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# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
import logging
from miplearn.solvers.gurobi import GurobiSolver
from miplearn.solvers.tests import _get_knapsack_instance
logger = logging.getLogger(__name__)
def test_lazy_cb():
solver = GurobiSolver()
instance = _get_knapsack_instance(solver)
model = instance.to_model()
def lazy_cb(cb_solver, cb_model):
logger.info("x[0] = %.f" % cb_solver.get_value("x", 0))
cobj = (cb_model.getVarByName("x[0]") * 1.0, "<", 0.0, "cut")
if not cb_solver.is_constraint_satisfied(cobj):
cb_solver.add_constraint(cobj)
solver.set_instance(instance, model)
solver.solve(lazy_cb=lazy_cb)
solution = solver.get_solution()
assert solution["x"][0] == 0.0