



from typing import TYPE_CHECKING

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


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

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

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

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

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






def      A_ (		__a       :			int = 1_000						):

				"""simple docstring"""
				return sum(i for i in range(__a						) if i % 3 == 0 or i % 5 == 0						)


if __name__ == "__main__":
	print(f"""{solution() = }""")

