Ipopt.jl/ext/IpoptMathOptInterfaceExt/IpoptMathOptInterfaceExt.jl at 2587a6a434917683340f25e47b8e69191876eeaf · jump-dev/Ipopt.jl · GitHub

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# Copyright (c) 2013: Iain Dunning, Miles Lubin, and contributors
#
# Use of this source code is governed by an MIT-style license that can be found
# in the LICENSE.md file or at https://opensource.org/licenses/MIT.

module IpoptMathOptInterfaceExt

import Ipopt
import MathOptInterface as MOI
import PrecompileTools

function __init__()
    setglobal!(Ipopt, :Optimizer, Optimizer)
    setglobal!(Ipopt, :CallbackFunction, CallbackFunction)
    setglobal!(Ipopt, :_VectorNonlinearOracle, _VectorNonlinearOracle)
    return
end

include("MOI_wrapper.jl")

#PrecompileTools.@setup_workload begin
#    PrecompileTools.@compile_workload begin
#        model = MOI.Utilities.CachingOptimizer(
#            MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()),
#            MOI.instantiate(Optimizer; with_bridge_type = Float64),
#        )
#        # We don't want to advertise this option, but it's required so that
#        # we don't print the banner during precompilation.
#        MOI.set(model, MOI.RawOptimizerAttribute("sb"), "yes")
#        MOI.set(model, MOI.Silent(), true)
#        x = MOI.add_variables(model, 3)
#        MOI.supports(model, MOI.VariableName(), typeof(x[1]))
#        MOI.set(model, MOI.VariableName(), x[1], "x1")
#        MOI.set(model, MOI.VariablePrimalStart(), x[1], 0.0)
#        for F in (MOI.VariableIndex, MOI.ScalarAffineFunction{Float64})
#            MOI.supports_constraint(model, F, MOI.GreaterThan{Float64})
#            MOI.supports_constraint(model, F, MOI.LessThan{Float64})
#            MOI.supports_constraint(model, F, MOI.EqualTo{Float64})
#            # These return false, but it doesn't matter
#            MOI.supports_constraint(model, F, MOI.ZeroOne)
#            MOI.supports_constraint(model, F, MOI.Integer)
#        end
#        MOI.add_constraint(model, x[1], MOI.GreaterThan(0.0))
#        MOI.add_constraint(model, x[2], MOI.LessThan(0.0))
#        MOI.add_constraint(model, x[3], MOI.EqualTo(0.0))
#        f = 1.0 * x[1] + x[2] + x[3]
#        c1 = MOI.add_constraint(model, f, MOI.GreaterThan(0.0))
#        MOI.set(model, MOI.ConstraintName(), c1, "c1")
#        MOI.supports(model, MOI.ConstraintName(), typeof(c1))
#        MOI.add_constraint(model, f, MOI.LessThan(0.0))
#        MOI.add_constraint(model, f, MOI.EqualTo(0.0))
#        y, _ = MOI.add_constrained_variables(model, MOI.Nonnegatives(2))
#        MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
#        MOI.supports(model, MOI.ObjectiveFunction{typeof(f)}())
#        MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
#        MOI.set(
#            model,
#            MOI.NLPBlock(),
#            MOI.NLPBlockData([], _EmptyNLPEvaluator(), false),
#        )
#        MOI.optimize!(model)
#        MOI.get(model, MOI.TerminationStatus())
#        MOI.get(model, MOI.PrimalStatus())
#        MOI.get(model, MOI.DualStatus())
#        MOI.get(model, MOI.VariablePrimal(), x)
#        # We put these after `optimize!` so that the error is thrown on add,
#        # not on optimize!
#        try
#            MOI.add_constraint(model, x[1], MOI.ZeroOne())
#        catch
#        end
#        try
#            MOI.add_constraint(model, x[1], MOI.Integer())
#        catch
#        end
#    end
#end

end  # module IpoptMathOptInterfaceExt