def METHOD_NAME(self):
    """Test decalin example."""
    # Decalin molecule from Fig 4 page 15 from the paper https://arxiv.org/pdf/2110.07875.pdf
    source, target = torch.as_tensor(
        [
            [1, 2, 3, 4, 5, 5, 0, 0, 6, 7, 8],
            [2, 3, 4, 5, 6, 0, 1, 9, 7, 8, 9],
        ]
    )
    # create triples with a dummy relation type 0
    decalin_triples = torch.stack([source, torch.zeros_like(source), target], dim=-1)
    templates = torch.as_tensor(
        data=[
            [0.0000, 0.5000, 0.0000, 0.3542, 0.0000],  # green
            [0.0000, 0.4167, 0.0000, 0.2824, 0.0000],  # red
            [0.0000, 0.4444, 0.0000, 0.3179, 0.0000],  # blue
        ],
    )
    # 0: green: 2, 3, 7, 8
    # 1: red: 1, 4, 6, 9
    # 2: blue: 0, 5
    colors = torch.as_tensor(data=[2, 1, 0, 0, 1, 2, 1, 0, 0, 1], dtype=torch.long)
    rwpe_vectors = templates[colors]
    initializer = pykeen.nn.init.RandomWalkPositionalEncodingInitializer(
        mapped_triples=decalin_triples,
        dim=5,
        # the example includes the first power
        skip_first_power=False,
    )
    assert torch.allclose(initializer.tensor, rwpe_vectors, rtol=1.0e-03)