def METHOD_NAME():
    data = HeteroData()
    data['paper'].x = torch.randn(2000, 16)
    data['paper'].y = torch.randint(4, (2000, ), dtype=torch.long)
    data['author'].x = torch.randn(300, 16)
    transform = RandomNodeSplit()
    assert str(transform) == 'RandomNodeSplit(split=train_rest)'
    data = transform(data)
    assert len(data) == 5
    assert len(data['author']) == 1
    assert len(data['paper']) == 5
    assert data['paper'].train_mask.sum() == 500
    assert data['paper'].val_mask.sum() == 500
    assert data['paper'].test_mask.sum() == 1000