




from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments





def 							lowerCamelCase    (							)->			Optional[int]:

       """simple docstring"""




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

       a			   =PyTorchBenchmark(args=UpperCAmelCase_      )
       benchmark.run()


if __name__ == "__main__":
    main()






from typing import TYPE_CHECKING

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


_lowerCamelCase							=      {'''configuration_cvt''': ['''CVT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CvtConfig''']}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase							=      [
        '''CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''CvtForImageClassification''',
        '''CvtModel''',
        '''CvtPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase							=      [
        '''TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFCvtForImageClassification''',
        '''TFCvtModel''',
        '''TFCvtPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_cvt import (
            CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
            CvtForImageClassification,
            CvtModel,
            CvtPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_cvt import (
            TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFCvtForImageClassification,
            TFCvtModel,
            TFCvtPreTrainedModel,
        )


else:
    import sys

    _lowerCamelCase							=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
