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141 lines
4.6 KiB
141 lines
4.6 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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import logging
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from typing import Any, TYPE_CHECKING, Hashable, Set, Tuple, Dict, List, Optional
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import numpy as np
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from overrides import overrides
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from miplearn.instance.base import Instance
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from miplearn.classifiers import Classifier
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from miplearn.classifiers.counting import CountingClassifier
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from miplearn.classifiers.threshold import Threshold, MinProbabilityThreshold
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from miplearn.components.component import Component
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from miplearn.components.dynamic_common import DynamicConstraintsComponent
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from miplearn.features import Features, TrainingSample, Sample
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from miplearn.types import LearningSolveStats
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logger = logging.getLogger(__name__)
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if TYPE_CHECKING:
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from miplearn.solvers.learning import LearningSolver
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class UserCutsComponent(Component):
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def __init__(
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self,
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classifier: Classifier = CountingClassifier(),
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threshold: Threshold = MinProbabilityThreshold([0.50, 0.50]),
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) -> None:
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self.dynamic = DynamicConstraintsComponent(
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classifier=classifier,
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threshold=threshold,
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attr="user_cuts_enforced",
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)
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self.enforced: Set[Hashable] = set()
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self.n_added_in_callback = 0
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@overrides
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def before_solve_mip_old(
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self,
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solver: "LearningSolver",
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instance: "Instance",
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model: Any,
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stats: LearningSolveStats,
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features: Features,
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training_data: TrainingSample,
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) -> None:
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assert solver.internal_solver is not None
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self.enforced.clear()
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self.n_added_in_callback = 0
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logger.info("Predicting violated user cuts...")
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cids = self.dynamic.sample_predict_old(instance, training_data)
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logger.info("Enforcing %d user cuts ahead-of-time..." % len(cids))
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for cid in cids:
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instance.enforce_user_cut(solver.internal_solver, model, cid)
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stats["UserCuts: Added ahead-of-time"] = len(cids)
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@overrides
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def user_cut_cb(
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self,
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solver: "LearningSolver",
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instance: "Instance",
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model: Any,
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) -> None:
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assert solver.internal_solver is not None
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logger.debug("Finding violated user cuts...")
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cids = instance.find_violated_user_cuts(model)
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logger.debug(f"Found {len(cids)} violated user cuts")
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logger.debug("Building violated user cuts...")
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for cid in cids:
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if cid in self.enforced:
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continue
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assert isinstance(cid, Hashable)
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instance.enforce_user_cut(solver.internal_solver, model, cid)
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self.enforced.add(cid)
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self.n_added_in_callback += 1
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if len(cids) > 0:
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logger.debug(f"Added {len(cids)} violated user cuts")
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@overrides
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def after_solve_mip_old(
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self,
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solver: "LearningSolver",
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instance: "Instance",
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model: Any,
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stats: LearningSolveStats,
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features: Features,
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training_data: TrainingSample,
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) -> None:
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training_data.user_cuts_enforced = set(self.enforced)
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stats["UserCuts: Added in callback"] = self.n_added_in_callback
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if self.n_added_in_callback > 0:
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logger.info(f"{self.n_added_in_callback} user cuts added in callback")
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# Delegate ML methods to self.dynamic
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# -------------------------------------------------------------------
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@overrides
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def sample_xy_old(
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self,
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instance: "Instance",
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sample: TrainingSample,
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) -> Tuple[Dict, Dict]:
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return self.dynamic.sample_xy_old(instance, sample)
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@overrides
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def sample_xy(
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self,
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instance: Optional[Instance],
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sample: Sample,
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) -> Tuple[Dict, Dict]:
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return self.dynamic.sample_xy(instance, sample)
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def sample_predict(
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self,
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instance: "Instance",
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sample: TrainingSample,
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) -> List[Hashable]:
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return self.dynamic.sample_predict(instance, sample)
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@overrides
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def fit_old(self, training_instances: List["Instance"]) -> None:
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self.dynamic.fit_old(training_instances)
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@overrides
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def fit_xy(
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self,
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x: Dict[Hashable, np.ndarray],
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y: Dict[Hashable, np.ndarray],
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) -> None:
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self.dynamic.fit_xy(x, y)
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@overrides
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def sample_evaluate_old(
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self,
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instance: "Instance",
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sample: TrainingSample,
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) -> Dict[Hashable, Dict[str, float]]:
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return self.dynamic.sample_evaluate_old(instance, sample)
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