
"""simple docstring"""


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)

"""simple docstring"""


import unittest
import warnings

from datasets.utils import experimental






@experimental
def      lowerCAmelCase_     (	)     ->Optional[Any]:
			return "success"

class 					A_			(  unittest.TestCase     ):



							"""simple docstring"""






							def    UpperCAmelCase__							(						self						:int ):





										"""simple docstring"""

										with warnings.catch_warnings(record=lowerCamelCase_ ) as w:
													warnings.simplefilter('always' )
													self.assertEqual(dummy_function()  ,							'success' )
										self.assertEqual(len(lowerCamelCase_ )  ,							1 )