
from typing import TYPE_CHECKING

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


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

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

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

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase					   =       [
							    '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

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

import warnings

from ...utils import logging
from .image_processing_yolos import YolosImageProcessor


__lowerCAmelCase					   =       logging.get_logger(__name__)





class     lowerCamelCase      (       __lowerCamelCase					):







	def __init__(     self      :List[Any]   ,     *lowercase      :List[str]   ,     **lowercase      :List[Any]			)		->      None:







				"""simple docstring"""






				warnings.warn(
				    '''The class YolosFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
				    ''' use YolosImageProcessor instead.'''   ,     lowercase   ,     )
				super().__init__(*lowercase   ,     **lowercase			)