


import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union



@dataclass
class 				A       :
					'''simple docstring'''






					A__     =					None
					A__     =					False
					A__     =					False
					A__     =					False
					A__     =					None
					A__     =					None
					A__     =					False
					A__     =					False
					A__     =					False
					A__     =					True
					A__     =					None
					A__     =					1
					A__     =					None
					A__     =					False
					A__     =					None
					A__     =					None

					def     lowerCamelCase__	(self       :		int						)		->  "DownloadConfig":




							"""simple docstring"""


							return self.__class__(**{k: copy.deepcopy(_UpperCAmelCase						) for k, v in self.__dict__.items()}						)





from typing import TYPE_CHECKING

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


A			:						Union[str, Any]        =  {
    'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNextConfig', 'ConvNextOnnxConfig']
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A			:						str        =  ['ConvNextFeatureExtractor']
	A			:						Optional[Any]        =  ['ConvNextImageProcessor']

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

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A			:						List[str]        =  [
	    '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

	A			:						int        =  _LazyModule(__name__, globals()['__file__'], _import_structure)

