


'''simple docstring'''
from typing import TYPE_CHECKING

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


__snake_case				 =	{
    '''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvNextConfig''', '''ConvNextOnnxConfig''']
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case				 =	['''ConvNextFeatureExtractor''']
		__snake_case				 =	['''ConvNextImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case				 =	[
		    '''CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ConvNextForImageClassification''',
		    '''ConvNextModel''',
		    '''ConvNextPreTrainedModel''',
		    '''ConvNextBackbone''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case				 =	[
		    '''TFConvNextForImageClassification''',
		    '''TFConvNextModel''',
		    '''TFConvNextPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_convnext import ConvNextFeatureExtractor
				from .image_processing_convnext import ConvNextImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_convnext import (
				    CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ConvNextBackbone,
				    ConvNextForImageClassification,
				    ConvNextModel,
				    ConvNextPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
		import sys

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



'''simple docstring'''
from __future__ import annotations

from math import pi, sqrt


def      a (     __a					,   __a  )    ->      tuple:



					'''simple docstring'''






					if inductance <= 0:
										raise ValueError('''Inductance cannot be 0 or negative'''  )

					elif capacitance <= 0:
										raise ValueError('''Capacitance cannot be 0 or negative'''  )

					else:
										return (
										    "Resonant frequency",
										    float(1 / (2 * pi * (sqrt(inductance * capacitance  )))  ),
										)


if __name__ == "__main__":
		import doctest

		doctest.testmod()