

import warnings

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


lowerCAmelCase_			      =      logging.get_logger(__name__)





class       snake_case_  (						__A   ):







			'''simple docstring'''

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







'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase									=   {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase									=   [
		    'SEW_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'SEWForCTC',
		    'SEWForSequenceClassification',
		    'SEWModel',
		    'SEWPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_sew import (
				    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SEWForCTC,
				    SEWForSequenceClassification,
				    SEWModel,
				    SEWPreTrainedModel,
				)


else:
		import sys

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




