MKLPardisoKKTSolver not correctly exported in namespace

[Sage0614]

I am trying to use MKLPardisoKKTSolver in JuMP

model = JuMP.Model(optimizer_with_attributes(COSMO.Optimizer, "kkt_solver" => with_options(PardisoDirectKKTSolver, msg_level_on = true));

and getting the error message UndefVarError: MKLPardisoKKTSolver not defined

I think the problem is with this file:

COSMO.jl/src/linear_solver/kktsolver_pardiso.jl

Line 3 in 8689f76

export PardisoDirectKKTSolver, PardisoIndirectKKTSolver, MKLPardisoSolver

MKLPardisoKKTSolver rather than MKLPardisoSolver should be exported to namespace.

Thanks,

[migarstka]

Hi @Sage0614,

You are right, I fixed it in this commit 8d0f108: (will be part of new releave v0.8.6):
If you checkout the commit or the master branch, the following script should work:

(Notice you need to load Pardiso using Pardiso independently.

using Pardiso, COSMO, JuMP, LinearAlgebra, SparseArrays, Test, Random

rng = Random.MersenneTwister(12345);
## create a random test matrix C
n = 8;
C = -1 .+ rand(rng, n, n) .* 2;
c = vec(C);

# Define problem in `JuMP`:
q = -vec(C);
r = 0.5 * vec(C)' * vec(C);
m = JuMP.Model(optimizer_with_attributes(COSMO.Optimizer, "verbose" => true, "kkt_solver" => MKLPardisoKKTSolver));
@variable(m, X[1:n, 1:n], PSD);
x = vec(X);
@objective(m, Min, 0.5 * x' * x  + q' * x + r);
for i = 1:n
  @constraint(m, X[i, i] == 1.);
end

# Solve the `JuMP` model with `COSMO` and query the solution `X_sol`:
status = JuMP.optimize!(m);
obj_val = JuMP.objective_value(m);
X_sol = JuMP.value.(X);

[Sage0614]

Hi @Sage0614,

You are right, I fixed it in this commit 8d0f108: (will be part of new releave v0.8.6): If you checkout the commit or the master branch, the following script should work:

(Notice you need to load Pardiso using Pardiso independently.

using Pardiso, COSMO, JuMP, LinearAlgebra, SparseArrays, Test, Random

rng = Random.MersenneTwister(12345);
## create a random test matrix C
n = 8;
C = -1 .+ rand(rng, n, n) .* 2;
c = vec(C);

# Define problem in `JuMP`:
q = -vec(C);
r = 0.5 * vec(C)' * vec(C);
m = JuMP.Model(optimizer_with_attributes(COSMO.Optimizer, "verbose" => true, "kkt_solver" => MKLPardisoKKTSolver));
@variable(m, X[1:n, 1:n], PSD);
x = vec(X);
@objective(m, Min, 0.5 * x' * x  + q' * x + r);
for i = 1:n
  @constraint(m, X[i, i] == 1.);
end

# Solve the `JuMP` model with `COSMO` and query the solution `X_sol`:
status = JuMP.optimize!(m);
obj_val = JuMP.objective_value(m);
X_sol = JuMP.value.(X);

That works fine for me, think you can close the issue.