


'''simple docstring'''




from typing import TYPE_CHECKING

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


_a   :   Any												=   {
    "configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig", "ResNetOnnxConfig"]
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _a   :   Union[str, Any]												=   [
           "RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
           "ResNetForImageClassification",
           "ResNetModel",
           "ResNetPreTrainedModel",
           "ResNetBackbone",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _a   :   List[str]												=   [
           "TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFResNetForImageClassification",
           "TFResNetModel",
           "TFResNetPreTrainedModel",
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _a   :   Any												=   [
           "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

       _a   :   List[str]												=   _LazyModule(__name__, globals()["__file__"], _import_structure)











from ..utils import DummyObject, requires_backends





class 				a			(      metaclass=__lowercase			):
				SCREAMING_SNAKE_CASE__     :   List[Any]		      =     ['''torch''', '''scipy''']






				def __init__(  self			, *_lowerCAmelCase			, **_lowerCAmelCase					):

										"""simple docstring"""




										requires_backends(self			, ['''torch''', '''scipy''']					)






				@classmethod
				def 			snake_case_    (  cls			, *_lowerCAmelCase			, **_lowerCAmelCase					):

										"""simple docstring"""




										requires_backends(cls			, ['''torch''', '''scipy''']					)






				@classmethod
				def 			snake_case_    (  cls			, *_lowerCAmelCase			, **_lowerCAmelCase					):

										"""simple docstring"""




										requires_backends(cls			, ['''torch''', '''scipy''']					)



