


from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def 							UpperCamelCase_(					)->		Tuple:
			UpperCamelCase__       =							HfArgumentParser(_A	)
			UpperCamelCase__       =							parser.parse_args_into_dataclasses()[0]
			UpperCamelCase__       =							TensorFlowBenchmark(args=_A	)
			try:
						UpperCamelCase__       =							parser.parse_args_into_dataclasses()[0]
			except ValueError as e:
						UpperCamelCase__       =							"Arg --no_{0} is no longer used, please use --no-{0} instead."
						UpperCamelCase__       =							" ".join(str(_A	).split(" "	)[:-1]	)
						UpperCamelCase__       =							""
						UpperCamelCase__       =							eval(str(_A	).split(" "	)[-1]	)
						UpperCamelCase__       =							[]
						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(_A	)
						if len(_A	) > 0:
									UpperCamelCase__       =							full_error_msg + begin_error_msg + str(_A	)
						raise ValueError(_A	)
			benchmark.run()


if __name__ == "__main__":
						main()





'''simple docstring'''




from typing import TYPE_CHECKING

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


_a					:			Any							=    {
    'configuration_groupvit': [
        'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'GroupViTConfig',
        'GroupViTOnnxConfig',
        'GroupViTTextConfig',
        'GroupViTVisionConfig',
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _a					:			Union[str, Any]							=    [
      'GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'GroupViTModel',
      'GroupViTPreTrainedModel',
      'GroupViTTextModel',
      'GroupViTVisionModel',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _a					:			Tuple							=    [
      'TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFGroupViTModel',
      'TFGroupViTPreTrainedModel',
      'TFGroupViTTextModel',
      'TFGroupViTVisionModel',
  ]

if TYPE_CHECKING:
  from .configuration_groupvit import (
      GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      GroupViTConfig,
      GroupViTOnnxConfig,
      GroupViTTextConfig,
      GroupViTVisionConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_groupvit import (
        GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
        GroupViTModel,
        GroupViTPreTrainedModel,
        GroupViTTextModel,
        GroupViTVisionModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_groupvit import (
        TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFGroupViTModel,
        TFGroupViTPreTrainedModel,
        TFGroupViTTextModel,
        TFGroupViTVisionModel,
    )

else:
  import sys

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


