





from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments




def 					__UpperCamelCase  ()    ->       Optional[int]:
  lowercase__           =  HfArgumentParser(_SCREAMING_SNAKE_CASE		)
  lowercase__           =  parser.parse_args_into_dataclasses()[0]
  lowercase__           =  TensorFlowBenchmark(args=_SCREAMING_SNAKE_CASE		)
  try:
    lowercase__           =  parser.parse_args_into_dataclasses()[0]
  except ValueError as e:
    lowercase__           =  'Arg --no_{0} is no longer used, please use --no-{0} instead.'
    lowercase__           =  ' '.join(str(_SCREAMING_SNAKE_CASE		).split(' '		)[:-1]		)
    lowercase__           =  ''
    lowercase__           =  eval(str(_SCREAMING_SNAKE_CASE		).split(' '		)[-1]		)
    lowercase__           =  []
    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(_SCREAMING_SNAKE_CASE		)
    if len(_SCREAMING_SNAKE_CASE		) > 0:
      lowercase__           =  full_error_msg + begin_error_msg + str(_SCREAMING_SNAKE_CASE		)
    raise ValueError(_SCREAMING_SNAKE_CASE		)
  benchmark.run()


if __name__ == "__main__":
      main()









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowercase_          =		{
    """configuration_efficientformer""": [
        """EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientFormerConfig""",
    ]
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_          =		["""EfficientFormerImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_          =		[
          """EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """EfficientFormerForImageClassification""",
          """EfficientFormerForImageClassificationWithTeacher""",
          """EfficientFormerModel""",
          """EfficientFormerPreTrainedModel""",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_          =		[
          """TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TFEfficientFormerForImageClassification""",
          """TFEfficientFormerForImageClassificationWithTeacher""",
          """TFEfficientFormerModel""",
          """TFEfficientFormerPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_efficientformer import EfficientFormerImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_efficientformer import (
                EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                EfficientFormerForImageClassification,
                EfficientFormerForImageClassificationWithTeacher,
                EfficientFormerModel,
                EfficientFormerPreTrainedModel,
            )
      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_efficientformer import (
                TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFEfficientFormerForImageClassification,
                TFEfficientFormerForImageClassificationWithTeacher,
                TFEfficientFormerModel,
                TFEfficientFormerPreTrainedModel,
            )

else:
      import sys

      lowercase_          =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


