






import warnings

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


snake_case    				=		logging.get_logger(__name__)


class  SCREAMING_SNAKE_CASE			(			lowerCAmelCase					):
     '''simple docstring'''


     def __init__(				self       :	Any					, *UpperCAmelCase_       :	Dict					, **UpperCAmelCase_       :	List[Any]      ):
       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_      )














from typing import TYPE_CHECKING

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


snake_case    				=		{"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   snake_case    				=		[
       """SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """SwinForImageClassification""",
       """SwinForMaskedImageModeling""",
       """SwinModel""",
       """SwinPreTrainedModel""",
       """SwinBackbone""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   snake_case    				=		[
       """TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """TFSwinForImageClassification""",
       """TFSwinForMaskedImageModeling""",
       """TFSwinModel""",
       """TFSwinPreTrainedModel""",
   ]

if TYPE_CHECKING:
   from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_swin import (
          SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          SwinBackbone,
          SwinForImageClassification,
          SwinForMaskedImageModeling,
          SwinModel,
          SwinPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_swin import (
          TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFSwinForImageClassification,
          TFSwinForMaskedImageModeling,
          TFSwinModel,
          TFSwinPreTrainedModel,
      )

else:
   import sys

   snake_case    				=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






