647580b3da745899695341fcbca2ec69eb4df8ef,benchmark/kernel/train_eval.py,,cross_validation_with_val_set,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,13

Before Change

    print("Val Loss: {:.4f}, Test Accuracy: {:.3f} ± {:.3f}, Duration: {:.3f}".
          format(loss.mean().item(),
                 acc.mean().item(),
                 acc.std().item(),
                 duration.mean().item()))

    return loss.mean().item(), acc.mean().item(), acc.std().item()

After Change

    loss, argmin = loss.min(dim=1)
    accs = accs[torch.arange(folds, dtype=torch.long), argmin]

    loss_mean = loss.mean().item()
    accs_mean = accs.mean().item()
    accs_std  = accs.std().item()
    print("Val Loss: {:.4f}, Test Accuracy: {:.3f} ± {:.3f}, Duration: {:.3f}".
          format(loss_mean,
                 accs_mean,
                 accs_std,
                 duration.mean().item()))

    return loss_mean, accs_mean, accs_std


def k_fold(dataset, folds):

Instances