mirror of
https://github.com/ANL-CEEESA/MIPLearn.git
synced 2025-12-06 17:38:51 -06:00
32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
|
|
# Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved.
|
|
# Released under the modified BSD license. See COPYING.md for more details.
|
|
|
|
from math import log
|
|
from typing import List, Dict, Any
|
|
import numpy as np
|
|
|
|
import gurobipy as gp
|
|
|
|
from ..h5 import H5File
|
|
|
|
|
|
class ExpertBranchPriorityComponent:
|
|
def __init__(self) -> None:
|
|
pass
|
|
|
|
def fit(self, train_h5: List[str]) -> None:
|
|
pass
|
|
|
|
def before_mip(self, test_h5: str, model: gp.Model, _: Dict[str, Any]) -> None:
|
|
with H5File(test_h5, "r") as h5:
|
|
var_names = h5.get_array("static_var_names")
|
|
var_priority = h5.get_array("bb_var_priority")
|
|
assert var_priority is not None
|
|
assert var_names is not None
|
|
|
|
for var_idx, var_name in enumerate(var_names):
|
|
if np.isfinite(var_priority[var_idx]):
|
|
var = model.getVarByName(var_name.decode())
|
|
var.branchPriority = int(log(1 + var_priority[var_idx]))
|