


from typing import TYPE_CHECKING

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


__UpperCamelCase				:  Dict      					=							{
    'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ResNetConfig', 'ResNetOnnxConfig']
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase				:  Optional[int]      					=							[
           'RESNET_PRETRAINED_MODEL_ARCHIVE_LIST',
           'ResNetForImageClassification',
           'ResNetModel',
           'ResNetPreTrainedModel',
           'ResNetBackbone',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase				:  int      					=							[
           'TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFResNetForImageClassification',
           'TFResNetModel',
           'TFResNetPreTrainedModel',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase				:  List[str]      					=							[
           'FlaxResNetForImageClassification',
           'FlaxResNetModel',
           'FlaxResNetPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_resnet import (
                  RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ResNetBackbone,
                  ResNetForImageClassification,
                  ResNetModel,
                  ResNetPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_resnet import (
                  TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFResNetForImageClassification,
                  TFResNetModel,
                  TFResNetPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
       import sys

       __UpperCamelCase				:  Tuple      					=							_LazyModule(__name__, globals()['__file__'], _import_structure)



def      snake_case_						( __lowercase       ):
   return " ".join(
       ''''''.join(word[::-1]       ) if len(__lowercase       ) > 4 else word for word in sentence.split()       )


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(reverse_long_words('Hey wollef sroirraw'))