





'''simple docstring'''


import warnings

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


lowerCAmelCase					:     Tuple												=logging.get_logger(__name__)
class       a_   (				_lowerCAmelCase							):





     def __init__( self		:					Union[str, Any]	,      *lowercase		:					Dict	,      **lowercase		:					Any						):





        """simple docstring"""




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









'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase					:     Optional[Any]												={
    '''configuration_x_clip''': [
        '''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XCLIPConfig''',
        '''XCLIPTextConfig''',
        '''XCLIPVisionConfig''',
    ],
    '''processing_x_clip''': ['''XCLIPProcessor'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase					:     Tuple												=[
     '''XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''XCLIPModel''',
     '''XCLIPPreTrainedModel''',
     '''XCLIPTextModel''',
     '''XCLIPVisionModel''',
 ]

if TYPE_CHECKING:
 from .configuration_x_clip import (
     XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
     XCLIPConfig,
     XCLIPTextConfig,
     XCLIPVisionConfig,
 )
 from .processing_x_clip import XCLIPProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_x_clip import (
      XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
      XCLIPModel,
      XCLIPPreTrainedModel,
      XCLIPTextModel,
      XCLIPVisionModel,
  )

else:
 import sys

 lowerCAmelCase					:     str												=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


