





from typing import TYPE_CHECKING

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


__lowerCamelCase       :     Union[str, Any]   =     {
    """configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
    """tokenization_tapas""": ["""TapasTokenizer"""],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       :     Optional[Any]   =     [
        """TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """TapasForMaskedLM""",
        """TapasForQuestionAnswering""",
        """TapasForSequenceClassification""",
        """TapasModel""",
        """TapasPreTrainedModel""",
        """load_tf_weights_in_tapas""",
    ]
try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       :     Union[str, Any]   =     [
        """TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """TFTapasForMaskedLM""",
        """TFTapasForQuestionAnswering""",
        """TFTapasForSequenceClassification""",
        """TFTapasModel""",
        """TFTapasPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
    from .tokenization_tapas import TapasTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tapas import (
            TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
            TapasForMaskedLM,
            TapasForQuestionAnswering,
            TapasForSequenceClassification,
            TapasModel,
            TapasPreTrainedModel,
            load_tf_weights_in_tapas,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_tapas import (
            TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFTapasForMaskedLM,
            TFTapasForQuestionAnswering,
            TFTapasForSequenceClassification,
            TFTapasModel,
            TFTapasPreTrainedModel,
        )


else:
    import sys

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


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__   :			Optional[Any]												=    {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			int												=    [
					    "WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "WavLMForAudioFrameClassification",
					    "WavLMForCTC",
					    "WavLMForSequenceClassification",
					    "WavLMForXVector",
					    "WavLMModel",
					    "WavLMPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_wavlm import (
										    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
										    WavLMForAudioFrameClassification,
										    WavLMForCTC,
										    WavLMForSequenceClassification,
										    WavLMForXVector,
										    WavLMModel,
										    WavLMPreTrainedModel,
										)

else:
					import sys

					SCREAMING_SNAKE_CASE__   :			int												=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



