Memory leak exists when using fix_vertices

[ArrogantGao]

I found that there exists a memory leak when using fix_vertices function, in the following MWE, the memory usage of the process will grow monotonically until it is killed.
I use the htop tool to check the memory usage, I would be glad to do more tests if you guys know better way to record the memory usage.

using KaHyPar, Graphs, SparseArrays

function edge2vertex(g::SimpleGraph)
    I = Int[]
    J = Int[]
    edgecount = 0
    @inbounds for i in 1:nv(g)-1, j in g.fadjlist[i]
        if j > i
            edgecount += 1
            push!(I, i)
            push!(I, j)
            push!(J, edgecount)
            push!(J, edgecount)
        end
    end
    return sparse(I, J, ones(length(I)))
end

function select_region(g, i, n)
    h = KaHyPar.HyperGraph(edge2vertex(g))
    imbalance = 1 - 2 * n / nv(g)

    local fix_vs = [j == i ? 1 : -1 for j in 1:nv(g)]
    KaHyPar.fix_vertices(h, 2, fix_vs)
    KaHyPar.set_target_block_weights(h, [nv(g) - n, n])

    parts = KaHyPar.partition(h, 2)
    return findall(!iszero, parts)
end

g = random_regular_graph(1000, 3)

while true
    for i in 1:1000
        select_region(g, i, 15)
    end
end

[YijiawWang]

I think that this issue might stem from the conflict between functions KaHyPar.fix_vertices and KaHyPar.set_target_block_weights, as the memory leak only occurs when they are used simultaneously.

[ArrogantGao]

I think that this issue might stem from the conflict between functions KaHyPar.fix_vertices and KaHyPar.set_target_block_weights, as the memory leak only occurs when they are used simultaneously.

I don't think so, actually I obseved that solely using fix_vertices will cause memory leak.

[SebastianSchlag]

Thanks for reporting this. @jalving do you have any idea what could be going wrong?