




"""simple docstring"""




from typing import TYPE_CHECKING

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


lowerCAmelCase							:    int  							=							{
    """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							:    Union[str, Any]  							=							[
					    """DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """Data2VecAudioForAudioFrameClassification""",
					    """Data2VecAudioForCTC""",
					    """Data2VecAudioForSequenceClassification""",
					    """Data2VecAudioForXVector""",
					    """Data2VecAudioModel""",
					    """Data2VecAudioPreTrainedModel""",
					]
					lowerCAmelCase							:    str  							=							[
					    """DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """Data2VecTextForCausalLM""",
					    """Data2VecTextForMaskedLM""",
					    """Data2VecTextForMultipleChoice""",
					    """Data2VecTextForQuestionAnswering""",
					    """Data2VecTextForSequenceClassification""",
					    """Data2VecTextForTokenClassification""",
					    """Data2VecTextModel""",
					    """Data2VecTextPreTrainedModel""",
					]
					lowerCAmelCase							:    Tuple  							=							[
					    """DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """Data2VecVisionForImageClassification""",
					    """Data2VecVisionForMaskedImageModeling""",
					    """Data2VecVisionForSemanticSegmentation""",
					    """Data2VecVisionModel""",
					    """Data2VecVisionPreTrainedModel""",
					]

if is_tf_available():
					lowerCAmelCase							:    Any  							=							[
					    """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"""




from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase							:    List[str]  							=							{
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase							:    Tuple  							=							[
					    """AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """AutoformerForPrediction""",
					    """AutoformerModel""",
					    """AutoformerPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_autoformer import (
					    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    AutoformerConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_autoformer import (
										    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    AutoformerForPrediction,
										    AutoformerModel,
										    AutoformerPreTrainedModel,
										)

else:
					import sys

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



