blegat
commented
3 years ago Can you reduce it to an example using the MOI wrapper directly without Convex ? Otherwise, it may be an issue with Convex. Trying a simple example work:
julia> using MosekTools
julia> model = Mosek.Optimizer()
MosekModel
julia> const MOI = MosekTools.MOI
MathOptInterface
julia> x = MOI.SingleVariable(MOI.add_variable(model))
MathOptInterface.SingleVariable(MathOptInterface.VariableIndex(1))
julia> y = MOI.SingleVariable(MOI.add_variable(model))
MathOptInterface.SingleVariable(MathOptInterface.VariableIndex(2))
julia> cx = MOI.add_constraint(model, x, MOI.GreaterThan(0.0))
MathOptInterface.ConstraintIndex{MathOptInterface.SingleVariable,MathOptInterface.GreaterThan{Float64}}(1)
julia> cy = MOI.add_constraint(model, y, MOI.GreaterThan(0.0))
MathOptInterface.ConstraintIndex{MathOptInterface.SingleVariable,MathOptInterface.GreaterThan{Float64}}(2)
julia> c = MOI.add_constraint(model, 1.0x + 1.0y, MOI.LessThan(1.0))
MathOptInterface.ConstraintIndex{MathOptInterface.ScalarAffineFunction{Float64},MathOptInterface.LessThan{Float64}}(1)
julia> MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
julia> MOI.set(model, MOI.ObjectiveFunction{typeof(1.0x)}(), 1.0x)
julia> MOI.optimize!(model)
Problem
Name :
Objective sense : min
Type : LO (linear optimization problem)
Constraints : 1
Cones : 0
Scalar variables : 2
Matrix variables : 0
Integer variables : 0
Optimizer started.
Presolve started.
Linear dependency checker started.
Linear dependency checker terminated.
Eliminator started.
Freed constraints in eliminator : 0
Eliminator terminated.
Eliminator started.
Freed constraints in eliminator : 0
Eliminator terminated.
Eliminator - tries : 2 time : 0.00
Lin. dep. - tries : 1 time : 0.00
Lin. dep. - number : 0
Presolve terminated. Time: 0.00
Optimizer terminated. Time: 0.00
2-element Array{MosekTools.MosekSolution,1}:
MosekTools.MosekSolution(Mosek.MSK_SOL_BAS, Mosek.MSK_SOL_STA_OPTIMAL, Mosek.MSK_PRO_STA_PRIM_AND_DUAL_FEAS, Mosek.Stakey[Mosek.MSK_SK_LOW, Mosek.MSK_SK_LOW], [0.0, 0.0], Array{Float64,1}[], [1.0, 0.0], [0.0, 0.0], Float64[], Mosek.Stakey[Mosek.MSK_SK_BAS], [0.0], [0.0], [0.0], [-0.0])
MosekTools.MosekSolution(Mosek.MSK_SOL_ITR, Mosek.MSK_SOL_STA_OPTIMAL, Mosek.MSK_PRO_STA_PRIM_AND_DUAL_FEAS, Mosek.Stakey[Mosek.MSK_SK_LOW, Mosek.MSK_SK_LOW], [0.0, 0.0], Array{Float64,1}[], [1.0, 0.0], [0.0, 0.0], [0.0, 0.0], Mosek.Stakey[Mosek.MSK_SK_SUPBAS], [0.0], [0.0], [0.0], [-0.0])
julia> MOI.optimize!(model)
Problem
Name :
Objective sense : min
Type : LO (linear optimization problem)
Constraints : 1
Cones : 0
Scalar variables : 2
Matrix variables : 0
Integer variables : 0
Optimizer started.
Optimizer terminated. Time: 0.00
2-element Array{MosekTools.MosekSolution,1}:
MosekTools.MosekSolution(Mosek.MSK_SOL_BAS, Mosek.MSK_SOL_STA_OPTIMAL, Mosek.MSK_PRO_STA_PRIM_AND_DUAL_FEAS, Mosek.Stakey[Mosek.MSK_SK_LOW, Mosek.MSK_SK_LOW], [0.0, 0.0], Array{Float64,1}[], [1.0, 0.0], [0.0, 0.0], Float64[], Mosek.Stakey[Mosek.MSK_SK_BAS], [0.0], [0.0], [0.0], [-0.0])
MosekTools.MosekSolution(Mosek.MSK_SOL_ITR, Mosek.MSK_SOL_STA_OPTIMAL, Mosek.MSK_PRO_STA_PRIM_AND_DUAL_FEAS, Mosek.Stakey[Mosek.MSK_SK_LOW, Mosek.MSK_SK_LOW], [0.0, 0.0], Array{Float64,1}[], [1.0, 0.0], [0.0, 0.0], [0.0, 0.0], Mosek.Stakey[Mosek.MSK_SK_SUPBAS], [0.0], [0.0], [0.0], [-0.0])
julia> MOI.get(model, MOI.ConstraintDual(), cx)
1.0
julia> MOI.get(model, MOI.ConstraintDual(), cy)
0.0
julia> MOI.get(model, MOI.ConstraintDual(), c)
-0.0
Here's a MWE