def METHOD_NAME():
    instances = ["instance a", "instance b"]
    tracks = ["track a", "track b"]
    # columns are tracks
    # rows are instances
    cost_matrix = np.array([[10, 150], [50, 100]])
    match_tuples = k.match_tuples_from_match_function(
        cost_matrix=cost_matrix,
        row_items=instances,
        column_items=tracks,
        match_function=sleap.nn.tracker.components.first_choice_matching,
    )
    assert len(match_tuples) == 2
    assert ("instance a", "track a", 10) in match_tuples
    assert ("instance b", "track a", 50) in match_tuples
    match_by_track = k.match_dict_from_match_function(
        cost_matrix=cost_matrix,
        row_items=instances,
        column_items=tracks,
        match_function=sleap.nn.tracker.components.first_choice_matching,
    )
    assert len(match_by_track) == 1
    assert match_by_track["track a"] == "instance a"
    match_by_instance = k.match_dict_from_match_function(
        cost_matrix=cost_matrix,
        row_items=instances,
        column_items=tracks,
        match_function=sleap.nn.tracker.components.first_choice_matching,
        key_by_column=False,
    )
    assert len(match_by_instance) == 2
    assert match_by_instance["instance a"] == "track a"
    assert match_by_instance["instance b"] == "track a"
    # another cost matrix
    # make sure we get *best* match for each track, regardless of row order
    cost_matrix = np.array(
        [
            [50, 100],
            [10, 150],
        ]
    )
    match_by_track = k.match_dict_from_match_function(
        cost_matrix=cost_matrix,
        row_items=instances,
        column_items=tracks,
        match_function=sleap.nn.tracker.components.first_choice_matching,
    )
    assert len(match_by_track) == 1
    assert match_by_track["track a"] == "instance b"