Add Uno_jll to MINLPTests

README.md

@@ -67,8 +67,9 @@ Supported packages include:
 | [Bonmin](https://github.com/coin-or/Bonmin)   | `Bonmin_jll.jl`   | `Bomin_jll.amplexe`   |
 | [Couenne](https://github.com/coin-or/Couenne) | `Couenne_jll.jl`  | `Couenne_jll.amplexe` |
 | [Ipopt](https://github.com/coin-or/Ipopt)     | `Ipopt_jll.jl`    | `Ipopt_jll.amplexe`   |
-| [SHOT](https://github.com/coin-or/SHOT)       | `SHOT_jll.jl`     | `SHOT_jll.amplexe`    |
 | [KNITRO](https://github.comjump-dev/KNITRO.jl)| `KNITRO.jl`       | `KNITRO.amplexe`      |
+| [SHOT](https://github.com/coin-or/SHOT)       | `SHOT_jll.jl`     | `SHOT_jll.amplexe`    |
+| [Uno](https://github.com/cvanaret/Uno)        | `Uno_jll.jl`      | `Uno_jll.amplexe`     |
 
 ## MathOptInterface API
 

test/MINLPTests/Project.toml

@@ -4,14 +4,18 @@ Couenne_jll = "f09e9e23-9010-5c9e-b679-9f1d8f79b85c"
 Ipopt_jll = "9cc047cb-c261-5740-88fc-0cf96f7bdcc7"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 MINLPTests = "ee0a3090-8ee9-5cdb-b8cb-8eeba3165522"
+MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 SHOT_jll = "c1ab834c-c4a5-50f5-9156-8f0fe7758b0e"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Uno_jll = "396d5378-14f1-5ab1-981d-48acd51740ed"
 
 [compat]
 Bonmin_jll = "100.800.801"
 Couenne_jll = "0.500.801"
-Ipopt_jll = "=300.1400.400, =300.1400.1400"
+Ipopt_jll = "=300.1400.1600"
 JuMP = "1"
+MathOptInterface = "1.33"
 MINLPTests = "0.6"
 SHOT_jll = "100.100.0"
+Uno_jll = "1.1.0"
 julia = "1.6"

test/MINLPTests/run_minlptests.jl

@@ -3,22 +3,28 @@
 # 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.
 
+using Test
+
 import AmplNLWriter
+import Bonmin_jll
+import Couenne_jll
+import Ipopt_jll
+import MathOptInterface as MOI
 import MINLPTests
-using Test
+import SHOT_jll
+import Uno_jll
 
 const TERMINATION_TARGET = Dict(
-    MINLPTests.FEASIBLE_PROBLEM => AmplNLWriter.MOI.LOCALLY_SOLVED,
-    MINLPTests.INFEASIBLE_PROBLEM => AmplNLWriter.MOI.LOCALLY_INFEASIBLE,
+    MINLPTests.FEASIBLE_PROBLEM => MOI.LOCALLY_SOLVED,
+    MINLPTests.INFEASIBLE_PROBLEM => MOI.LOCALLY_INFEASIBLE,
 )
 
 const PRIMAL_TARGET = Dict(
-    MINLPTests.FEASIBLE_PROBLEM => AmplNLWriter.MOI.FEASIBLE_POINT,
-    MINLPTests.INFEASIBLE_PROBLEM => AmplNLWriter.MOI.NO_SOLUTION,
+    MINLPTests.FEASIBLE_PROBLEM => MOI.FEASIBLE_POINT,
+    MINLPTests.INFEASIBLE_PROBLEM => MOI.NO_SOLUTION,
 )
 
 # Common reasons for exclusion:
-# nlp/005_011     : Uses the function `\`
 # nlp/006_010     : Uses a user-defined function
 # nlp/007_010     : Ipopt returns an infeasible point, not NO_SOLUTION.
 # nlp/008_010     : Couenne fails to converge
@@ -29,140 +35,188 @@ const PRIMAL_TARGET = Dict(
 # nlp-cvx/206_010 : Couenne can't evaluate pow
 # nlp-mi/001_010  : Couenne fails to converge
 
-const CONFIG = Dict{String,Any}()
-
-import Bonmin_jll
-CONFIG["Bonmin"] = Dict(
-    "amplexe" => Bonmin_jll.amplexe,
-    "options" => String["bonmin.nlp_log_level=0"],
-    "tol" => 1e-5,
-    "dual_tol" => NaN,
-    "nlp_exclude" => ["005_011", "006_010"],
-    "nlpcvx_exclude" => ["109_010"],
-    # 004_010 and 004_011 are tolerance failures on Bonmin
-    "nlpmi_exclude" => ["004_010", "004_011", "005_011", "006_010"],
-    "infeasible_point" => AmplNLWriter.MOI.NO_SOLUTION,
+const CONFIG = Dict{String,Any}(
+    "Bonmin" => Dict(
+        "mixed-integer" => true,
+        "amplexe" => Bonmin_jll.amplexe,
+        "options" => String["bonmin.nlp_log_level=0"],
+        "dual_tol" => NaN,
+        "nlpcvx_exclude" => ["109_010"],
+        # 004_010 and 004_011 are tolerance failures on Bonmin
+        "nlpmi_exclude" => ["004_010", "004_011"],
+    ),
+    "Couenne" => Dict(
+        "mixed-integer" => true,
+        "amplexe" => Couenne_jll.amplexe,
+        "options" => String[],
+        "tol" => 1e-2,
+        "dual_tol" => NaN,
+        "nlp_exclude" => ["008_010", "008_011", "009_010", "009_011"],
+        "nlpcvx_exclude" => ["109_010", "206_010"],
+        "nlpmi_exclude" => ["001_010"],
+    ),
+    "Ipopt" => Dict(
+        "mixed-integer" => false,
+        "amplexe" => Ipopt_jll.amplexe,
+        "options" => String["print_level=0"],
+        "nlp_exclude" => ["007_010"],
+        "nlpcvx_exclude" => ["109_010"],
+    ),
+    # SHOT fails too many tests to recommend using it.
+    # e.g., https://github.com/coin-or/SHOT/issues/134
+    # Even problems such as `@variable(model, x); @objective(model, Min, (x-1)^2)`
+    # "SHOT" => Dict(
+    #     "amplexe" => SHOT_jll.amplexe,
+    #     "options" => String[
+    #         "Output.Console.LogLevel=6",
+    #         "Output.File.LogLevel=6",
+    #         "Termination.ObjectiveGap.Absolute=1e-6",
+    #         "Termination.ObjectiveGap.Relative=1e-6",
+    #     ],
+    #     "tol" => 1e-2,
+    #     "dual_tol" => NaN,
+    #     "infeasible_point" => AmplNLWriter.MOI.UNKNOWN_RESULT_STATUS,
+    # ),
+    "Uno" => Dict(
+        "mixed-integer" => false,
+        "amplexe" => Uno_jll.amplexe,
+        "options" => ["logger=SILENT"],
+        "nlp_exclude" => [
+            # See https://github.com/cvanaret/Uno/issues/39
+            "005_010",
+            # See https://github.com/cvanaret/Uno/issues/38
+            "007_010",
+        ],
+    ),
 )
 
-import Couenne_jll
-CONFIG["Couenne"] = Dict(
-    "amplexe" => Couenne_jll.amplexe,
-    "options" => String[],
-    "tol" => 1e-2,
-    "dual_tol" => NaN,
-    "nlp_exclude" =>
-        ["005_011", "006_010", "008_010", "008_011", "009_010", "009_011"],
-    "nlpcvx_exclude" => ["109_010", "206_010"],
-    "nlpmi_exclude" => ["001_010", "005_011", "006_010"],
-    "infeasible_point" => AmplNLWriter.MOI.NO_SOLUTION,
-)
-
-import Ipopt_jll
-CONFIG["Ipopt"] = Dict(
-    "amplexe" => Ipopt_jll.amplexe,
-    "options" => String["print_level=0"],
-    "tol" => 1e-5,
-    "dual_tol" => 1e-5,
-    "nlp_exclude" => ["005_011", "006_010", "007_010"],
-    "nlpcvx_exclude" => ["109_010"],
-    "nlpmi_exclude" => ["005_011", "006_010"],
-    "infeasible_point" => AmplNLWriter.MOI.NO_SOLUTION,
-)
-
-# SHOT fails too many tests to recommend using it.
-# e.g., https://github.com/coin-or/SHOT/issues/134
-# Even problems such as `@variable(model, x); @objective(model, Min, (x-1)^2)`
-#
-# import SHOT_jll
-# CONFIG["SHOT"] = Dict(
-#     "amplexe" => SHOT_jll.amplexe,
-#     "options" => String[
-#         "Output.Console.LogLevel=6",
-#         "Output.File.LogLevel=6",
-#         "Termination.ObjectiveGap.Absolute=1e-6",
-#         "Termination.ObjectiveGap.Relative=1e-6",
-#     ],
-#     "tol" => 1e-2,
-#     "dual_tol" => NaN,
-#     "nlp_exclude" => [
-#         "005_011",  # `\` function
-#         "006_010",  # User-defined function
-#     ],
-#     "nlpcvx_exclude" => [
-#         "501_011",  # `\` function
-#     ],
-#     "nlpmi_exclude" => [
-#         "005_011",  # `\` function
-#         "006_010",  # User-defined function
-#     ],
-#     "infeasible_point" => AmplNLWriter.MOI.UNKNOWN_RESULT_STATUS,
-# )
-
-@testset "$(name)" for name in ["Ipopt", "Bonmin", "Couenne"]
-    config = CONFIG[name]
+@testset "$k" for (k, config) in CONFIG
     OPTIMIZER =
         () -> AmplNLWriter.Optimizer(config["amplexe"], config["options"])
-    PRIMAL_TARGET[MINLPTests.INFEASIBLE_PROBLEM] = config["infeasible_point"]
+    # PRIMAL_TARGET[MINLPTests.INFEASIBLE_PROBLEM] = config["infeasible_point"]
     @testset "NLP" begin
+        exclude = vcat(get(config, "nlp_exclude", String[]), ["006_010"])
         MINLPTests.test_nlp(
-            OPTIMIZER,
-            exclude = config["nlp_exclude"],
+            OPTIMIZER;
+            exclude = exclude,
             termination_target = TERMINATION_TARGET,
             primal_target = PRIMAL_TARGET,
-            objective_tol = config["tol"],
-            primal_tol = config["tol"],
-            dual_tol = config["dual_tol"],
+            objective_tol = get(config, "tol", 1e-5),
+            primal_tol = get(config, "tol", 1e-5),
+            dual_tol = get(config, "dual_tol", 1e-5),
         )
         MINLPTests.test_nlp_expr(
-            OPTIMIZER,
-            exclude = config["nlp_exclude"],
+            OPTIMIZER;
+            exclude = exclude,
             termination_target = TERMINATION_TARGET,
             primal_target = PRIMAL_TARGET,
-            objective_tol = config["tol"],
-            primal_tol = config["tol"],
-            dual_tol = config["dual_tol"],
+            objective_tol = get(config, "tol", 1e-5),
+            primal_tol = get(config, "tol", 1e-5),
+            dual_tol = get(config, "dual_tol", 1e-5),
         )
     end
     @testset "NLP-CVX" begin
+        exclude = get(config, "nlpcvx_exclude", String[])
         MINLPTests.test_nlp_cvx(
-            OPTIMIZER,
-            exclude = config["nlpcvx_exclude"],
+            OPTIMIZER;
+            exclude = exclude,
             termination_target = TERMINATION_TARGET,
             primal_target = PRIMAL_TARGET,
-            objective_tol = config["tol"],
-            primal_tol = config["tol"],
-            dual_tol = config["dual_tol"],
+            objective_tol = get(config, "tol", 1e-5),
+            primal_tol = get(config, "tol", 1e-5),
+            dual_tol = get(config, "dual_tol", 1e-5),
         )
         MINLPTests.test_nlp_cvx_expr(
-            OPTIMIZER,
-            exclude = config["nlpcvx_exclude"],
+            OPTIMIZER;
+            exclude = exclude,
             termination_target = TERMINATION_TARGET,
             primal_target = PRIMAL_TARGET,
-            objective_tol = config["tol"],
-            primal_tol = config["tol"],
-            dual_tol = config["dual_tol"],
+            objective_tol = get(config, "tol", 1e-5),
+            primal_tol = get(config, "tol", 1e-5),
+            dual_tol = get(config, "dual_tol", 1e-5),
         )
     end
-    if name != "Ipopt"
+    if config["mixed-integer"]
+        exclude = vcat(get(config, "nlpmi_exclude", String[]), ["006_010"])
         @testset "NLP-MI" begin
             MINLPTests.test_nlp_mi(
-                OPTIMIZER,
-                exclude = config["nlpmi_exclude"],
+                OPTIMIZER;
+                exclude = exclude,
                 termination_target = TERMINATION_TARGET,
                 primal_target = PRIMAL_TARGET,
-                objective_tol = config["tol"],
-                primal_tol = config["tol"],
-                dual_tol = config["dual_tol"],
+                objective_tol = get(config, "tol", 1e-5),
+                primal_tol = get(config, "tol", 1e-5),
+                dual_tol = get(config, "dual_tol", 1e-5),
             )
             MINLPTests.test_nlp_mi_expr(
-                OPTIMIZER,
-                exclude = config["nlpmi_exclude"],
+                OPTIMIZER;
+                exclude = exclude,
                 termination_target = TERMINATION_TARGET,
                 primal_target = PRIMAL_TARGET,
-                objective_tol = config["tol"],
-                primal_tol = config["tol"],
-                dual_tol = config["dual_tol"],
+                objective_tol = get(config, "tol", 1e-5),
+                primal_tol = get(config, "tol", 1e-5),
+                dual_tol = get(config, "dual_tol", 1e-5),
             )
         end
     end
 end
+
+function test_uno_runtests()
+    optimizer = MOI.instantiate(
+        () -> AmplNLWriter.Optimizer(Uno_jll.amplexe, ["logger=SILENT"]);
+        with_cache_type = Float64,
+        with_bridge_type = Float64,
+    )
+    MOI.Test.runtests(
+        optimizer,
+        MOI.Test.Config(
+            atol = 1e-4,
+            rtol = 1e-4,
+            optimal_status = MOI.LOCALLY_SOLVED,
+            infeasible_status = MOI.LOCALLY_INFEASIBLE,
+            exclude = Any[
+                MOI.VariableBasisStatus,
+                MOI.ConstraintBasisStatus,
+                MOI.ObjectiveBound,
+            ],
+        );
+        exclude = [
+            # OTHER_LIMIT instead of LOCALLY_SOLVED
+            r"^test_conic_linear_VectorOfVariables_2$",
+            r"^test_nonlinear_expression_hs109$",
+            r"^test_quadratic_constraint_GreaterThan$",
+            r"^test_quadratic_constraint_LessThan$",
+            r"^test_solve_VariableIndex_ConstraintDual_MAX_SENSE$",
+            r"^test_solve_VariableIndex_ConstraintDual_MIN_SENSE$",
+            # OTHER_ERROR instead of LOCALLY_SOLVED
+            r"^test_linear_integration$",
+            r"^test_linear_transform$",
+            # OTHER_LIMIT instead of DUAL_INFEASIBLE
+            r"^test_solve_TerminationStatus_DUAL_INFEASIBLE$",
+            # OTHER_LIMIT instead of LOCALLY_INFEASIBLE
+            r"^test_conic_NormInfinityCone_INFEASIBLE$",
+            r"^test_conic_NormOneCone_INFEASIBLE$",
+            r"^test_conic_linear_INFEASIBLE$",
+            r"^test_conic_linear_INFEASIBLE_2$",
+            r"^test_linear_INFEASIBLE$",
+            r"^test_linear_INFEASIBLE_2$",
+            r"^test_solve_DualStatus_INFEASIBILITY_CERTIFICATE_",
+            # Uno does not support integrality
+            "Indicator",
+            r"[Ii]nteger",
+            "Semicontinuous",
+            "Semiinteger",
+            "SOS1",
+            "SOS2",
+            "ZeroOne",
+            r"^test_cpsat_",
+            # Existing MOI issues
+            r"^test_attribute_SolverVersion$",
+            r"^test_nonlinear_invalid$",
+            r"^test_basic_VectorNonlinearFunction_",
+        ],
+    )
+    return
+end
+
+test_uno_runtests()