


'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCAmelCase				:Optional[Any]        =      {
    '''configuration_poolformer''': [
        '''POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''PoolFormerConfig''',
        '''PoolFormerOnnxConfig''',
    ]
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase				:int        =      ['''PoolFormerFeatureExtractor''']
							lowerCAmelCase				:Tuple        =      ['''PoolFormerImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase				:List[str]        =      [
							    '''POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''PoolFormerForImageClassification''',
							    '''PoolFormerModel''',
							    '''PoolFormerPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_poolformer import (
							    POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    PoolFormerConfig,
							    PoolFormerOnnxConfig,
							)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_poolformer import PoolFormerFeatureExtractor
														from .image_processing_poolformer import PoolFormerImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_poolformer import (
														    POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    PoolFormerForImageClassification,
														    PoolFormerModel,
														    PoolFormerPreTrainedModel,
														)


else:
							import sys

							lowerCAmelCase				:List[Any]        =      _LazyModule(__name__, globals()['''__file__'''], _import_structure)



'''simple docstring'''

import warnings

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


lowerCAmelCase				:Tuple        =      logging.get_logger(__name__)
class _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		def __init__( self		:						Any  ,					*_A		:						List[Any]  ,					**_A		:						str      )  ->			None:
			warnings.warn(
			    'The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
			    ' use BeitImageProcessor instead.'  ,					_A  ,					)
			super().__init__(*_A  ,					**_A      )