



'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase		     =  {
    '''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetConfig''', '''ResNetOnnxConfig''']
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase		     =  [
							    '''RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''ResNetForImageClassification''',
							    '''ResNetModel''',
							    '''ResNetPreTrainedModel''',
							    '''ResNetBackbone''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase		     =  [
							    '''TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFResNetForImageClassification''',
							    '''TFResNetModel''',
							    '''TFResNetPreTrainedModel''',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase		     =  [
							    '''FlaxResNetForImageClassification''',
							    '''FlaxResNetModel''',
							    '''FlaxResNetPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_resnet import (
														    RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ResNetBackbone,
														    ResNetForImageClassification,
														    ResNetModel,
														    ResNetPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_resnet import (
														    TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFResNetForImageClassification,
														    TFResNetModel,
														    TFResNetPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
							import sys

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









'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


__lowerCAmelCase		     =  logging.get_logger(__name__)

class       __magic_name__		(       _UpperCamelCase  ):







							def __init__(				self   :			Tuple      ,*_UpperCAmelCase   :			str      ,**_UpperCAmelCase   :			int						):
									warnings.warn(
									    'The class DeiTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
									    ' use DeiTImageProcessor instead.'      ,_UpperCAmelCase      ,)
									super().__init__(*_UpperCAmelCase      ,**_UpperCAmelCase						)




