def METHOD_NAME(reverse_row, reverse_column):
    node_pairs = (torch.tensor([0, 2, 3]), torch.tensor([1, 4, 2]))
    if reverse_row:
        reverse_row_node_ids = torch.tensor([10, 15, 11, 24, 9])
        src_to_exclude = torch.tensor([11])
    else:
        reverse_row_node_ids = None
        src_to_exclude = torch.tensor([2])
    if reverse_column:
        reverse_column_node_ids = torch.tensor([10, 15, 11, 24, 9])
        dst_to_exclude = torch.tensor([9])
    else:
        reverse_column_node_ids = None
        dst_to_exclude = torch.tensor([4])
    reverse_edge_ids = torch.Tensor([5, 9, 10])
    subgraph = SampledSubgraphImpl(
        node_pairs,
        reverse_column_node_ids,
        reverse_row_node_ids,
        reverse_edge_ids,
    )
    edges_to_exclude = (src_to_exclude, dst_to_exclude)
    result = exclude_edges(subgraph, edges_to_exclude)
    expected_node_pairs = (torch.tensor([0, 3]), torch.tensor([1, 2]))
    if reverse_row:
        expected_row_node_ids = torch.tensor([10, 15, 11, 24, 9])
    else:
        expected_row_node_ids = None
    if reverse_column:
        expected_column_node_ids = torch.tensor([10, 15, 11, 24, 9])
    else:
        expected_column_node_ids = None
    expected_edge_ids = torch.Tensor([5, 10])
    _assert_container_equal(result.node_pairs, expected_node_pairs)
    _assert_container_equal(
        result.reverse_column_node_ids, expected_column_node_ids
    )
    _assert_container_equal(result.reverse_row_node_ids, expected_row_node_ids)
    _assert_container_equal(result.reverse_edge_ids, expected_edge_ids)