MIPLearn/miplearn/features.py

#  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, Hashable

from miplearn.types import (
    Features,
    ConstraintFeatures,
    InstanceFeatures,
    VariableFeatures,
    VarIndex,
)

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") -> None:
        instance.features.variables = self._extract_variables(instance)
        instance.features.constraints = self._extract_constraints(instance)
        instance.features.instance = self._extract_instance(instance, instance.features)

    def _extract_variables(
        self,
        instance: "Instance",
    ) -> Dict[str, Dict[VarIndex, VariableFeatures]]:
        result: Dict[str, Dict[VarIndex, VariableFeatures]] = {}
        empty_solution = self.solver.get_empty_solution()
        for (var_name, var_dict) in empty_solution.items():
            result[var_name] = {}
            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}]."
                        )
                result[var_name][idx] = VariableFeatures(
                    category=category,
                    user_features=user_features,
                )
        return result

    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:
        assert features.constraints is not None
        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 InstanceFeatures(
            user_features=user_features,
            lazy_constraint_count=lazy_count,
        )