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MIPLearn/miplearn/instance/file.py

132 lines
4.1 KiB

# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
import gc
import os
import pickle
from typing import Any, Optional, List, Dict, TYPE_CHECKING
import numpy as np
from overrides import overrides
from miplearn.features.sample import Hdf5Sample, Sample
from miplearn.instance.base import Instance
from miplearn.types import ConstraintName
if TYPE_CHECKING:
from miplearn.solvers.learning import InternalSolver
class FileInstance(Instance):
def __init__(self, filename: str) -> None:
super().__init__()
assert os.path.exists(filename), f"File not found: {filename}"
self.h5 = Hdf5Sample(filename)
self.instance: Optional[Instance] = None
# Delegation
# -------------------------------------------------------------------------
@overrides
def to_model(self) -> Any:
assert self.instance is not None
return self.instance.to_model()
@overrides
def get_instance_features(self) -> np.ndarray:
assert self.instance is not None
return self.instance.get_instance_features()
@overrides
def get_variable_features(self, names: np.ndarray) -> np.ndarray:
assert self.instance is not None
return self.instance.get_variable_features(names)
@overrides
def get_variable_categories(self, names: np.ndarray) -> np.ndarray:
assert self.instance is not None
return self.instance.get_variable_categories(names)
@overrides
def get_constraint_features(self, names: np.ndarray) -> np.ndarray:
assert self.instance is not None
return self.instance.get_constraint_features(names)
@overrides
def get_constraint_categories(self, names: np.ndarray) -> np.ndarray:
assert self.instance is not None
return self.instance.get_constraint_categories(names)
@overrides
def has_dynamic_lazy_constraints(self) -> bool:
assert self.instance is not None
return self.instance.has_dynamic_lazy_constraints()
@overrides
def are_constraints_lazy(self, names: np.ndarray) -> np.ndarray:
assert self.instance is not None
return self.instance.are_constraints_lazy(names)
@overrides
def find_violated_lazy_constraints(
self,
solver: "InternalSolver",
model: Any,
) -> Dict[ConstraintName, Any]:
assert self.instance is not None
return self.instance.find_violated_lazy_constraints(solver, model)
@overrides
def enforce_lazy_constraint(
self,
solver: "InternalSolver",
model: Any,
violation_data: Any,
) -> None:
assert self.instance is not None
self.instance.enforce_lazy_constraint(solver, model, violation_data)
@overrides
def find_violated_user_cuts(self, model: Any) -> Dict[ConstraintName, Any]:
assert self.instance is not None
return self.instance.find_violated_user_cuts(model)
@overrides
def enforce_user_cut(
self,
solver: "InternalSolver",
model: Any,
violation_data: Any,
) -> None:
assert self.instance is not None
self.instance.enforce_user_cut(solver, model, violation_data)
# Input & Output
# -------------------------------------------------------------------------
@overrides
def free(self) -> None:
self.instance = None
gc.collect()
@overrides
def load(self) -> None:
if self.instance is not None:
return
pkl = self.h5.get_bytes("pickled")
assert pkl is not None
self.instance = pickle.loads(pkl)
assert isinstance(self.instance, Instance)
@classmethod
def save(cls, instance: Instance, filename: str) -> None:
h5 = Hdf5Sample(filename, mode="w")
instance_pkl = pickle.dumps(instance)
h5.put_bytes("pickled", instance_pkl)
@overrides
def create_sample(self) -> Sample:
return self.h5
@overrides
def get_samples(self) -> List[Sample]:
return [self.h5]