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Organize test fixtures; handle infeasibility in DropRedundant
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@@ -3,11 +3,8 @@
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# Released under the modified BSD license. See COPYING.md for more details.
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from inspect import isclass
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from typing import List, Callable, Any
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from typing import List, Callable
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from pyomo import environ as pe
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from miplearn.instance import Instance
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from miplearn.problems.knapsack import KnapsackInstance, GurobiKnapsackInstance
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from miplearn.solvers.gurobi import GurobiSolver
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from miplearn.solvers.internal import InternalSolver
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@@ -16,27 +13,6 @@ from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver
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from miplearn.solvers.pyomo.xpress import XpressPyomoSolver
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class InfeasiblePyomoInstance(Instance):
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def to_model(self) -> pe.ConcreteModel:
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model = pe.ConcreteModel()
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model.x = pe.Var([0], domain=pe.Binary)
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model.OBJ = pe.Objective(expr=model.x[0], sense=pe.maximize)
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model.eq = pe.Constraint(expr=model.x[0] >= 2)
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return model
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class InfeasibleGurobiInstance(Instance):
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def to_model(self) -> Any:
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import gurobipy as gp
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from gurobipy import GRB
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model = gp.Model()
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x = model.addVars(1, vtype=GRB.BINARY, name="x")
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model.addConstr(x[0] >= 2)
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model.setObjective(x[0])
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return model
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def _is_subclass_or_instance(obj, parent_class):
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return isinstance(obj, parent_class) or (
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isclass(obj) and issubclass(obj, parent_class)
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@@ -59,12 +35,5 @@ def _get_knapsack_instance(solver):
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assert False
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def _get_infeasible_instance(solver):
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if _is_subclass_or_instance(solver, BasePyomoSolver):
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return InfeasiblePyomoInstance()
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if _is_subclass_or_instance(solver, GurobiSolver):
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return InfeasibleGurobiInstance()
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def _get_internal_solvers() -> List[Callable[[], InternalSolver]]:
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return [GurobiPyomoSolver, GurobiSolver, XpressPyomoSolver]
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@@ -14,8 +14,8 @@ from miplearn.solvers.pyomo.base import BasePyomoSolver
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from . import (
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_get_knapsack_instance,
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_get_internal_solvers,
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_get_infeasible_instance,
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)
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from ..fixtures.infeasible import get_infeasible_instance
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logger = logging.getLogger(__name__)
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@@ -186,7 +186,7 @@ def test_relax():
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def test_infeasible_instance():
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for solver_class in _get_internal_solvers():
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instance = _get_infeasible_instance(solver_class)
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instance = get_infeasible_instance(solver_class)
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solver = solver_class()
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solver.set_instance(instance)
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stats = solver.solve()
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