def METHOD_NAME():
    """See issue: https://github.com/Lightning-AI/torchmetrics/issues/2022."""
    target = torch.tensor([[10, 0, 0, 1, 5]])
    preds = torch.tensor([[0.1, 0, 0, 0, 0.1]])
    for k in [1, 3, 5]:
        assert torch.allclose(
            retrieval_normalized_dcg(preds, target, top_k=k),
            torch.tensor([ndcg_score(target, preds, k=k)], dtype=torch.float32),
        )