


"""simple docstring"""







import warnings

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


__lowercase    					=      logging.get_logger(__name__)






class 						_A  (  _a  ):







    """simple docstring"""




    def __init__(					self				:    List[Any]				, *__UpperCAmelCase				:    Optional[Any]				, **__UpperCAmelCase				:    Optional[Any]):
      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_tf_available, is_torch_available


__lowercase    					=      {
    """configuration_rag""": ["""RagConfig"""],
    """retrieval_rag""": ["""RagRetriever"""],
    """tokenization_rag""": ["""RagTokenizer"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowercase    					=      [
     """RagModel""",
     """RagPreTrainedModel""",
     """RagSequenceForGeneration""",
     """RagTokenForGeneration""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowercase    					=      [
     """TFRagModel""",
     """TFRagPreTrainedModel""",
     """TFRagSequenceForGeneration""",
     """TFRagTokenForGeneration""",
 ]


if TYPE_CHECKING:
 from .configuration_rag import RagConfig
 from .retrieval_rag import RagRetriever
 from .tokenization_rag import RagTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_rag import (
      TFRagModel,
      TFRagPreTrainedModel,
      TFRagSequenceForGeneration,
      TFRagTokenForGeneration,
  )

else:
 import sys

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






