Update UserCutsComponent

miplearn/components/dynamic_lazy.py

@@ -41,7 +41,7 @@ class DynamicLazyConstraintsComponent(Component):
         self.classifiers = self.dynamic.classifiers
         self.thresholds = self.dynamic.thresholds
         self.known_cids = self.dynamic.known_cids
-        self.lazy_enforced: Set[str] = set()
+        self.lazy_enforced: Set[Hashable] = set()
 
     @staticmethod
     def enforce(

miplearn/components/dynamic_user_cuts.py

@@ -38,20 +38,19 @@ class UserCutsComponent(Component):
         self.n_added_in_callback = 0
 
     @overrides
-    def before_solve_mip_old(
+    def before_solve_mip(
         self,
         solver: "LearningSolver",
         instance: "Instance",
         model: Any,
         stats: LearningSolveStats,
-        features: Features,
-        training_data: TrainingSample,
+        sample: Sample,
     ) -> None:
         assert solver.internal_solver is not None
         self.enforced.clear()
         self.n_added_in_callback = 0
         logger.info("Predicting violated user cuts...")
-        cids = self.dynamic.sample_predict_old(instance, training_data)
+        cids = self.dynamic.sample_predict(instance, sample)
         logger.info("Enforcing %d user cuts ahead-of-time..." % len(cids))
         for cid in cids:
             instance.enforce_user_cut(solver.internal_solver, model, cid)
@@ -80,34 +79,27 @@ class UserCutsComponent(Component):
             logger.debug(f"Added {len(cids)} violated user cuts")
 
     @overrides
-    def after_solve_mip_old(
+    def after_solve_mip(
         self,
         solver: "LearningSolver",
         instance: "Instance",
         model: Any,
         stats: LearningSolveStats,
-        features: Features,
-        training_data: TrainingSample,
+        sample: Sample,
     ) -> None:
-        training_data.user_cuts_enforced = set(self.enforced)
+        assert sample.after_mip is not None
+        assert sample.after_mip.extra is not None
+        sample.after_mip.extra["user_cuts_enforced"] = set(self.enforced)
         stats["UserCuts: Added in callback"] = self.n_added_in_callback
         if self.n_added_in_callback > 0:
             logger.info(f"{self.n_added_in_callback} user cuts added in callback")
 
     # Delegate ML methods to self.dynamic
     # -------------------------------------------------------------------
-    @overrides
-    def sample_xy_old(
-        self,
-        instance: "Instance",
-        sample: TrainingSample,
-    ) -> Tuple[Dict, Dict]:
-        return self.dynamic.sample_xy_old(instance, sample)
-
     @overrides
     def sample_xy(
         self,
-        instance: Optional[Instance],
+        instance: "Instance",
         sample: Sample,
     ) -> Tuple[Dict, Dict]:
         return self.dynamic.sample_xy(instance, sample)
@@ -115,13 +107,13 @@ class UserCutsComponent(Component):
     def sample_predict(
         self,
         instance: "Instance",
-        sample: TrainingSample,
+        sample: Sample,
     ) -> List[Hashable]:
         return self.dynamic.sample_predict(instance, sample)
 
     @overrides
-    def fit_old(self, training_instances: List["Instance"]) -> None:
-        self.dynamic.fit_old(training_instances)
+    def fit(self, training_instances: List["Instance"]) -> None:
+        self.dynamic.fit(training_instances)
 
     @overrides
     def fit_xy(
@@ -132,9 +124,9 @@ class UserCutsComponent(Component):
         self.dynamic.fit_xy(x, y)
 
     @overrides
-    def sample_evaluate_old(
+    def sample_evaluate(
         self,
         instance: "Instance",
-        sample: TrainingSample,
+        sample: Sample,
     ) -> Dict[Hashable, Dict[str, float]]:
-        return self.dynamic.sample_evaluate_old(instance, sample)
+        return self.dynamic.sample_evaluate(instance, sample)