def METHOD_NAME(data):
    edge_mask = torch.tensor([1., 0., 1., 0., 0., 1.])
    explanation = Explanation(
        edge_mask=edge_mask,
        x=data.x,
        edge_index=data.edge_index,
        edge_attr=data.edge_attr,
    )
    explanation.validate(raise_on_error=True)
    out = explanation.get_explanation_subgraph()
    assert out.x.size() == (4, 3)
    assert out.edge_mask.size() == (3, )
    assert (out.edge_mask > 0.0).sum() == 3
    assert out.edge_index.size() == (2, 3)
    assert out.edge_attr.size() == (3, 3)
    out = explanation.get_complement_subgraph()
    assert out.x.size() == (4, 3)
    assert out.edge_mask.size() == (3, )
    assert (out.edge_mask == 0.0).sum() == 3
    assert out.edge_index.size() == (2, 3)
    assert out.edge_attr.size() == (3, 3)