Reformat source code with Black; add pre-commit hooks and CI checks

This commit is contained in:
2020-12-05 10:59:33 -06:00
parent 3823931382
commit d99600f101
49 changed files with 1291 additions and 972 deletions

View File

@@ -4,10 +4,12 @@
from unittest.mock import Mock, call
from miplearn import (StaticLazyConstraintsComponent,
LearningSolver,
Instance,
InternalSolver)
from miplearn import (
StaticLazyConstraintsComponent,
LearningSolver,
Instance,
InternalSolver,
)
from miplearn.classifiers import Classifier
@@ -23,39 +25,47 @@ def test_usage_with_solver():
instance = Mock(spec=Instance)
instance.has_static_lazy_constraints = Mock(return_value=True)
instance.is_constraint_lazy = Mock(side_effect=lambda cid: {
"c1": False,
"c2": True,
"c3": True,
"c4": True,
}[cid])
instance.get_constraint_features = Mock(side_effect=lambda cid: {
"c2": [1.0, 0.0],
"c3": [0.5, 0.5],
"c4": [1.0],
}[cid])
instance.get_constraint_category = Mock(side_effect=lambda cid: {
"c2": "type-a",
"c3": "type-a",
"c4": "type-b",
}[cid])
instance.is_constraint_lazy = Mock(
side_effect=lambda cid: {
"c1": False,
"c2": True,
"c3": True,
"c4": True,
}[cid]
)
instance.get_constraint_features = Mock(
side_effect=lambda cid: {
"c2": [1.0, 0.0],
"c3": [0.5, 0.5],
"c4": [1.0],
}[cid]
)
instance.get_constraint_category = Mock(
side_effect=lambda cid: {
"c2": "type-a",
"c3": "type-a",
"c4": "type-b",
}[cid]
)
component = StaticLazyConstraintsComponent(threshold=0.90,
use_two_phase_gap=False,
violation_tolerance=1.0)
component = StaticLazyConstraintsComponent(
threshold=0.90, use_two_phase_gap=False, violation_tolerance=1.0
)
component.classifiers = {
"type-a": Mock(spec=Classifier),
"type-b": Mock(spec=Classifier),
}
component.classifiers["type-a"].predict_proba = \
Mock(return_value=[
component.classifiers["type-a"].predict_proba = Mock(
return_value=[
[0.20, 0.80],
[0.05, 0.95],
])
component.classifiers["type-b"].predict_proba = \
Mock(return_value=[
]
)
component.classifiers["type-b"].predict_proba = Mock(
return_value=[
[0.02, 0.98],
])
]
)
# LearningSolver calls before_solve
component.before_solve(solver, instance, None)
@@ -67,37 +77,59 @@ def test_usage_with_solver():
internal.get_constraint_ids.assert_called_once()
# Should ask if each constraint in the model is lazy
instance.is_constraint_lazy.assert_has_calls([
call("c1"), call("c2"), call("c3"), call("c4"),
])
instance.is_constraint_lazy.assert_has_calls(
[
call("c1"),
call("c2"),
call("c3"),
call("c4"),
]
)
# For the lazy ones, should ask for features
instance.get_constraint_features.assert_has_calls([
call("c2"), call("c3"), call("c4"),
])
instance.get_constraint_features.assert_has_calls(
[
call("c2"),
call("c3"),
call("c4"),
]
)
# Should also ask for categories
assert instance.get_constraint_category.call_count == 3
instance.get_constraint_category.assert_has_calls([
call("c2"), call("c3"), call("c4"),
])
instance.get_constraint_category.assert_has_calls(
[
call("c2"),
call("c3"),
call("c4"),
]
)
# Should ask internal solver to remove constraints identified as lazy
assert internal.extract_constraint.call_count == 3
internal.extract_constraint.assert_has_calls([
call("c2"), call("c3"), call("c4"),
])
internal.extract_constraint.assert_has_calls(
[
call("c2"),
call("c3"),
call("c4"),
]
)
# Should ask ML to predict whether each lazy constraint should be enforced
component.classifiers["type-a"].predict_proba.assert_called_once_with([[1.0, 0.0], [0.5, 0.5]])
component.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]])
# For the ones that should be enforced, should ask solver to re-add them
# to the formulation. The remaining ones should remain in the pool.
assert internal.add_constraint.call_count == 2
internal.add_constraint.assert_has_calls([
call("<c3>"), call("<c4>"),
])
internal.add_constraint.assert_has_calls(
[
call("<c3>"),
call("<c4>"),
]
)
internal.add_constraint.reset_mock()
# LearningSolver calls after_iteration (first time)
@@ -126,37 +158,45 @@ def test_usage_with_solver():
def test_fit():
instance_1 = Mock(spec=Instance)
instance_1.found_violated_lazy_constraints = ["c1", "c2", "c4", "c5"]
instance_1.get_constraint_category = Mock(side_effect=lambda cid: {
"c1": "type-a",
"c2": "type-a",
"c3": "type-a",
"c4": "type-b",
"c5": "type-b",
}[cid])
instance_1.get_constraint_features = Mock(side_effect=lambda cid: {
"c1": [1, 1],
"c2": [1, 2],
"c3": [1, 3],
"c4": [1, 4, 0],
"c5": [1, 5, 0],
}[cid])
instance_1.get_constraint_category = Mock(
side_effect=lambda cid: {
"c1": "type-a",
"c2": "type-a",
"c3": "type-a",
"c4": "type-b",
"c5": "type-b",
}[cid]
)
instance_1.get_constraint_features = Mock(
side_effect=lambda cid: {
"c1": [1, 1],
"c2": [1, 2],
"c3": [1, 3],
"c4": [1, 4, 0],
"c5": [1, 5, 0],
}[cid]
)
instance_2 = Mock(spec=Instance)
instance_2.found_violated_lazy_constraints = ["c2", "c3", "c4"]
instance_2.get_constraint_category = Mock(side_effect=lambda cid: {
"c1": "type-a",
"c2": "type-a",
"c3": "type-a",
"c4": "type-b",
"c5": "type-b",
}[cid])
instance_2.get_constraint_features = Mock(side_effect=lambda cid: {
"c1": [2, 1],
"c2": [2, 2],
"c3": [2, 3],
"c4": [2, 4, 0],
"c5": [2, 5, 0],
}[cid])
instance_2.get_constraint_category = Mock(
side_effect=lambda cid: {
"c1": "type-a",
"c2": "type-a",
"c3": "type-a",
"c4": "type-b",
"c5": "type-b",
}[cid]
)
instance_2.get_constraint_features = Mock(
side_effect=lambda cid: {
"c1": [2, 1],
"c2": [2, 2],
"c3": [2, 3],
"c4": [2, 4, 0],
"c5": [2, 5, 0],
}[cid]
)
instances = [instance_1, instance_2]
component = StaticLazyConstraintsComponent()
@@ -171,18 +211,22 @@ def test_fit():
}
expected_x = {
"type-a": [[1, 1], [1, 2], [1, 3], [2, 1], [2, 2], [2, 3]],
"type-b": [[1, 4, 0], [1, 5, 0], [2, 4, 0], [2, 5, 0]]
"type-b": [[1, 4, 0], [1, 5, 0], [2, 4, 0], [2, 5, 0]],
}
expected_y = {
"type-a": [[0, 1], [0, 1], [1, 0], [1, 0], [0, 1], [0, 1]],
"type-b": [[0, 1], [0, 1], [0, 1], [1, 0]]
"type-b": [[0, 1], [0, 1], [0, 1], [1, 0]],
}
assert component._collect_constraints(instances) == expected_constraints
assert component.x(instances) == expected_x
assert component.y(instances) == expected_y
component.fit(instances)
component.classifiers["type-a"].fit.assert_called_once_with(expected_x["type-a"],
expected_y["type-a"])
component.classifiers["type-b"].fit.assert_called_once_with(expected_x["type-b"],
expected_y["type-b"])
component.classifiers["type-a"].fit.assert_called_once_with(
expected_x["type-a"],
expected_y["type-a"],
)
component.classifiers["type-b"].fit.assert_called_once_with(
expected_x["type-b"],
expected_y["type-b"],
)