pytorchvideo_trainer/pytorchvideo_trainer/module/byol.py [235:255]:
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    def __init__(
        self,
        model: Any,  # pyre-ignore[2]
        loss: Any,  # pyre-ignore[2]
        optim: Any,  # pyre-ignore[2]
        metrics: List[Any],  # pyre-ignore[2]
        lr_scheduler: Optional[Any] = None,  # pyre-ignore[2]
        modality_key: BatchKey = "video",
        ensemble_method: Optional[EnsembleMethod] = None,
        knn_memory: Optional[Any] = None,  # pyre-ignore[2]
        momentum_anneal_cosine: bool = False,
        num_sync_devices: int = 1,
    ) -> None:
        super().__init__(
            model=model,
            loss=loss,
            optim=optim,
            metrics=metrics,
            lr_scheduler=lr_scheduler,
            modality_key=modality_key,
            ensemble_method=ensemble_method,
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pytorchvideo_trainer/pytorchvideo_trainer/module/ssl_helper.py [349:369]:
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    def __init__(
        self,
        model: Any,  # pyre-ignore[2]
        loss: Any,  # pyre-ignore[2]
        optim: Any,  # pyre-ignore[2]
        metrics: List[Any],  # pyre-ignore[2]
        lr_scheduler: Optional[Any] = None,  # pyre-ignore[2]
        modality_key: BatchKey = "video",
        ensemble_method: Optional[EnsembleMethod] = None,
        knn_memory: Optional[Any] = None,  # pyre-ignore[2]
        momentum_anneal_cosine: bool = False,  # TODO: Refactor out mmt from base class.
        num_sync_devices: int = 1,
    ) -> None:
        super().__init__(
            model=model,
            loss=loss,
            optim=optim,
            metrics=metrics,
            lr_scheduler=lr_scheduler,
            modality_key=modality_key,
            ensemble_method=ensemble_method,
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