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Make InternalSolver clonable

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This commit is contained in:
Alinson S. Xavier
2021-04-07 19:52:21 -05:00
parent ebccde6a03
commit 0232219a0e
12 changed files with 69 additions and 46 deletions
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8
benchmark/benchmark.py
View File

@@ -62,7 +62,7 @@ def train(args):
PickleGzInstance(f) for f in glob.glob(f"{basepath}/train/*.gz")
]
solver = LearningSolver(
solver=lambda: GurobiPyomoSolver(
solver=GurobiPyomoSolver(
params={
"TimeLimit": int(args["--train-time-limit"]),
"Threads": int(args["--solver-threads"]),
@@ -83,7 +83,7 @@ def test_baseline(args):
if not os.path.isfile(csv_filename):
solvers = {
"baseline": LearningSolver(
solver=lambda: GurobiPyomoSolver(
solver=GurobiPyomoSolver(
params={
"TimeLimit": int(args["--test-time-limit"]),
"Threads": int(args["--solver-threads"]),
@@ -107,7 +107,7 @@ def test_ml(args):
if not os.path.isfile(csv_filename):
solvers = {
"ml-exact": LearningSolver(
solver=lambda: GurobiPyomoSolver(
solver=GurobiPyomoSolver(
params={
"TimeLimit": int(args["--test-time-limit"]),
"Threads": int(args["--solver-threads"]),
@@ -115,7 +115,7 @@ def test_ml(args):
),
),
"ml-heuristic": LearningSolver(
solver=lambda: GurobiPyomoSolver(
solver=GurobiPyomoSolver(
params={
"TimeLimit": int(args["--test-time-limit"]),
"Threads": int(args["--solver-threads"]),

15
miplearn/solvers/gurobi.py
View File

@@ -51,9 +51,11 @@ class GurobiSolver(InternalSolver):
) -> None:
import gurobipy
assert lazy_cb_frequency in [1, 2]
if params is None:
params = {}
params["InfUnbdInfo"] = True
params["Seed"] = randint(0, 1_000_000)
self.gp = gurobipy
self.instance: Optional[Instance] = None
@@ -62,9 +64,9 @@ class GurobiSolver(InternalSolver):
self.varname_to_var: Dict[str, "gurobipy.Var"] = {}
self.bin_vars: List["gurobipy.Var"] = []
self.cb_where: Optional[int] = None
self.lazy_cb_frequency = lazy_cb_frequency
assert lazy_cb_frequency in [1, 2]
if lazy_cb_frequency == 1:
if self.lazy_cb_frequency == 1:
self.lazy_cb_where = [self.gp.GRB.Callback.MIPSOL]
else:
self.lazy_cb_where = [
@@ -113,8 +115,6 @@ class GurobiSolver(InternalSolver):
with _RedirectOutput(streams):
for (name, value) in self.params.items():
self.model.setParam(name, value)
if "seed" not in [k.lower() for k in self.params.keys()]:
self.model.setParam("Seed", randint(0, 1_000_000))
@overrides
def solve_lp(
@@ -428,3 +428,10 @@ class GurobiSolver(InternalSolver):
self.instance = None
self.model = None
self.cb_where = None
@overrides
def clone(self) -> "GurobiSolver":
return GurobiSolver(
params=self.params,
lazy_cb_frequency=self.lazy_cb_frequency,
)

8
miplearn/solvers/internal.py
View File

@@ -284,3 +284,11 @@ class InternalSolver(ABC, EnforceOverrides):
model before a solution is available.
"""
pass
@abstractmethod
def clone(self) -> "InternalSolver":
"""
Returns a new copy of this solver with identical parameters, but otherwise
completely unitialized.
"""
pass

12
miplearn/solvers/learning.py
View File

@@ -91,20 +91,20 @@ class LearningSolver:
self,
components: List[Component] = None,
mode: str = "exact",
solver: Callable[[], InternalSolver] = None,
solver: InternalSolver = None,
use_lazy_cb: bool = False,
solve_lp: bool = True,
simulate_perfect: bool = False,
):
) -> None:
if solver is None:
solver = GurobiPyomoSolver
assert callable(solver), f"Callable expected. Found {solver.__class__} instead."
solver = GurobiPyomoSolver()
assert isinstance(solver, InternalSolver)
self.components: Dict[str, Component] = {}
self.internal_solver: Optional[InternalSolver] = None
self.internal_solver_prototype: InternalSolver = solver
self.mode: str = mode
self.simulate_perfect: bool = simulate_perfect
self.solve_lp: bool = solve_lp
self.solver_factory: Callable[[], InternalSolver] = solver
self.tee = False
self.use_lazy_cb: bool = use_lazy_cb
if components is not None:
@@ -144,7 +144,7 @@ class LearningSolver:
# Initialize internal solver
# -------------------------------------------------------
self.tee = tee
self.internal_solver = self.solver_factory()
self.internal_solver = self.internal_solver_prototype.clone()
assert self.internal_solver is not None
assert isinstance(self.internal_solver, InternalSolver)
self.internal_solver.set_instance(instance, model)

1
miplearn/solvers/pyomo/base.py
View File

@@ -46,6 +46,7 @@ class BasePyomoSolver(InternalSolver):
) -> None:
self.instance: Optional[Instance] = None
self.model: Optional[pe.ConcreteModel] = None
self.params = params
self._all_vars: List[pe.Var] = []
self._bin_vars: List[pe.Var] = []
self._is_warm_start_available: bool = False

5
miplearn/solvers/pyomo/cplex.py
View File

@@ -28,7 +28,6 @@ class CplexPyomoSolver(BasePyomoSolver):
) -> None:
if params is None:
params = {}
if "randomseed" not in params.keys():
params["randomseed"] = randint(low=0, high=1000).rvs()
if "mip_display" not in params.keys():
params["mip_display"] = 4
@@ -44,3 +43,7 @@ class CplexPyomoSolver(BasePyomoSolver):
@overrides
def _get_node_count_regexp(self):
return "^[ *] *([0-9]+)"
@overrides
def clone(self) -> "CplexPyomoSolver":
return CplexPyomoSolver(params=self.params)

5
miplearn/solvers/pyomo/gurobi.py
View File

@@ -32,7 +32,6 @@ class GurobiPyomoSolver(BasePyomoSolver):
) -> None:
if params is None:
params = {}
if "seed" not in params.keys():
params["seed"] = randint(low=0, high=1000).rvs()
super().__init__(
solver_factory=pe.SolverFactory("gurobi_persistent"),
@@ -61,3 +60,7 @@ class GurobiPyomoSolver(BasePyomoSolver):
var = self._varname_to_var[varname]
gvar = self._pyomo_solver._pyomo_var_to_solver_var_map[var]
gvar.setAttr(GRB.Attr.BranchPriority, int(round(priority)))
@overrides
def clone(self) -> "GurobiPyomoSolver":
return GurobiPyomoSolver(params=self.params)

6
miplearn/solvers/pyomo/xpress.py
View File

@@ -4,6 +4,7 @@
import logging
from overrides import overrides
from pyomo import environ as pe
from scipy.stats import randint
@@ -27,9 +28,12 @@ class XpressPyomoSolver(BasePyomoSolver):
def __init__(self, params: SolverParams = None) -> None:
if params is None:
params = {}
if "randomseed" not in params.keys():
params["randomseed"] = randint(low=0, high=1000).rvs()
super().__init__(
solver_factory=pe.SolverFactory("xpress_persistent"),
params=params,
)
@overrides
def clone(self) -> "XpressPyomoSolver":
return XpressPyomoSolver(params=self.params)

6
tests/components/test_dynamic_user_cuts.py
View File

@@ -64,10 +64,8 @@ def stab_instance() -> Instance:
@pytest.fixture
def solver() -> LearningSolver:
return LearningSolver(
solver=lambda: GurobiSolver(),
components=[
UserCutsComponent(),
],
solver=GurobiSolver(),
components=[UserCutsComponent()],
)

8
tests/solvers/__init__.py
View File

@@ -35,5 +35,9 @@ def _get_knapsack_instance(solver):
assert False
def get_internal_solvers() -> List[Callable[[], InternalSolver]]:
return [GurobiPyomoSolver, GurobiSolver, XpressPyomoSolver]
def get_internal_solvers() -> List[InternalSolver]:
return [
GurobiPyomoSolver(),
GurobiSolver(),
XpressPyomoSolver(),
]

33
tests/solvers/test_internal_solver.py
View File

@@ -32,18 +32,17 @@ def test_redirect_output():
def test_internal_solver_warm_starts():
for solver_class in get_internal_solvers():
logger.info("Solver: %s" % solver_class)
instance = _get_knapsack_instance(solver_class)
for solver in get_internal_solvers():
logger.info("Solver: %s" % solver)
instance = _get_knapsack_instance(solver)
model = instance.to_model()
solver = solver_class()
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")
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)
@@ -56,12 +55,11 @@ def test_internal_solver_warm_starts():
def test_internal_solver():
for solver_class in get_internal_solvers():
logger.info("Solver: %s" % solver_class)
for solver in get_internal_solvers():
logger.info("Solver: %s" % solver)
instance = _get_knapsack_instance(solver_class)
instance = _get_knapsack_instance(solver)
model = instance.to_model()
solver = solver_class()
solver.set_instance(instance, model)
assert solver.get_variable_names() == ["x[0]", "x[1]", "x[2]", "x[3]"]
@@ -150,9 +148,8 @@ def test_internal_solver():
def test_relax():
for solver_class in get_internal_solvers():
instance = _get_knapsack_instance(solver_class)
solver = solver_class()
for solver in get_internal_solvers():
instance = _get_knapsack_instance(solver)
solver.set_instance(instance)
solver.relax()
stats = solver.solve()
@@ -160,9 +157,8 @@ def test_relax():
def test_infeasible_instance():
for solver_class in get_internal_solvers():
instance = get_infeasible_instance(solver_class)
solver = solver_class()
for solver in get_internal_solvers():
instance = get_infeasible_instance(solver)
solver.set_instance(instance)
stats = solver.solve()
@@ -177,10 +173,9 @@ def test_infeasible_instance():
def test_iteration_cb():
for solver_class in get_internal_solvers():
logger.info("Solver: %s" % solver_class)
instance = _get_knapsack_instance(solver_class)
solver = solver_class()
for solver in get_internal_solvers():
logger.info("Solver: %s" % solver)
instance = _get_knapsack_instance(solver)
solver.set_instance(instance)
count = 0

2
tests/solvers/test_learning_solver.py
View File

@@ -109,7 +109,7 @@ def test_solve_fit_from_disk():
def test_simulate_perfect():
internal_solver = GurobiSolver
internal_solver = GurobiSolver()
instance = _get_knapsack_instance(internal_solver)
with tempfile.NamedTemporaryFile(suffix=".pkl", delete=False) as tmp:
write_pickle_gz(instance, tmp.name)