ANL-CEEESA/MIPLearn
1
0
Fork 0
mirror of https://github.com/ANL-CEEESA/MIPLearn.git synced 2025-12-06 09:28:51 -06:00
Code Issues Packages Projects Releases Wiki Activity

Remove unused classes and methods

Browse Source
This commit is contained in:
Alinson S. Xavier
2021-05-15 14:29:11 -05:00
parent 91c8db2225
commit 4bf4d09cb5
11 changed files with 19 additions and 195 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
miplearn/components/static_lazy.py
View File

@@ -12,7 +12,7 @@ from miplearn.classifiers import Classifier
from miplearn.classifiers.counting import CountingClassifier
from miplearn.classifiers.threshold import MinProbabilityThreshold, Threshold
from miplearn.components.component import Component
from miplearn.features import Constraint, Sample, ConstraintFeatures
from miplearn.features import Sample, ConstraintFeatures
from miplearn.instance.base import Instance
from miplearn.types import LearningSolveStats
@@ -45,7 +45,6 @@ class StaticLazyConstraintsComponent(Component):
self.threshold_prototype: Threshold = threshold
self.classifiers: Dict[Hashable, Classifier] = {}
self.thresholds: Dict[Hashable, Threshold] = {}
self.pool_old: Dict[str, Constraint] = {}
self.pool: ConstraintFeatures = ConstraintFeatures()
self.violation_tolerance: float = violation_tolerance
self.enforced_cids: Set[Hashable] = set()

36
miplearn/features.py
View File

@@ -133,42 +133,6 @@ class ConstraintFeatures:
return tuple(obj[i] for (i, selected_i) in enumerate(selected) if selected_i)
@dataclass
class Constraint:
basis_status: Optional[str] = None
category: Optional[Hashable] = None
dual_value: Optional[float] = None
lazy: bool = False
lhs: Optional[Dict[str, float]] = None
rhs: float = 0.0
sa_rhs_down: Optional[float] = None
sa_rhs_up: Optional[float] = None
sense: str = "<"
slack: Optional[float] = None
user_features: Optional[List[float]] = None
def to_list(self) -> List[float]:
features: List[float] = []
for attr in [
"dual value",
"rhs",
"sa_rhs_down",
"sa_rhs_up",
"slack",
]:
if getattr(self, attr) is not None:
features.append(getattr(self, attr))
for attr in ["user_features"]:
if getattr(self, attr) is not None:
features.extend(getattr(self, attr))
if self.lhs is not None and len(self.lhs) > 0:
features.append(np.max(self.lhs.values()))
features.append(np.average(self.lhs.values()))
features.append(np.min(self.lhs.values()))
_clip(features)
return features
@dataclass
class Features:
instance: Optional[InstanceFeatures] = None

48
miplearn/solvers/gurobi.py
View File

@@ -10,7 +10,7 @@ from typing import List, Any, Dict, Optional, Hashable, Tuple, TYPE_CHECKING
from overrides import overrides
from miplearn.features import Constraint, VariableFeatures, ConstraintFeatures
from miplearn.features import VariableFeatures, ConstraintFeatures
from miplearn.instance.base import Instance
from miplearn.solvers import _RedirectOutput
from miplearn.solvers.internal import (
@@ -81,7 +81,6 @@ class GurobiSolver(InternalSolver):
self._var_lbs: Tuple[float, ...] = tuple()
self._var_ubs: Tuple[float, ...] = tuple()
self._var_obj_coeffs: Tuple[float, ...] = tuple()
self._relaxed_constrs: Dict[str, Tuple["gurobipy.LinExpr", str, float]] = {}
if self.lazy_cb_frequency == 1:
self.lazy_cb_where = [self.gp.GRB.Callback.MIPSOL]
@@ -156,10 +155,6 @@ class GurobiSolver(InternalSolver):
capacity=67.0,
)
@overrides
def build_test_instance_redundancy(self) -> Instance:
return GurobiTestInstanceRedundancy()
@overrides
def clone(self) -> "GurobiSolver":
return GurobiSolver(
@@ -167,17 +162,6 @@ class GurobiSolver(InternalSolver):
lazy_cb_frequency=self.lazy_cb_frequency,
)
def enforce_constraints(self, names: List[str]) -> None:
assert self.model is not None
constr = [self._relaxed_constrs[n] for n in names]
for (i, (lhs, sense, rhs)) in enumerate(constr):
if sense == "=":
self.model.addConstr(lhs == rhs, name=names[i])
elif sense == "<":
self.model.addConstr(lhs <= rhs, name=names[i])
else:
self.model.addConstr(lhs >= rhs, name=names[i])
@overrides
def fix(self, solution: Solution) -> None:
self._raise_if_callback()
@@ -385,15 +369,6 @@ class GurobiSolver(InternalSolver):
assert self.model is not None
return self.model.status in [self.gp.GRB.INFEASIBLE, self.gp.GRB.INF_OR_UNBD]
def relax_constraints(self, names: List[str]) -> None:
assert self.model is not None
constrs = [self._cname_to_constr[n] for n in names]
for (i, name) in enumerate(names):
c = constrs[i]
self._relaxed_constrs[name] = self.model.getRow(c), c.sense, c.rhs
self.model.remove(constrs)
self.model.update()
@overrides
def remove_constraints(self, names: Tuple[str, ...]) -> None:
assert self.model is not None
@@ -536,13 +511,6 @@ class GurobiSolver(InternalSolver):
lp_wallclock_time=self.model.runtime,
)
@overrides
def relax(self) -> None:
assert self.model is not None
self.model.update()
self.model = self.model.relax()
self._update()
def _apply_params(self, streams: List[Any]) -> None:
assert self.model is not None
with _RedirectOutput(streams):
@@ -666,20 +634,6 @@ class GurobiTestInstanceInfeasible(Instance):
return model
class GurobiTestInstanceRedundancy(Instance):
@overrides
def to_model(self) -> Any:
import gurobipy as gp
from gurobipy import GRB
model = gp.Model()
x = model.addVars(2, vtype=GRB.BINARY, name="x")
model.addConstr(x[0] + x[1] <= 1, name="c1")
model.addConstr(x[0] + x[1] <= 2, name="c2")
model.setObjective(x[0] + x[1], GRB.MAXIMIZE)
return model
class GurobiTestInstanceKnapsack(PyomoTestInstanceKnapsack):
"""
Simpler (one-dimensional) knapsack instance, implemented directly in Gurobi

31
miplearn/solvers/internal.py
View File

@@ -5,14 +5,13 @@
import logging
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple
from typing import Any, List, Optional, Tuple
from miplearn.features import Constraint, VariableFeatures, ConstraintFeatures
from miplearn.features import VariableFeatures, ConstraintFeatures
from miplearn.instance.base import Instance
from miplearn.types import (
IterationCallback,
LazyCallback,
BranchPriorities,
UserCutCallback,
Solution,
)
@@ -75,6 +74,9 @@ class InternalSolver(ABC):
@abstractmethod
def build_test_instance_infeasible(self) -> Instance:
"""
Returns an infeasible instance, for testing purposes.
"""
pass
@abstractmethod
@@ -89,10 +91,6 @@ class InternalSolver(ABC):
"""
pass
@abstractmethod
def build_test_instance_redundancy(self) -> Instance:
pass
@abstractmethod
def clone(self) -> "InternalSolver":
"""
@@ -184,25 +182,6 @@ class InternalSolver(ABC):
"""
pass
@abstractmethod
def relax(self) -> None:
"""
Drops all integrality constraints from the model.
"""
pass
def set_branching_priorities(self, priorities: BranchPriorities) -> None:
"""
Sets the branching priorities for the given decision variables.
When the MIP solver needs to decide on which variable to branch, variables
with higher priority are picked first, given that they are fractional.
Ties are solved arbitrarily. By default, all variables have priority zero.
Missing values indicate variables whose priorities should not be modified.
"""
raise NotImplementedError()
@abstractmethod
def set_instance(
self,

34
miplearn/solvers/pyomo/base.py
View File

@@ -136,10 +136,6 @@ class BasePyomoSolver(InternalSolver):
def build_test_instance_infeasible(self) -> Instance:
return PyomoTestInstanceInfeasible()
@overrides
def build_test_instance_redundancy(self) -> Instance:
return PyomoTestInstanceRedundancy()
@overrides
def build_test_instance_knapsack(self) -> Instance:
return PyomoTestInstanceKnapsack(
@@ -490,7 +486,7 @@ class BasePyomoSolver(InternalSolver):
self,
tee: bool = False,
) -> LPSolveStats:
self.relax()
self._relax()
streams: List[Any] = [StringIO()]
if tee:
streams += [sys.stdout]
@@ -510,15 +506,6 @@ class BasePyomoSolver(InternalSolver):
lp_wallclock_time=results["Solver"][0]["Wallclock time"],
)
@overrides
def relax(self) -> None:
for var in self._bin_vars:
lb, ub = var.bounds
var.setlb(lb)
var.setub(ub)
var.domain = pyomo.core.base.set_types.Reals
self._pyomo_solver.update_var(var)
def _clear_warm_start(self) -> None:
for var in self._all_vars:
if not var.fixed:
@@ -575,6 +562,14 @@ class BasePyomoSolver(InternalSolver):
raise Exception(f"Unknown expression type: {expr.__class__.__name__}")
return lhs
def _relax(self) -> None:
for var in self._bin_vars:
lb, ub = var.bounds
var.setlb(lb)
var.setub(ub)
var.domain = pyomo.core.base.set_types.Reals
self._pyomo_solver.update_var(var)
def _restore_integrality(self) -> None:
for var in self._bin_vars:
var.domain = pyomo.core.base.set_types.Binary
@@ -624,17 +619,6 @@ class PyomoTestInstanceInfeasible(Instance):
return model
class PyomoTestInstanceRedundancy(Instance):
@overrides
def to_model(self) -> pe.ConcreteModel:
model = pe.ConcreteModel()
model.x = pe.Var([0, 1], domain=pe.Binary)
model.OBJ = pe.Objective(expr=model.x[0] + model.x[1], sense=pe.maximize)
model.eq1 = pe.Constraint(expr=model.x[0] + model.x[1] <= 1)
model.eq2 = pe.Constraint(expr=model.x[0] + model.x[1] <= 2)
return model
class PyomoTestInstanceKnapsack(Instance):
"""
Simpler (one-dimensional) Knapsack Problem, used for testing.

13
miplearn/solvers/pyomo/gurobi.py
View File

@@ -10,7 +10,7 @@ from pyomo import environ as pe
from scipy.stats import randint
from miplearn.solvers.pyomo.base import BasePyomoSolver
from miplearn.types import SolverParams, BranchPriorities
from miplearn.types import SolverParams
logger = logging.getLogger(__name__)
@@ -42,17 +42,6 @@ class GurobiPyomoSolver(BasePyomoSolver):
def clone(self) -> "GurobiPyomoSolver":
return GurobiPyomoSolver(params=self.params)
@overrides
def set_branching_priorities(self, priorities: BranchPriorities) -> None:
from gurobipy import GRB
for (varname, priority) in priorities.items():
if priority is None:
continue
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 _extract_node_count(self, log: str) -> int:
return max(1, int(self._pyomo_solver._solver_model.getAttr("NodeCount")))

26
miplearn/solvers/tests/__init__.py
View File

@@ -2,9 +2,9 @@
# 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 Any, Dict, List
from typing import Any, List
from miplearn.features import Constraint, VariableFeatures, ConstraintFeatures
from miplearn.features import VariableFeatures, ConstraintFeatures
from miplearn.solvers.internal import InternalSolver
inf = float("inf")
@@ -13,14 +13,6 @@ inf = float("inf")
# This file is in the main source folder, so that it can be called from Julia.
def _round_constraints(constraints: Dict[str, Constraint]) -> Dict[str, Constraint]:
for (cname, c) in constraints.items():
for attr in ["slack", "dual_value"]:
if getattr(c, attr) is not None:
setattr(c, attr, round(getattr(c, attr), 6))
return constraints
def _round(obj: Any) -> Any:
if obj is None:
return None
@@ -46,20 +38,6 @@ def _filter_attrs(allowed_keys: List[str], obj: Any) -> Any:
return obj
def _remove_unsupported_constr_attrs(
solver: InternalSolver,
constraints: Dict[str, Constraint],
) -> Dict[str, Constraint]:
for (cname, c) in constraints.items():
to_remove = []
for k in c.__dict__.keys():
if k not in solver.get_constraint_attrs():
to_remove.append(k)
for k in to_remove:
setattr(c, k, None)
return constraints
def run_internal_solver_tests(solver: InternalSolver) -> None:
run_basic_usage_tests(solver.clone())
run_warm_start_tests(solver.clone())

1
miplearn/types.py
View File

@@ -10,7 +10,6 @@ if TYPE_CHECKING:
# noinspection PyUnresolvedReferences
from miplearn.solvers.learning import InternalSolver
BranchPriorities = Dict[str, Optional[float]]
Category = Hashable
IterationCallback = Callable[[], bool]
LazyCallback = Callable[[Any, Any], None]