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MIPLearn
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Enforce more overrides

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master
Alinson S. Xavier 5 years ago
parent 1cf6124757
commit 96093a9b8e
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GPG Key ID: DCA0DAD4D2F58624
8 changed files with 42 additions and 1 deletions
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3
miplearn/__init__.py
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@ -27,3 +27,6 @@ from .solvers.learning import LearningSolver
from .solvers.pyomo.base import BasePyomoSolver
from .solvers.pyomo.cplex import CplexPyomoSolver
from .solvers.pyomo.gurobi import GurobiPyomoSolver
# noinspection PyUnresolvedReferences
from overrides import overrides

3
miplearn/components/component.py
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@ -5,6 +5,7 @@
from typing import Any, List, TYPE_CHECKING, Tuple, Dict, Hashable
import numpy as np
from overrides import EnforceOverrides
from miplearn.features import TrainingSample, Features
from miplearn.instance.base import Instance
@ -15,7 +16,7 @@ if TYPE_CHECKING:
# noinspection PyMethodMayBeStatic
class Component:
class Component(EnforceOverrides):
"""
A Component is an object which adds functionality to a LearningSolver.

5
miplearn/components/dynamic_common.py
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@ -5,6 +5,7 @@
from typing import Dict, Hashable, List, Tuple, TYPE_CHECKING
import numpy as np
from overrides import overrides
from miplearn.classifiers import Classifier
from miplearn.classifiers.threshold import Threshold
@ -73,6 +74,7 @@ class DynamicConstraintsComponent(Component):
y[category] += [[True, False]]
return x, y, cids
@overrides
def sample_xy(
self,
instance: "Instance",
@ -101,6 +103,7 @@ class DynamicConstraintsComponent(Component):
pred += [cids[category][i]]
return pred
@overrides
def fit(self, training_instances: List["Instance"]) -> None:
collected_cids = set()
for instance in training_instances:
@ -114,6 +117,7 @@ class DynamicConstraintsComponent(Component):
self.known_cids.extend(sorted(collected_cids))
super().fit(training_instances)
@overrides
def fit_xy(
self,
x: Dict[Hashable, np.ndarray],
@ -127,6 +131,7 @@ class DynamicConstraintsComponent(Component):
self.classifiers[category].fit(npx, npy)
self.thresholds[category].fit(self.classifiers[category], npx, npy)
@overrides
def sample_evaluate(
self,
instance: "Instance",

7
miplearn/components/dynamic_lazy.py
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@ -6,6 +6,7 @@ import logging
from typing import Dict, List, TYPE_CHECKING, Hashable, Tuple, Any
import numpy as np
from overrides import overrides
from miplearn.instance.base import Instance
from miplearn.classifiers import Classifier
@ -53,6 +54,7 @@ class DynamicLazyConstraintsComponent(Component):
cobj = instance.build_lazy_constraint(model, cid)
solver.internal_solver.add_constraint(cobj)
@overrides
def before_solve_mip(
self,
solver: "LearningSolver",
@ -68,6 +70,7 @@ class DynamicLazyConstraintsComponent(Component):
logger.info("Enforcing %d lazy constraints..." % len(cids))
self.enforce(cids, instance, model, solver)
@overrides
def iteration_cb(
self,
solver: "LearningSolver",
@ -89,6 +92,7 @@ class DynamicLazyConstraintsComponent(Component):
# Delegate ML methods to self.dynamic
# -------------------------------------------------------------------
@overrides
def sample_xy(
self,
instance: "Instance",
@ -103,9 +107,11 @@ class DynamicLazyConstraintsComponent(Component):
) -> List[Hashable]:
return self.dynamic.sample_predict(instance, sample)
@overrides
def fit(self, training_instances: List["Instance"]) -> None:
self.dynamic.fit(training_instances)
@overrides
def fit_xy(
self,
x: Dict[Hashable, np.ndarray],
@ -113,6 +119,7 @@ class DynamicLazyConstraintsComponent(Component):
) -> None:
self.dynamic.fit_xy(x, y)
@overrides
def sample_evaluate(
self,
instance: "Instance",

8
miplearn/components/dynamic_user_cuts.py
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@ -6,6 +6,7 @@ import logging
from typing import Any, TYPE_CHECKING, Hashable, Set, Tuple, Dict, List
import numpy as np
from overrides import overrides
from miplearn.classifiers import Classifier
from miplearn.classifiers.counting import CountingClassifier
@ -35,6 +36,7 @@ class UserCutsComponent(Component):
self.enforced: Set[Hashable] = set()
self.n_added_in_callback = 0
@overrides
def before_solve_mip(
self,
solver: "LearningSolver",
@ -55,6 +57,7 @@ class UserCutsComponent(Component):
solver.internal_solver.add_constraint(cobj)
stats["UserCuts: Added ahead-of-time"] = len(cids)
@overrides
def user_cut_cb(
self,
solver: "LearningSolver",
@ -78,6 +81,7 @@ class UserCutsComponent(Component):
if len(cids) > 0:
logger.debug(f"Added {len(cids)} violated user cuts")
@overrides
def after_solve_mip(
self,
solver: "LearningSolver",
@ -93,6 +97,7 @@ class UserCutsComponent(Component):
# Delegate ML methods to self.dynamic
# -------------------------------------------------------------------
@overrides
def sample_xy(
self,
instance: "Instance",
@ -107,9 +112,11 @@ class UserCutsComponent(Component):
) -> List[Hashable]:
return self.dynamic.sample_predict(instance, sample)
@overrides
def fit(self, training_instances: List["Instance"]) -> None:
self.dynamic.fit(training_instances)
@overrides
def fit_xy(
self,
x: Dict[Hashable, np.ndarray],
@ -117,6 +124,7 @@ class UserCutsComponent(Component):
) -> None:
self.dynamic.fit_xy(x, y)
@overrides
def sample_evaluate(
self,
instance: "Instance",

5
miplearn/components/objective.py
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@ -6,6 +6,7 @@ import logging
from typing import List, Dict, Any, TYPE_CHECKING, Tuple, Hashable
import numpy as np
from overrides import overrides
from sklearn.linear_model import LinearRegression
from miplearn.classifiers import Regressor
@ -34,6 +35,7 @@ class ObjectiveValueComponent(Component):
self.regressors: Dict[str, Regressor] = {}
self.regressor_prototype = regressor
@overrides
def before_solve_mip(
self,
solver: "LearningSolver",
@ -49,6 +51,7 @@ class ObjectiveValueComponent(Component):
logger.info(f"Predicted {c.lower()}: %.6e" % v)
stats[f"Objective: Predicted {c.lower()}"] = v # type: ignore
@overrides
def fit_xy(
self,
x: Dict[Hashable, np.ndarray],
@ -73,6 +76,7 @@ class ObjectiveValueComponent(Component):
logger.info(f"{c} regressor not fitted. Skipping.")
return pred
@overrides
def sample_xy(
self,
instance: Instance,
@ -94,6 +98,7 @@ class ObjectiveValueComponent(Component):
y["Upper bound"] = [[sample.upper_bound]]
return x, y
@overrides
def sample_evaluate(
self,
instance: Instance,

5
miplearn/components/primal.py
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@ -13,6 +13,7 @@ from typing import (
)
import numpy as np
from overrides import overrides
from miplearn.classifiers import Classifier
from miplearn.classifiers.adaptive import AdaptiveClassifier
@ -58,6 +59,7 @@ class PrimalSolutionComponent(Component):
self.threshold_prototype = threshold
self.classifier_prototype = classifier
@overrides
def before_solve_mip(
self,
solver: "LearningSolver",
@ -137,6 +139,7 @@ class PrimalSolutionComponent(Component):
return solution
@overrides
def sample_xy(
self,
instance: Instance,
@ -172,6 +175,7 @@ class PrimalSolutionComponent(Component):
y[category] += [[opt_value < 0.5, opt_value >= 0.5]]
return x, y
@overrides
def sample_evaluate(
self,
instance: Instance,
@ -212,6 +216,7 @@ class PrimalSolutionComponent(Component):
),
}
@overrides
def fit_xy(
self,
x: Dict[Hashable, np.ndarray],

7
miplearn/components/static_lazy.py
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@ -6,6 +6,7 @@ import logging
from typing import Dict, Tuple, List, Hashable, Any, TYPE_CHECKING, Set
import numpy as np
from overrides import overrides
from miplearn.classifiers import Classifier
from miplearn.classifiers.counting import CountingClassifier
@ -49,6 +50,7 @@ class StaticLazyConstraintsComponent(Component):
self.n_restored: int = 0
self.n_iterations: int = 0
@overrides
def before_solve_mip(
self,
solver: "LearningSolver",
@ -84,6 +86,7 @@ class StaticLazyConstraintsComponent(Component):
self.n_restored = 0
self.n_iterations = 0
@overrides
def after_solve_mip(
self,
solver: "LearningSolver",
@ -97,6 +100,7 @@ class StaticLazyConstraintsComponent(Component):
stats["LazyStatic: Restored"] = self.n_restored
stats["LazyStatic: Iterations"] = self.n_iterations
@overrides
def iteration_cb(
self,
solver: "LearningSolver",
@ -108,6 +112,7 @@ class StaticLazyConstraintsComponent(Component):
else:
return self._check_and_add(solver)
@overrides
def lazy_cb(
self,
solver: "LearningSolver",
@ -170,6 +175,7 @@ class StaticLazyConstraintsComponent(Component):
enforced_cids += [category_to_cids[category][i]]
return enforced_cids
@overrides
def sample_xy(
self,
instance: "Instance",
@ -195,6 +201,7 @@ class StaticLazyConstraintsComponent(Component):
y[category] += [[True, False]]
return x, y
@overrides
def fit_xy(
self,
x: Dict[Hashable, np.ndarray],

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