


"""simple docstring"""







from typing import TYPE_CHECKING

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


lowerCamelCase_   :   Optional[Any]									=  {
    """configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Data2VecAudioConfig"""],
    """configuration_data2vec_text""": [
        """DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Data2VecTextConfig""",
        """Data2VecTextOnnxConfig""",
    ],
    """configuration_data2vec_vision""": [
        """DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Data2VecVisionConfig""",
        """Data2VecVisionOnnxConfig""",
    ],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase_   :   Optional[int]									=  [
           """DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """Data2VecAudioForAudioFrameClassification""",
           """Data2VecAudioForCTC""",
           """Data2VecAudioForSequenceClassification""",
           """Data2VecAudioForXVector""",
           """Data2VecAudioModel""",
           """Data2VecAudioPreTrainedModel""",
       ]
       lowerCamelCase_   :   Dict									=  [
           """DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """Data2VecTextForCausalLM""",
           """Data2VecTextForMaskedLM""",
           """Data2VecTextForMultipleChoice""",
           """Data2VecTextForQuestionAnswering""",
           """Data2VecTextForSequenceClassification""",
           """Data2VecTextForTokenClassification""",
           """Data2VecTextModel""",
           """Data2VecTextPreTrainedModel""",
       ]
       lowerCamelCase_   :   Union[str, Any]									=  [
           """DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """Data2VecVisionForImageClassification""",
           """Data2VecVisionForMaskedImageModeling""",
           """Data2VecVisionForSemanticSegmentation""",
           """Data2VecVisionModel""",
           """Data2VecVisionPreTrainedModel""",
       ]

if is_tf_available():
       lowerCamelCase_   :   List[str]									=  [
           """TFData2VecVisionForImageClassification""",
           """TFData2VecVisionForSemanticSegmentation""",
           """TFData2VecVisionModel""",
           """TFData2VecVisionPreTrainedModel""",
       ]

if TYPE_CHECKING:
       from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
       from .configuration_dataavec_text import (
           DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
           DataaVecTextConfig,
           DataaVecTextOnnxConfig,
       )
       from .configuration_dataavec_vision import (
           DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
           DataaVecVisionConfig,
           DataaVecVisionOnnxConfig,
       )

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_dataavec_audio import (
                  DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DataaVecAudioForAudioFrameClassification,
                  DataaVecAudioForCTC,
                  DataaVecAudioForSequenceClassification,
                  DataaVecAudioForXVector,
                  DataaVecAudioModel,
                  DataaVecAudioPreTrainedModel,
              )
              from .modeling_dataavec_text import (
                  DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DataaVecTextForCausalLM,
                  DataaVecTextForMaskedLM,
                  DataaVecTextForMultipleChoice,
                  DataaVecTextForQuestionAnswering,
                  DataaVecTextForSequenceClassification,
                  DataaVecTextForTokenClassification,
                  DataaVecTextModel,
                  DataaVecTextPreTrainedModel,
              )
              from .modeling_dataavec_vision import (
                  DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DataaVecVisionForImageClassification,
                  DataaVecVisionForMaskedImageModeling,
                  DataaVecVisionForSemanticSegmentation,
                  DataaVecVisionModel,
                  DataaVecVisionPreTrainedModel,
              )
       if is_tf_available():
              from .modeling_tf_dataavec_vision import (
                  TFDataaVecVisionForImageClassification,
                  TFDataaVecVisionForSemanticSegmentation,
                  TFDataaVecVisionModel,
                  TFDataaVecVisionPreTrainedModel,
              )

else:
       import sys

       lowerCamelCase_   :   List[Any]									=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





"""simple docstring"""


import os
from typing import Dict, List, Tuple, TypeVar, Union


A_						=				TypeVar('''T''')

A_						=				Union[List[T], Tuple[T, ...]]
A_						=				Union[T, List[T], Dict[str, T]]
A_						=				Union[str, bytes, os.PathLike]


