f4beaac559e00a3676d942dc7e8fea69efc01cfe,catalyst/metrics/tests/test_ndcg.py,,test_dcg,#,10

Before Change

    y_true = [2.0, 2.0, 1.0, 0.0]
    y_pred = np.arange(3, -1, -1)

    dcg_at4 = metrics.dcg(
        torch.tensor([y_pred]), torch.tensor([y_true]), gain_function="rank"
    )
    assert torch.isclose(dcg_at4, torch.tensor(4.631), atol=0.05)

    y_true = [3, 2, 3, 0, 0, 1, 2, 2, 3, 0]
    y_pred = np.arange(9, -1, -1)

After Change

    y_true = [2.0, 2.0, 1.0, 0.0]
    y_pred = np.arange(3, -1, -1)

    dcg_at4 = torch.sum(
        metrics.dcg(
            torch.tensor([y_pred]),
            torch.tensor([y_true]),
            gain_function="linear_rank",
        )
    )
    assert torch.isclose(dcg_at4, torch.tensor(4.631), atol=0.05)

    y_true = [3, 2, 3, 0, 0, 1, 2, 2, 3, 0]
    y_pred = np.arange(9, -1, -1)

Instances