


'''simple docstring'''



from typing import TYPE_CHECKING

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


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

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

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

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__A		=[
		    '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		=_LazyModule(__name__, globals()['__file__'], _import_structure)



import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


lowerCAmelCase__      		= logging.get_logger(__name__)







class      lowerCAmelCase__       (				a):




     '''simple docstring'''


     def __init__(						self ,						*__lowerCamelCase ,						**__lowerCamelCase)			->				None:
            warnings.warn(
                "The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
                " use BeitImageProcessor instead." ,						__lowerCamelCase ,						)
            super().__init__(*__lowerCamelCase ,						**__lowerCamelCase)
