvaModel,
          SwinvaPreTrainedModel,
      )


else:
   import sys

   _a   :	Union[str, Any] 							=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







'''simple docstring'''




from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def _lowercase	(      )					->       Dict:





       """simple docstring"""


       __UpperCAmelCase  :				str       				=		HfArgumentParser(lowerCamelCase__						)
       __UpperCAmelCase  :				Optional[Any]       				=		parser.parse_args_into_dataclasses()[0]
       __UpperCAmelCase  :				Any       				=		TensorFlowBenchmark(args=lowerCamelCase__						)
       try:
              __UpperCAmelCase  :				List[Any]       				=		parser.parse_args_into_dataclasses()[0]
       except ValueError as e:
              __UpperCAmelCase  :				str       				=		"Arg --no_{0} is no longer used, please use --no-{0} instead."
              __UpperCAmelCase  :				Tuple       				=		" ".join(str(lowerCamelCase__						).split(" "						)[:-1]						)
              __UpperCAmelCase  :				Any       				=		""
              __UpperCAmelCase  :				List[Any]       				=		eval(str(lowerCamelCase__						).split(" "						)[-1]						)
              __UpperCAmelCase  :				Optional[int]       				=		[]
              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:
                     __UpperCAmelCase  :				Union[str, Any]       				=		full_error_msg + begin_error_msg + str(lowerCamelCase__						)
              raise ValueError(lowerCamelCase__						)
       benchmark.run()


if __name__ == "__main__":
   main()






