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MIPLearn/miplearn/features.py

118 lines
4.8 KiB

# 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 numbers
import collections
from typing import TYPE_CHECKING, Dict
from miplearn.types import Features, ConstraintFeatures, InstanceFeatures
if TYPE_CHECKING:
from miplearn import InternalSolver, Instance
class FeaturesExtractor:
def __init__(
self,
internal_solver: "InternalSolver",
) -> None:
self.solver = internal_solver
def extract(self, instance: "Instance") -> Features:
features: Features = {
"Variables": self._extract_variables(instance),
"Constraints": self._extract_constraints(instance),
}
features["Instance"] = self._extract_instance(instance, features)
return features
def _extract_variables(self, instance: "Instance") -> Dict:
variables = self.solver.get_empty_solution()
for (var_name, var_dict) in variables.items():
for idx in var_dict.keys():
user_features = None
category = instance.get_variable_category(var_name, idx)
if category is not None:
assert isinstance(category, collections.Hashable), (
f"Variable category must be be hashable. "
f"Found {type(category).__name__} instead for var={var_name}."
)
user_features = instance.get_variable_features(var_name, idx)
assert isinstance(user_features, list), (
f"Variable features must be a list. "
f"Found {type(user_features).__name__} instead for "
f"var={var_name}[{idx}]."
)
for v in user_features:
assert isinstance(v, numbers.Real), (
f"Variable features must be a list of numbers. "
f"Found {type(v).__name__} instead "
f"for var={var_name}[{idx}]."
)
var_dict[idx] = {
"Category": category,
"User features": user_features,
}
return variables
def _extract_constraints(
self,
instance: "Instance",
) -> Dict[str, ConstraintFeatures]:
has_static_lazy = instance.has_static_lazy_constraints()
constraints: Dict[str, ConstraintFeatures] = {}
for cid in self.solver.get_constraint_ids():
user_features = None
category = instance.get_constraint_category(cid)
if category is not None:
assert isinstance(category, collections.Hashable), (
f"Constraint category must be hashable. "
f"Found {type(category).__name__} instead for cid={cid}.",
)
user_features = instance.get_constraint_features(cid)
assert isinstance(user_features, list), (
f"Constraint features must be a list. "
f"Found {type(user_features).__name__} instead for cid={cid}."
)
assert isinstance(user_features[0], float), (
f"Constraint features must be a list of floats. "
f"Found {type(user_features[0]).__name__} instead for cid={cid}."
)
constraints[cid] = {
"RHS": self.solver.get_constraint_rhs(cid),
"LHS": self.solver.get_constraint_lhs(cid),
"Sense": self.solver.get_constraint_sense(cid),
"Category": category,
"User features": user_features,
}
if has_static_lazy:
constraints[cid]["Lazy"] = instance.is_constraint_lazy(cid)
else:
constraints[cid]["Lazy"] = False
return constraints
@staticmethod
def _extract_instance(
instance: "Instance",
features: Features,
) -> InstanceFeatures:
user_features = instance.get_instance_features()
assert isinstance(user_features, list), (
f"Instance features must be a list. "
f"Found {type(user_features).__name__} instead."
)
for v in user_features:
assert isinstance(v, numbers.Real), (
f"Instance features must be a list of numbers. "
f"Found {type(v).__name__} instead."
)
lazy_count = 0
for (cid, cdict) in features["Constraints"].items():
if cdict["Lazy"]:
lazy_count += 1
return {
"User features": user_features,
"Lazy constraint count": lazy_count,
}