Convert ConstraintFeatures to dataclass

miplearn/components/lazy_static.py

@@ -3,11 +3,9 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 import logging
-import sys
-from typing import Dict, Tuple, Optional, List, Hashable, Any, TYPE_CHECKING, Set
+from typing import Dict, Tuple, List, Hashable, Any, TYPE_CHECKING, Set
 
 import numpy as np
-from tqdm.auto import tqdm
 
 from miplearn import Classifier
 from miplearn.classifiers.counting import CountingClassifier
@@ -71,7 +69,7 @@ class StaticLazyConstraintsComponent(Component):
         logger.info("Moving lazy constraints to the pool...")
         self.pool = {}
         for (cid, cdict) in features.constraints.items():
-            if cdict["Lazy"] and cid not in self.enforced_cids:
+            if cdict.lazy and cid not in self.enforced_cids:
                 self.pool[cid] = LazyConstraint(
                     cid=cid,
                     obj=solver.internal_solver.extract_constraint(cid),
@@ -152,10 +150,10 @@ class StaticLazyConstraintsComponent(Component):
 
         x, y = self.sample_xy(features, sample)
         category_to_cids: Dict[Hashable, List[str]] = {}
-        for (cid, cdict) in features.constraints.items():
-            if "Category" not in cdict or cdict["Category"] is None:
+        for (cid, cfeatures) in features.constraints.items():
+            if cfeatures.category is None:
                 continue
-            category = cdict["Category"]
+            category = cfeatures.category
             if category not in category_to_cids:
                 category_to_cids[category] = []
             category_to_cids[category] += [cid]
@@ -181,15 +179,15 @@ class StaticLazyConstraintsComponent(Component):
         x: Dict = {}
         y: Dict = {}
         for (cid, cfeatures) in features.constraints.items():
-            if not cfeatures["Lazy"]:
+            if not cfeatures.lazy:
                 continue
-            category = cfeatures["Category"]
+            category = cfeatures.category
             if category is None:
                 continue
             if category not in x:
                 x[category] = []
                 y[category] = []
-            x[category] += [cfeatures["User features"]]
+            x[category] += [cfeatures.user_features]
             if "LazyStatic: Enforced" in sample:
                 if cid in sample["LazyStatic: Enforced"]:
                     y[category] += [[False, True]]

miplearn/components/objective.py

@@ -78,6 +78,7 @@ class ObjectiveValueComponent(Component):
         sample: TrainingSample,
     ) -> Tuple[Dict[Hashable, List[List[float]]], Dict[Hashable, List[List[float]]]]:
         assert features.instance is not None
+        assert features.instance.user_features is not None
         x: Dict[Hashable, List[List[float]]] = {}
         y: Dict[Hashable, List[List[float]]] = {}
         f = list(features.instance.user_features)

miplearn/features.py

@@ -2,9 +2,9 @@
 #  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-import numbers
 import collections
-from typing import TYPE_CHECKING, Dict, Hashable
+import numbers
+from typing import TYPE_CHECKING, Dict
 
 from miplearn.types import (
     Features,
@@ -87,17 +87,15 @@ class FeaturesExtractor:
                     f"Constraint features must be a list of floats. "
                     f"Found {type(user_features[0]).__name__} instead for cid={cid}."
                 )
-            constraints[cid] = {
-                "RHS": self.solver.get_constraint_rhs(cid),
-                "LHS": self.solver.get_constraint_lhs(cid),
-                "Sense": self.solver.get_constraint_sense(cid),
-                "Category": category,
-                "User features": user_features,
-            }
+            constraints[cid] = ConstraintFeatures(
+                rhs=self.solver.get_constraint_rhs(cid),
+                lhs=self.solver.get_constraint_lhs(cid),
+                sense=self.solver.get_constraint_sense(cid),
+                category=category,
+                user_features=user_features,
+            )
             if has_static_lazy:
-                constraints[cid]["Lazy"] = instance.is_constraint_lazy(cid)
-            else:
-                constraints[cid]["Lazy"] = False
+                constraints[cid].lazy = instance.is_constraint_lazy(cid)
         return constraints
 
     @staticmethod
@@ -118,7 +116,7 @@ class FeaturesExtractor:
             )
         lazy_count = 0
         for (cid, cdict) in features.constraints.items():
-            if cdict["Lazy"]:
+            if cdict.lazy:
                 lazy_count += 1
         return InstanceFeatures(
             user_features=user_features,

miplearn/types.py

@@ -81,7 +81,7 @@ LearningSolveStats = TypedDict(
 
 @dataclass
 class InstanceFeatures:
-    user_features: List[float]
+    user_features: Optional[List[float]] = None
     lazy_constraint_count: int = 0
 
 
@@ -91,18 +91,14 @@ class VariableFeatures:
     user_features: Optional[List[float]] = None
 
 
-ConstraintFeatures = TypedDict(
-    "ConstraintFeatures",
-    {
-        "RHS": float,
-        "LHS": Dict[str, float],
-        "Sense": str,
-        "Category": Optional[Hashable],
-        "User features": Optional[List[float]],
-        "Lazy": bool,
-    },
-    total=False,
-)
+@dataclass
+class ConstraintFeatures:
+    rhs: Optional[float] = None
+    lhs: Optional[Dict[str, float]] = None
+    sense: Optional[str] = None
+    category: Optional[Hashable] = None
+    user_features: Optional[List[float]] = None
+    lazy: bool = False
 
 
 @dataclass

tests/components/test_lazy_static.py

@@ -17,6 +17,7 @@ from miplearn.types import (
     Features,
     LearningSolveStats,
     InstanceFeatures,
+    ConstraintFeatures,
 )
 
 
@@ -35,31 +36,31 @@ def features() -> Features:
             lazy_constraint_count=4,
         ),
         constraints={
-            "c1": {
-                "Category": "type-a",
-                "User features": [1.0, 1.0],
-                "Lazy": True,
-            },
-            "c2": {
-                "Category": "type-a",
-                "User features": [1.0, 2.0],
-                "Lazy": True,
-            },
-            "c3": {
-                "Category": "type-a",
-                "User features": [1.0, 3.0],
-                "Lazy": True,
-            },
-            "c4": {
-                "Category": "type-b",
-                "User features": [1.0, 4.0, 0.0],
-                "Lazy": True,
-            },
-            "c5": {
-                "Category": "type-b",
-                "User features": [1.0, 5.0, 0.0],
-                "Lazy": False,
-            },
+            "c1": ConstraintFeatures(
+                category="type-a",
+                user_features=[1.0, 1.0],
+                lazy=True,
+            ),
+            "c2": ConstraintFeatures(
+                category="type-a",
+                user_features=[1.0, 2.0],
+                lazy=True,
+            ),
+            "c3": ConstraintFeatures(
+                category="type-a",
+                user_features=[1.0, 3.0],
+                lazy=True,
+            ),
+            "c4": ConstraintFeatures(
+                category="type-b",
+                user_features=[1.0, 4.0, 0.0],
+                lazy=True,
+            ),
+            "c5": ConstraintFeatures(
+                category="type-b",
+                user_features=[1.0, 5.0, 0.0],
+                lazy=False,
+            ),
         },
     )
 

tests/test_features.py

@@ -4,7 +4,7 @@
 
 from miplearn import GurobiSolver
 from miplearn.features import FeaturesExtractor
-from miplearn.types import VariableFeatures, InstanceFeatures
+from miplearn.types import VariableFeatures, InstanceFeatures, ConstraintFeatures
 from tests.fixtures.knapsack import get_knapsack_instance
 
 
@@ -36,19 +36,19 @@ def test_knapsack() -> None:
             }
         }
         assert instance.features.constraints == {
-            "eq_capacity": {
-                "LHS": {
+            "eq_capacity": ConstraintFeatures(
+                lhs={
                     "x[0]": 23.0,
                     "x[1]": 26.0,
                     "x[2]": 20.0,
                     "x[3]": 18.0,
                 },
-                "Sense": "<",
-                "RHS": 67.0,
-                "Lazy": False,
-                "Category": "eq_capacity",
-                "User features": [0.0],
-            }
+                sense="<",
+                rhs=67.0,
+                lazy=False,
+                category="eq_capacity",
+                user_features=[0.0],
+            )
         }
         assert instance.features.instance == InstanceFeatures(
             user_features=[67.0, 21.75],