


from ..utils import DummyObject, requires_backends



class 				A       (			metaclass=UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					['''torch''', '''transformers''', '''onnx''']

					def __init__(self       :		str ,   *_UpperCAmelCase       :		Tuple ,   **_UpperCAmelCase       :		Optional[int]						)		->  Optional[Any]:




							"""simple docstring"""


							requires_backends(self ,   ["""torch""", """transformers""", """onnx"""]						)

					@classmethod
					def     lowerCamelCase__	(cls       :		str ,   *_UpperCAmelCase       :		List[Any] ,   **_UpperCAmelCase       :		Optional[int]						)		->  Optional[Any]:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)


					@classmethod
					def     lowerCamelCase__	(cls       :		Tuple ,   *_UpperCAmelCase       :		int ,   **_UpperCAmelCase       :		Tuple						)		->  Optional[int]:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)






class 				A       (			metaclass=UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					['''torch''', '''transformers''', '''onnx''']

					def __init__(self       :		Optional[int] ,   *_UpperCAmelCase       :		int ,   **_UpperCAmelCase       :		Optional[int]						)		->  Union[str, Any]:




							"""simple docstring"""


							requires_backends(self ,   ["""torch""", """transformers""", """onnx"""]						)

					@classmethod
					def     lowerCamelCase__	(cls       :		Optional[Any] ,   *_UpperCAmelCase       :		Tuple ,   **_UpperCAmelCase       :		int						)		->  Tuple:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)


					@classmethod
					def     lowerCamelCase__	(cls       :		str ,   *_UpperCAmelCase       :		Dict ,   **_UpperCAmelCase       :		Any						)		->  int:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)






class 				A       (			metaclass=UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					['''torch''', '''transformers''', '''onnx''']

					def __init__(self       :		Any ,   *_UpperCAmelCase       :		Tuple ,   **_UpperCAmelCase       :		Tuple						)		->  int:




							"""simple docstring"""


							requires_backends(self ,   ["""torch""", """transformers""", """onnx"""]						)

					@classmethod
					def     lowerCamelCase__	(cls       :		Union[str, Any] ,   *_UpperCAmelCase       :		str ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  Union[str, Any]:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)


					@classmethod
					def     lowerCamelCase__	(cls       :		Any ,   *_UpperCAmelCase       :		Tuple ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  Union[str, Any]:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)






class 				A       (			metaclass=UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					['''torch''', '''transformers''', '''onnx''']

					def __init__(self       :		Dict ,   *_UpperCAmelCase       :		Optional[int] ,   **_UpperCAmelCase       :		List[str]						)		->  Dict:




							"""simple docstring"""


							requires_backends(self ,   ["""torch""", """transformers""", """onnx"""]						)

					@classmethod
					def     lowerCamelCase__	(cls       :		List[Any] ,   *_UpperCAmelCase       :		int ,   **_UpperCAmelCase       :		List[str]						)		->  List[Any]:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)


					@classmethod
					def     lowerCamelCase__	(cls       :		Optional[int] ,   *_UpperCAmelCase       :		Optional[int] ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  Tuple:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)






class 				A       (			metaclass=UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					['''torch''', '''transformers''', '''onnx''']

					def __init__(self       :		List[Any] ,   *_UpperCAmelCase       :		Optional[int] ,   **_UpperCAmelCase       :		Tuple						)		->  Dict:




							"""simple docstring"""


							requires_backends(self ,   ["""torch""", """transformers""", """onnx"""]						)

					@classmethod
					def     lowerCamelCase__	(cls       :		Union[str, Any] ,   *_UpperCAmelCase       :		List[str] ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  str:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)


					@classmethod
					def     lowerCamelCase__	(cls       :		Optional[int] ,   *_UpperCAmelCase       :		Optional[Any] ,   **_UpperCAmelCase       :		List[str]						)		->  List[str]:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)






class 				A       (			metaclass=UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					['''torch''', '''transformers''', '''onnx''']

					def __init__(self       :		Optional[int] ,   *_UpperCAmelCase       :		Tuple ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  Optional[Any]:




							"""simple docstring"""


							requires_backends(self ,   ["""torch""", """transformers""", """onnx"""]						)

					@classmethod
					def     lowerCamelCase__	(cls       :		Union[str, Any] ,   *_UpperCAmelCase       :		Tuple ,   **_UpperCAmelCase       :		Optional[Any]						)		->  Any:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)


					@classmethod
					def     lowerCamelCase__	(cls       :		Tuple ,   *_UpperCAmelCase       :		List[str] ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  Optional[Any]:




							"""simple docstring"""


							requires_backends(cls ,   ["""torch""", """transformers""", """onnx"""]						)





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)

