


"""simple docstring"""



from typing import TYPE_CHECKING

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


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

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

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

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

  __snake_case       =       _LazyModule(__name__, globals()["""__file__"""], _import_structure)












def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__=2_81_23						):
		lowerCamelCase_	:     Any 						=      [1] * (limit + 1)

		for i in range(2							,int(limit**0.5						) + 1						):
				sum_divs[i * i] += i
				for k in range(i + 1							,limit // i + 1						):
						sum_divs[k * i] += k + i

		lowerCamelCase_	:     List[str] 						=      set()
		lowerCamelCase_	:     List[str] 						=      0

		for n in range(1							,limit + 1						):
				if sum_divs[n] > n:
						abundants.add(lowerCAmelCase__						)

				if not any((n - a in abundants) for a in abundants						):
						res += n

		return res


if __name__ == "__main__":
		print(solution())
