





"""simple docstring"""


from typing import TYPE_CHECKING

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


a__					:     Tuple							=				{"""configuration_regnet""": ["""REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RegNetConfig"""]}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__					:     Optional[int]							=				[
       """REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """RegNetForImageClassification""",
       """RegNetModel""",
       """RegNetPreTrainedModel""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__					:     List[Any]							=				[
       """TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """TFRegNetForImageClassification""",
       """TFRegNetModel""",
       """TFRegNetPreTrainedModel""",
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__					:     Optional[Any]							=				[
       """FlaxRegNetForImageClassification""",
       """FlaxRegNetModel""",
       """FlaxRegNetPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_regnet import (
          REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          RegNetForImageClassification,
          RegNetModel,
          RegNetPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_regnet import (
          TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFRegNetForImageClassification,
          TFRegNetModel,
          TFRegNetPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_regnet import (
          FlaxRegNetForImageClassification,
          FlaxRegNetModel,
          FlaxRegNetPreTrainedModel,
      )


else:
   import sys

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








"""simple docstring"""


def 							a__			(  _UpperCAmelCase	)    ->  int:

 '''simple docstring'''






 return int(_UpperCAmelCase	) if x - int(_UpperCAmelCase	) <= 0 else int(_UpperCAmelCase	) + 1


if __name__ == "__main__":
   import doctest

   doctest.testmod()

