




from typing import TYPE_CHECKING

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


_lowerCamelCase			 =						{'configuration_regnet': ['REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RegNetConfig']}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase			 =						[
     'REGNET_PRETRAINED_MODEL_ARCHIVE_LIST',
     'RegNetForImageClassification',
     'RegNetModel',
     'RegNetPreTrainedModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase			 =						[
     'TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFRegNetForImageClassification',
     'TFRegNetModel',
     'TFRegNetPreTrainedModel',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase			 =						[
     '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

 _lowerCamelCase			 =						_LazyModule(__name__, globals()['__file__'], _import_structure)











from __future__ import annotations




def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						list[int | float]      )  ->							int | float:
    if len(__UpperCamelCase      ) == 0:
        raise ValueError('''find_max() arg is an empty sequence'''      )
    UpperCAmelCase_							 =     nums[0]
    for x in nums:
        if x > max_num:
            UpperCAmelCase_							 =     x
    return max_num


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)





