Finish rewrite of user cuts component

tests/classifiers/test_adaptive.py

@@ -5,8 +5,8 @@
 from numpy.linalg import norm
 from sklearn.svm import SVC
 
-from miplearn import AdaptiveClassifier, ScikitLearnClassifier
-from miplearn.classifiers.adaptive import CandidateClassifierSpecs
+from miplearn.classifiers.adaptive import CandidateClassifierSpecs, AdaptiveClassifier
+from miplearn.classifiers.sklearn import ScikitLearnClassifier
 from tests.classifiers import _build_circle_training_data
 
 

tests/components/steps/test_drop_redundant.py

@@ -6,10 +6,11 @@ from unittest.mock import Mock, call
 
 import numpy as np
 
-from miplearn import RelaxIntegralityStep, GurobiSolver
 from miplearn.classifiers import Classifier
 from miplearn.components.steps.drop_redundant import DropRedundantInequalitiesStep
+from miplearn.components.steps.relax_integrality import RelaxIntegralityStep
 from miplearn.instance import Instance
+from miplearn.solvers.gurobi import GurobiSolver
 from miplearn.solvers.internal import InternalSolver
 from miplearn.solvers.learning import LearningSolver
 from miplearn.features import TrainingSample, Features

tests/components/test_component.py

@@ -3,7 +3,8 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 from unittest.mock import Mock
 
-from miplearn import Component, Instance
+from miplearn.components.component import Component
+from miplearn.instance import Instance
 
 
 def test_xy_instance():

tests/components/test_dynamic_lazy.py

@@ -8,16 +8,16 @@ import numpy as np
 import pytest
 from numpy.testing import assert_array_equal
 
-from miplearn import Instance
 from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import MinProbabilityThreshold
 from miplearn.components import classifier_evaluation_dict
-from miplearn.components.lazy_dynamic import DynamicLazyConstraintsComponent
+from miplearn.components.dynamic_lazy import DynamicLazyConstraintsComponent
 from miplearn.features import (
     TrainingSample,
     Features,
     InstanceFeatures,
 )
+from miplearn.instance import Instance
 
 E = 0.1
 
@@ -144,7 +144,7 @@ def test_fit(training_instances: List[Instance]) -> None:
 
 def test_sample_predict_evaluate(training_instances: List[Instance]) -> None:
     comp = DynamicLazyConstraintsComponent()
-    comp.known_cids = ["c1", "c2", "c3", "c4"]
+    comp.known_cids.extend(["c1", "c2", "c3", "c4"])
     comp.thresholds["type-a"] = MinProbabilityThreshold([0.5, 0.5])
     comp.thresholds["type-b"] = MinProbabilityThreshold([0.5, 0.5])
     comp.classifiers["type-a"] = Mock(spec=Classifier)

tests/components/test_dynamic_user_cuts.py

@@ -11,8 +11,10 @@ import pytest
 from gurobipy import GRB
 from networkx import Graph
 
-from miplearn import Instance, LearningSolver, GurobiSolver
-from miplearn.components.user_cuts import UserCutsComponentNG
+from miplearn.components.dynamic_user_cuts import UserCutsComponent
+from miplearn.instance import Instance
+from miplearn.solvers.gurobi import GurobiSolver
+from miplearn.solvers.learning import LearningSolver
 
 logger = logging.getLogger(__name__)
 
@@ -20,12 +22,11 @@ logger = logging.getLogger(__name__)
 class GurobiStableSetProblem(Instance):
     def __init__(self, graph: Graph) -> None:
         super().__init__()
-        self.graph = graph
-        self.nodes = list(self.graph.nodes)
+        self.graph: Graph = graph
 
     def to_model(self) -> Any:
         model = gp.Model()
-        x = [model.addVar(vtype=GRB.BINARY) for _ in range(len(self.nodes))]
+        x = [model.addVar(vtype=GRB.BINARY) for _ in range(len(self.graph.nodes))]
         model.setObjective(gp.quicksum(x), GRB.MAXIMIZE)
         for e in list(self.graph.edges):
             model.addConstr(x[e[0]] + x[e[1]] <= 1)
@@ -39,16 +40,14 @@ class GurobiStableSetProblem(Instance):
         vals = model.cbGetNodeRel(model.getVars())
         violations = []
         for clique in nx.find_cliques(self.graph):
-            lhs = sum(vals[i] for i in clique)
-            if lhs > 1:
+            if sum(vals[i] for i in clique) > 1:
                 violations += [frozenset(clique)]
         return violations
 
-    def build_user_cut(self, model: Any, violation: Hashable) -> Any:
-        assert isinstance(violation, FrozenSet)
+    def build_user_cut(self, model: Any, cid: Hashable) -> Any:
+        assert isinstance(cid, FrozenSet)
         x = model.getVars()
-        cut = gp.quicksum([x[i] for i in violation]) <= 1
-        return cut
+        return gp.quicksum([x[i] for i in cid]) <= 1
 
 
 @pytest.fixture
@@ -62,7 +61,7 @@ def solver() -> LearningSolver:
     return LearningSolver(
         solver=lambda: GurobiSolver(),
         components=[
-            UserCutsComponentNG(),
+            UserCutsComponent(),
         ],
     )
 
@@ -71,7 +70,17 @@ def test_usage(
     stab_instance: Instance,
     solver: LearningSolver,
 ) -> None:
-    solver.solve(stab_instance)
+    stats_before = solver.solve(stab_instance)
     sample = stab_instance.training_data[0]
     assert sample.user_cuts_enforced is not None
     assert len(sample.user_cuts_enforced) > 0
+    print(stats_before)
+    assert stats_before["UserCuts: Added ahead-of-time"] == 0
+    assert stats_before["UserCuts: Added in callback"] > 0
+
+    solver.fit([stab_instance])
+    stats_after = solver.solve(stab_instance)
+    assert (
+        stats_after["UserCuts: Added ahead-of-time"]
+        == stats_before["UserCuts: Added in callback"]
+    )

tests/components/test_objective.py

@@ -7,9 +7,12 @@ from unittest.mock import Mock
 import pytest
 from numpy.testing import assert_array_equal
 
-from miplearn import GurobiPyomoSolver, LearningSolver, Regressor, Instance
+from miplearn.classifiers import Regressor
 from miplearn.components.objective import ObjectiveValueComponent
 from miplearn.features import TrainingSample, InstanceFeatures, Features
+from miplearn.instance import Instance
+from miplearn.solvers.learning import LearningSolver
+from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver
 from tests.fixtures.knapsack import get_knapsack_instance
 
 import numpy as np

tests/components/test_primal.py

@@ -8,12 +8,14 @@ import numpy as np
 from numpy.testing import assert_array_equal
 from scipy.stats import randint
 
-from miplearn import Classifier, LearningSolver, Instance
+from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import Threshold
 from miplearn.components import classifier_evaluation_dict
 from miplearn.components.primal import PrimalSolutionComponent
+from miplearn.instance import Instance
 from miplearn.problems.tsp import TravelingSalesmanGenerator
 from miplearn.features import TrainingSample, VariableFeatures, Features
+from miplearn.solvers.learning import LearningSolver
 
 
 def test_xy() -> None:

tests/components/test_static_lazy.py

@@ -8,10 +8,12 @@ import numpy as np
 import pytest
 from numpy.testing import assert_array_equal
 
-from miplearn import LearningSolver, InternalSolver, Instance
 from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import Threshold, MinProbabilityThreshold
-from miplearn.components.lazy_static import StaticLazyConstraintsComponent
+from miplearn.components.static_lazy import StaticLazyConstraintsComponent
+from miplearn.instance import Instance
+from miplearn.solvers.internal import InternalSolver
+from miplearn.solvers.learning import LearningSolver
 from miplearn.types import (
     LearningSolveStats,
 )

tests/fixtures/knapsack.py

@@ -1,10 +1,12 @@
 #  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 BasePyomoSolver, GurobiSolver, InternalSolver, Instance
+from miplearn.instance import Instance
 from miplearn.problems.knapsack import KnapsackInstance, GurobiKnapsackInstance
+from miplearn.solvers.gurobi import GurobiSolver
+from miplearn.solvers.internal import InternalSolver
 from miplearn.solvers.learning import LearningSolver
+from miplearn.solvers.pyomo.base import BasePyomoSolver
 from tests.solvers import _is_subclass_or_instance
 
 

tests/fixtures/redundant.py

@@ -3,9 +3,11 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 from typing import Any
 
-from miplearn import Instance, BasePyomoSolver, GurobiSolver
 import pyomo.environ as pe
 
+from miplearn.instance import Instance
+from miplearn.solvers.gurobi import GurobiSolver
+from miplearn.solvers.pyomo.base import BasePyomoSolver
 from tests.solvers import _is_subclass_or_instance
 
 

tests/problems/test_tsp.py

@@ -67,7 +67,6 @@ def test_subtour():
     solver = LearningSolver()
     solver.solve(instance)
     assert len(instance.training_data[0].lazy_enforced) > 0
-    assert hasattr(instance, "found_violated_user_cuts")
     x = instance.training_data[0].solution["x"]
     assert x[0, 1] == 1.0
     assert x[0, 4] == 1.0

tests/test_benchmark.py

@@ -30,7 +30,7 @@ def test_benchmark():
         benchmark = BenchmarkRunner(test_solvers)
         benchmark.fit(train_instances)
         benchmark.parallel_solve(test_instances, n_jobs=n_jobs, n_trials=2)
-        assert benchmark.results.values.shape == (12, 18)
+        assert benchmark.results.values.shape == (12, 20)
 
         benchmark.write_csv("/tmp/benchmark.csv")
         assert os.path.isfile("/tmp/benchmark.csv")

tests/test_features.py

@@ -2,13 +2,13 @@
 #  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-from miplearn import GurobiSolver
 from miplearn.features import (
     FeaturesExtractor,
     InstanceFeatures,
     VariableFeatures,
     ConstraintFeatures,
 )
+from miplearn.solvers.gurobi import GurobiSolver
 from tests.fixtures.knapsack import get_knapsack_instance
 
 

tests/test_instance.py

@@ -3,8 +3,8 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 import tempfile
 
-from miplearn import GurobiSolver
 from miplearn.instance import write_pickle_gz, PickleGzInstance
+from miplearn.solvers.gurobi import GurobiSolver
 from tests.fixtures.knapsack import get_knapsack_instance