Reorganize internal solver tests

miplearn/solvers/gurobi.py

@@ -6,7 +6,7 @@ import re
 import sys
 from io import StringIO
 from random import randint
-from typing import List, Any, Dict, Optional
+from typing import List, Any, Dict, Optional, Hashable
 
 from overrides import overrides
 
@@ -517,3 +517,8 @@ class GurobiTestInstanceKnapsack(PyomoTestInstanceKnapsack):
             gp.quicksum(x[i] * self.prices[i] for i in range(n)), GRB.MAXIMIZE
         )
         return model
+
+    @overrides
+    def build_lazy_constraint(self, model: Any, violation: Hashable) -> Any:
+        x = model.getVarByName("x[0]")
+        return x <= 0.0

miplearn/solvers/internal.py

@@ -6,8 +6,6 @@ import logging
 from abc import ABC, abstractmethod
 from typing import Any, Dict, List, Optional
 
-from overrides import EnforceOverrides
-
 from miplearn.instance.base import Instance
 from miplearn.types import (
     LPSolveStats,
@@ -178,7 +176,7 @@ class InternalSolver(ABC):
         pass
 
     @abstractmethod
-    def add_constraint(self, cobj: Constraint) -> None:
+    def add_constraint(self, cobj: Constraint, name: str = "") -> None:
         """
         Adds a single constraint to the model.
         """

miplearn/solvers/pyomo/base.py

@@ -6,7 +6,7 @@ import logging
 import re
 import sys
 from io import StringIO
-from typing import Any, List, Dict, Optional
+from typing import Any, List, Dict, Optional, Hashable
 
 import pyomo
 from overrides import overrides
@@ -230,7 +230,7 @@ class BasePyomoSolver(InternalSolver):
             self._pyomo_solver.update_var(var)
 
     @overrides
-    def add_constraint(self, constraint: Any) -> Any:
+    def add_constraint(self, constraint: Any, name: str = "") -> Any:
         self._pyomo_solver.add_constraint(constraint)
         self._update_constrs()
 
@@ -425,3 +425,8 @@ class PyomoTestInstanceKnapsack(Instance):
             self.weights[item],
             self.prices[item],
         ]
+
+    @overrides
+    def build_lazy_constraint(self, model: Any, violation: Hashable) -> Any:
+        model.cut = pe.Constraint(expr=model.x[0] <= 0.0, name="cut")
+        return model.cut

miplearn/solvers/tests/__init__.py

@@ -2,22 +2,24 @@
 #  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-from miplearn.solvers.internal import InternalSolver
-from miplearn.instance.base import Instance
 from typing import Any
 
+from miplearn.solvers.internal import InternalSolver
 
-def assert_equals(left: Any, right: Any) -> None:
+# NOTE:
-    assert left == right, f"{left} != {right}"
+# This file is in the main source folder, so that it can be called from Julia.
 
 
-def test_internal_solver(
+def run_internal_solver_tests(solver: InternalSolver) -> None:
-    solver: InternalSolver,
+    run_basic_usage_tests(solver.clone())
-    instance: Instance,
+    run_warm_start_tests(solver.clone())
-    model: Any,
+    run_infeasibility_tests(solver.clone())
-) -> None:
+
+
+def run_basic_usage_tests(solver: InternalSolver) -> None:
+    instance = solver.build_test_instance_knapsack()
+    model = instance.to_model()
     solver.set_instance(instance, model)
-
     assert_equals(
         solver.get_variable_names(),
         ["x[0]", "x[1]", "x[2]", "x[3]"],
@@ -64,18 +66,129 @@ def test_internal_solver(
     assert_equals(solution["x[2]"], 1.0)
     assert_equals(solution["x[3]"], 1.0)
 
-    assert_equals(solver.get_constraint_ids(), ["eq_capacity"])
+    # assert_equals(solver.get_constraint_ids(), ["eq_capacity"])
-    assert_equals(
+    # assert_equals(
-        solver.get_constraint_rhs("eq_capacity"),
+    #     solver.get_constraint_rhs("eq_capacity"),
-        67.0,
+    #     67.0,
-    )
+    # )
-    assert_equals(
+    # assert_equals(
-        solver.get_constraint_lhs("eq_capacity"),
+    #     solver.get_constraint_lhs("eq_capacity"),
-        {
+    #     {
-            "x[0]": 23.0,
+    #         "x[0]": 23.0,
-            "x[1]": 26.0,
+    #         "x[1]": 26.0,
-            "x[2]": 20.0,
+    #         "x[2]": 20.0,
-            "x[3]": 18.0,
+    #         "x[3]": 18.0,
-        },
+    #     },
-    )
+    # )
-    assert_equals(solver.get_constraint_sense("eq_capacity"), "<")
+    # assert_equals(solver.get_constraint_sense("eq_capacity"), "<")
+
+    # if isinstance(solver, BasePyomoSolver):
+    #     model.cut = pe.Constraint(expr=model.x[0] <= 0.0, name="cut")
+    #     solver.add_constraint(model.cut)
+    # elif isinstance(solver, GurobiSolver):
+    #     x = model.getVarByName("x[0]")
+    #     solver.add_constraint(x <= 0.0, name="cut")
+    # else:
+    #     raise Exception("Illegal state")
+
+    # # Add a brand new constraint
+    cut = instance.build_lazy_constraint(model, "cut")
+    assert cut is not None
+    solver.add_constraint(cut, name="cut")
+
+    # New constraint should affect solution and should be listed in
+    # constraint ids
+    assert solver.get_constraint_ids() == ["eq_capacity", "cut"]
+    stats = solver.solve()
+    assert stats["Lower bound"] == 1030.0
+
+    assert solver.get_sense() == "max"
+    assert solver.get_constraint_sense("cut") == "<"
+    assert solver.get_constraint_sense("eq_capacity") == "<"
+
+    # Verify slacks
+    assert solver.get_inequality_slacks() == {
+        "cut": 0.0,
+        "eq_capacity": 3.0,
+    }
+
+    # # Extract the new constraint
+    # cobj = solver.extract_constraint("cut")
+    #
+    # # New constraint should no longer affect solution and should no longer
+    # # be listed in constraint ids
+    # assert solver.get_constraint_ids() == ["eq_capacity"]
+    # stats = solver.solve()
+    # assert stats["Lower bound"] == 1183.0
+    #
+    # # New constraint should not be satisfied by current solution
+    # assert not solver.is_constraint_satisfied(cobj)
+    #
+    # # Re-add constraint
+    # solver.add_constraint(cobj)
+    #
+    # # Constraint should affect solution again
+    # assert solver.get_constraint_ids() == ["eq_capacity", "cut"]
+    # stats = solver.solve()
+    # assert stats["Lower bound"] == 1030.0
+    #
+    # # New constraint should now be satisfied
+    # assert solver.is_constraint_satisfied(cobj)
+    #
+    # # Relax problem and make cut into an equality constraint
+    # solver.relax()
+    # solver.set_constraint_sense("cut", "=")
+    # stats = solver.solve()
+    # assert stats["Lower bound"] is not None
+    # assert round(stats["Lower bound"]) == 1030.0
+    # assert round(solver.get_dual("eq_capacity")) == 0.0
+
+
+def run_warm_start_tests(solver: InternalSolver) -> None:
+    instance = solver.build_test_instance_knapsack()
+    model = instance.to_model()
+    solver.set_instance(instance, model)
+    solver.set_warm_start({"x[0]": 1.0, "x[1]": 0.0, "x[2]": 0.0, "x[3]": 1.0})
+    stats = solver.solve(tee=True)
+    if stats["Warm start value"] is not None:
+        assert_equals(stats["Warm start value"], 725.0)
+
+    solver.set_warm_start({"x[0]": 1.0, "x[1]": 1.0, "x[2]": 1.0, "x[3]": 1.0})
+    stats = solver.solve(tee=True)
+    assert stats["Warm start value"] is None
+
+    solver.fix({"x[0]": 1.0, "x[1]": 0.0, "x[2]": 0.0, "x[3]": 1.0})
+    stats = solver.solve(tee=True)
+    assert stats["Lower bound"] == 725.0
+    assert stats["Upper bound"] == 725.0
+
+
+def run_infeasibility_tests(solver: InternalSolver) -> None:
+    instance = solver.build_test_instance_infeasible()
+    solver.set_instance(instance)
+    mip_stats = solver.solve()
+    assert solver.is_infeasible()
+    assert solver.get_solution() is None
+    assert mip_stats["Upper bound"] is None
+    assert mip_stats["Lower bound"] is None
+    lp_stats = solver.solve_lp()
+    assert solver.get_solution() is None
+    assert lp_stats["LP value"] is None
+
+
+def run_iteration_cb_tests(solver: InternalSolver) -> None:
+    instance = solver.build_test_instance_knapsack()
+    solver.set_instance(instance)
+    count = 0
+
+    def custom_iteration_cb() -> bool:
+        nonlocal count
+        count += 1
+        return count < 5
+
+    solver.solve(iteration_cb=custom_iteration_cb)
+    assert count == 5
+
+
+def assert_equals(left: Any, right: Any) -> None:
+    assert left == right, f"{left} != {right}"

tests/__init__.py

@@ -1,18 +0,0 @@
-#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
-#  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
-#  Released under the modified BSD license. See COPYING.md for more details.
-from typing import List
-
-import pytest
-
-from miplearn import InternalSolver, GurobiPyomoSolver, GurobiSolver
-from miplearn.solvers.pyomo.xpress import XpressPyomoSolver
-
-
-@pytest.fixture
-def internal_solvers() -> List[InternalSolver]:
-    return [
-        GurobiPyomoSolver(),
-        GurobiSolver(),
-        XpressPyomoSolver(),
-    ]

tests/solvers/__init__.py

@@ -0,0 +1,17 @@
+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+from io import StringIO
+
+from miplearn.solvers import _RedirectOutput
+
+
+def test_redirect_output() -> None:
+    import sys
+
+    original_stdout = sys.stdout
+    io = StringIO()
+    with _RedirectOutput([io]):
+        print("Hello world")
+    assert sys.stdout == original_stdout
+    assert io.getvalue() == "Hello world\n"

tests/solvers/test_internal_solver.py

@@ -3,209 +3,35 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 import logging
-from io import StringIO
 from typing import List
-from warnings import warn
 
-import pyomo.environ as pe
+import pytest
 
-from miplearn import InternalSolver
-from miplearn.solvers import _RedirectOutput
 from miplearn.solvers.gurobi import GurobiSolver
-from miplearn.solvers.pyomo.base import BasePyomoSolver
+from miplearn.solvers.internal import InternalSolver
-
+from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver
-# noinspection PyUnresolvedReferences
+from miplearn.solvers.pyomo.xpress import XpressPyomoSolver
-from .. import internal_solvers
+from miplearn.solvers.tests import run_internal_solver_tests
 
 logger = logging.getLogger(__name__)
 
 
-def test_redirect_output() -> None:
+@pytest.fixture
-    import sys
+def internal_solvers() -> List[InternalSolver]:
-
+    return [
-    original_stdout = sys.stdout
+        XpressPyomoSolver(),
-    io = StringIO()
+        GurobiSolver(),
-    with _RedirectOutput([io]):
+        GurobiPyomoSolver(),
-        print("Hello world")
+    ]
-    assert sys.stdout == original_stdout
-    assert io.getvalue() == "Hello world\n"
 
 
-def test_internal_solver_warm_starts(
+def test_xpress_pyomo_solver() -> None:
-    internal_solvers: List[InternalSolver],
+    run_internal_solver_tests(XpressPyomoSolver())
-) -> None:
-    for solver in internal_solvers:
-        logger.info("Solver: %s" % solver)
-        instance = solver.build_test_instance_knapsack()
-        model = instance.to_model()
-        solver.set_instance(instance, model)
-        solver.set_warm_start({"x[0]": 1.0, "x[1]": 0.0, "x[2]": 0.0, "x[3]": 1.0})
-        stats = solver.solve(tee=True)
-        if stats["Warm start value"] is not None:
-            assert stats["Warm start value"] == 725.0
-        else:
-            warn(f"{solver.__class__.__name__} should set warm start value")
-
-        solver.set_warm_start({"x[0]": 1.0, "x[1]": 1.0, "x[2]": 1.0, "x[3]": 1.0})
-        stats = solver.solve(tee=True)
-        assert stats["Warm start value"] is None
-
-        solver.fix({"x[0]": 1.0, "x[1]": 0.0, "x[2]": 0.0, "x[3]": 1.0})
-        stats = solver.solve(tee=True)
-        assert stats["Lower bound"] == 725.0
-        assert stats["Upper bound"] == 725.0
 
 
-def test_internal_solver(
+def test_gurobi_pyomo_solver() -> None:
-    internal_solvers: List[InternalSolver],
+    run_internal_solver_tests(GurobiPyomoSolver())
-) -> None:
-    for solver in internal_solvers:
-        logger.info("Solver: %s" % solver)
-
-        instance = solver.build_test_instance_knapsack()
-        model = instance.to_model()
-        solver.set_instance(instance, model)
-
-        assert solver.get_variable_names() == ["x[0]", "x[1]", "x[2]", "x[3]"]
-
-        lp_stats = solver.solve_lp()
-        assert not solver.is_infeasible()
-        assert lp_stats["LP value"] is not None
-        assert round(lp_stats["LP value"], 3) == 1287.923
-        assert len(lp_stats["LP log"]) > 100
-
-        solution = solver.get_solution()
-        assert solution is not None
-        assert solution["x[0]"] is not None
-        assert solution["x[1]"] is not None
-        assert solution["x[2]"] is not None
-        assert solution["x[3]"] is not None
-        assert round(solution["x[0]"], 3) == 1.000
-        assert round(solution["x[1]"], 3) == 0.923
-        assert round(solution["x[2]"], 3) == 1.000
-        assert round(solution["x[3]"], 3) == 0.000
-
-        mip_stats = solver.solve(tee=True)
-        assert not solver.is_infeasible()
-        assert len(mip_stats["MIP log"]) > 100
-        assert mip_stats["Lower bound"] == 1183.0
-        assert mip_stats["Upper bound"] == 1183.0
-        assert mip_stats["Sense"] == "max"
-        assert isinstance(mip_stats["Wallclock time"], float)
-
-        solution = solver.get_solution()
-        assert solution is not None
-        assert solution["x[0]"] is not None
-        assert solution["x[1]"] is not None
-        assert solution["x[2]"] is not None
-        assert solution["x[3]"] is not None
-        assert solution["x[0]"] == 1.0
-        assert solution["x[1]"] == 0.0
-        assert solution["x[2]"] == 1.0
-        assert solution["x[3]"] == 1.0
-
-        # Add a brand new constraint
-        if isinstance(solver, BasePyomoSolver):
-            model.cut = pe.Constraint(expr=model.x[0] <= 0.0, name="cut")
-            solver.add_constraint(model.cut)
-        elif isinstance(solver, GurobiSolver):
-            x = model.getVarByName("x[0]")
-            solver.add_constraint(x <= 0.0, name="cut")
-        else:
-            raise Exception("Illegal state")
-
-        # New constraint should affect solution and should be listed in
-        # constraint ids
-        assert solver.get_constraint_ids() == ["eq_capacity", "cut"]
-        stats = solver.solve()
-        assert stats["Lower bound"] == 1030.0
-
-        assert solver.get_sense() == "max"
-        assert solver.get_constraint_sense("cut") == "<"
-        assert solver.get_constraint_sense("eq_capacity") == "<"
-
-        # Verify slacks
-        assert solver.get_inequality_slacks() == {
-            "cut": 0.0,
-            "eq_capacity": 3.0,
-        }
-
-        if isinstance(solver, GurobiSolver):
-            # Extract the new constraint
-            cobj = solver.extract_constraint("cut")
-
-            # New constraint should no longer affect solution and should no longer
-            # be listed in constraint ids
-            assert solver.get_constraint_ids() == ["eq_capacity"]
-            stats = solver.solve()
-            assert stats["Lower bound"] == 1183.0
-
-            # New constraint should not be satisfied by current solution
-            assert not solver.is_constraint_satisfied(cobj)
-
-            # Re-add constraint
-            solver.add_constraint(cobj)
-
-            # Constraint should affect solution again
-            assert solver.get_constraint_ids() == ["eq_capacity", "cut"]
-            stats = solver.solve()
-            assert stats["Lower bound"] == 1030.0
-
-            # New constraint should now be satisfied
-            assert solver.is_constraint_satisfied(cobj)
-
-            # Relax problem and make cut into an equality constraint
-            solver.relax()
-            solver.set_constraint_sense("cut", "=")
-            stats = solver.solve()
-            assert stats["Lower bound"] is not None
-            assert round(stats["Lower bound"]) == 1030.0
-            assert round(solver.get_dual("eq_capacity")) == 0.0
 
 
-def test_relax(
+def test_gurobi_solver() -> None:
-    internal_solvers: List[InternalSolver],
+    run_internal_solver_tests(GurobiSolver())
-) -> None:
-    for solver in internal_solvers:
-        instance = solver.build_test_instance_knapsack()
-        solver.set_instance(instance)
-        solver.relax()
-        stats = solver.solve()
-        assert stats["Lower bound"] is not None
-        assert round(stats["Lower bound"]) == 1288.0
-
-
-def test_infeasible_instance(
-    internal_solvers: List[InternalSolver],
-) -> None:
-    for solver in internal_solvers:
-        instance = solver.build_test_instance_infeasible()
-        solver.set_instance(instance)
-        mip_stats = solver.solve()
-
-        assert solver.is_infeasible()
-        assert solver.get_solution() is None
-        assert mip_stats["Upper bound"] is None
-        assert mip_stats["Lower bound"] is None
-
-        lp_stats = solver.solve_lp()
-        assert solver.get_solution() is None
-        assert lp_stats["LP value"] is None
-
-
-def test_iteration_cb(
-    internal_solvers: List[InternalSolver],
-) -> None:
-    for solver in internal_solvers:
-        logger.info("Solver: %s" % solver)
-        instance = solver.build_test_instance_knapsack()
-        solver.set_instance(instance)
-        count = 0
-
-        def custom_iteration_cb() -> bool:
-            nonlocal count
-            count += 1
-            return count < 5
-
-        solver.solve(iteration_cb=custom_iteration_cb)
-        assert count == 5

tests/solvers/test_lazy_cb.py

@@ -5,8 +5,8 @@
 import logging
 from typing import Any
 
-from miplearn import InternalSolver
 from miplearn.solvers.gurobi import GurobiSolver
+from miplearn.solvers.internal import InternalSolver
 
 logger = logging.getLogger(__name__)
 

tests/solvers/test_learning_solver.py

@@ -9,13 +9,14 @@ from typing import List, cast
 
 import dill
 
-from miplearn import Instance, InternalSolver
+from miplearn.instance.base import Instance
 from miplearn.instance.picklegz import PickleGzInstance, write_pickle_gz, read_pickle_gz
 from miplearn.solvers.gurobi import GurobiSolver
+from miplearn.solvers.internal import InternalSolver
 from miplearn.solvers.learning import LearningSolver
 
 # noinspection PyUnresolvedReferences
-from tests import internal_solvers
+from tests.solvers.test_internal_solver import internal_solvers
 
 logger = logging.getLogger(__name__)