ANL-CEEESA/MIPLearn
1
0
Fork 0
mirror of https://github.com/ANL-CEEESA/MIPLearn.git synced 2025-12-06 09:28:51 -06:00
Code Issues Packages Projects Releases Wiki Activity

Break down RelaxationComponent into multiple steps

Browse Source
This commit is contained in:
Alinson S. Xavier
2020-12-05 20:34:29 -06:00
parent 6540c88cc5
commit 8bb9996384
3 changed files with 77 additions and 28 deletions
Download Patch File Download Diff File Expand all files Collapse all files

13
miplearn/components/tests/test_relaxation.py
View File

@@ -6,6 +6,7 @@ from unittest.mock import Mock, call
from miplearn import RelaxationComponent, LearningSolver, Instance, InternalSolver
from miplearn.classifiers import Classifier
from miplearn.components.relaxation import DropRedundantInequalitiesStep
def _setup():
@@ -64,7 +65,8 @@ def test_usage():
solver, internal, instance, classifiers = _setup()
component = RelaxationComponent()
component.classifiers = classifiers
drop_ineqs_step = component.steps[1]
drop_ineqs_step.classifiers = classifiers
# LearningSolver calls before_solve
component.before_solve(solver, instance, None)
@@ -97,10 +99,10 @@ def test_usage():
)
# Should ask ML to predict whether constraint should be removed
component.classifiers["type-a"].predict_proba.assert_called_once_with(
drop_ineqs_step.classifiers["type-a"].predict_proba.assert_called_once_with(
[[1.0, 0.0], [0.5, 0.5]]
)
component.classifiers["type-b"].predict_proba.assert_called_once_with([[1.0]])
drop_ineqs_step.classifiers["type-b"].predict_proba.assert_called_once_with([[1.0]])
# Should ask internal solver to remove constraints predicted as redundant
assert internal.extract_constraint.call_count == 2
@@ -131,7 +133,8 @@ def test_usage_with_check_dropped():
solver, internal, instance, classifiers = _setup()
component = RelaxationComponent(check_dropped=True, violation_tolerance=1e-3)
component.classifiers = classifiers
drop_ineqs_step = component.steps[1]
drop_ineqs_step.classifiers = classifiers
# LearningSolver call before_solve
component.before_solve(solver, instance, None)
@@ -169,7 +172,7 @@ def test_usage_with_check_dropped():
def test_x_y_fit_predict_evaluate():
instances = [Mock(spec=Instance), Mock(spec=Instance)]
component = RelaxationComponent(slack_tolerance=0.05, threshold=0.80)
component = DropRedundantInequalitiesStep(slack_tolerance=0.05, threshold=0.80)
component.classifiers = {
"type-a": Mock(spec=Classifier),
"type-b": Mock(spec=Classifier),