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This commit is contained in:
Alinson S. Xavier
2020-03-05 17:58:56 -06:00
parent 37795fe013
commit 7765d1f822
50 changed files with 168 additions and 11 deletions
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miplearn/tests/test_benchmark.py
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# 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.
from miplearn import LearningSolver, BenchmarkRunner
from miplearn.problems.stab import MaxWeightStableSetGenerator
from scipy.stats import randint
import numpy as np
import pyomo.environ as pe
import os.path
def test_benchmark():
# Generate training and test instances
train_instances = MaxWeightStableSetGenerator(n=randint(low=25, high=26)).generate(5)
test_instances = MaxWeightStableSetGenerator(n=randint(low=25, high=26)).generate(3)
# Training phase...
training_solver = LearningSolver()
training_solver.parallel_solve(train_instances, n_jobs=10)
# Test phase...
test_solvers = {
"Strategy A": LearningSolver(),
"Strategy B": LearningSolver(),
}
benchmark = BenchmarkRunner(test_solvers)
benchmark.fit(train_instances)
benchmark.parallel_solve(test_instances, n_jobs=2, n_trials=2)
assert benchmark.raw_results().values.shape == (12,16)
benchmark.save_results("/tmp/benchmark.csv")
assert os.path.isfile("/tmp/benchmark.csv")
benchmark = BenchmarkRunner(test_solvers)
benchmark.load_results("/tmp/benchmark.csv")
assert benchmark.raw_results().values.shape == (12,16)