


"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase_     :     List[str]    		=						{
    """configuration_wav2vec2_conformer""": [
        """WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Wav2Vec2ConformerConfig""",
    ],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase_     :     Tuple    		=						[
           """WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """Wav2Vec2ConformerForAudioFrameClassification""",
           """Wav2Vec2ConformerForCTC""",
           """Wav2Vec2ConformerForPreTraining""",
           """Wav2Vec2ConformerForSequenceClassification""",
           """Wav2Vec2ConformerForXVector""",
           """Wav2Vec2ConformerModel""",
           """Wav2Vec2ConformerPreTrainedModel""",
       ]

if TYPE_CHECKING:
       from .configuration_wavaveca_conformer import (
           WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
           WavaVecaConformerConfig,
       )

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_wavaveca_conformer import (
                  WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  WavaVecaConformerForAudioFrameClassification,
                  WavaVecaConformerForCTC,
                  WavaVecaConformerForPreTraining,
                  WavaVecaConformerForSequenceClassification,
                  WavaVecaConformerForXVector,
                  WavaVecaConformerModel,
                  WavaVecaConformerPreTrainedModel,
              )

else:
       import sys

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



"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase_     :     Any    		=						{"""configuration_dinat""": ["""DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DinatConfig"""]}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase_     :     List[str]    		=						[
           """DINAT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """DinatForImageClassification""",
           """DinatModel""",
           """DinatPreTrainedModel""",
           """DinatBackbone""",
       ]

if TYPE_CHECKING:
       from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_dinat import (
                  DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DinatBackbone,
                  DinatForImageClassification,
                  DinatModel,
                  DinatPreTrainedModel,
              )

else:
       import sys

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