def get_preds(self, ds_type:DatasetType=DatasetType.Valid, with_loss:bool=False, n_batch:Optional[int]=None, pbar:Optional[PBar]=None,
                  ordered:bool=False) -> List[Tensor]:
        "Return predictions and targets on the valid, train, or test set, depending on `ds_type`."
        self.model.reset()
        if ordered: np.random.seed(42)
        preds = super().get_preds(ds_type=ds_type, with_loss=with_loss, n_batch=n_batch, pbar=pbar)
        if ordered and hasattr(self.dl(ds_type), 'sampler'):
            np.random.seed(42)
            sampler = [i for i in self.dl(ds_type).sampler]
            reverse_sampler = np.argsort(sampler)
            preds = [p[reverse_sampler] for p in preds] 
        return(preds)
Return predictions and targets on the valid, train, or test set, depending on `ds_type`.