Replace Hashable by str

miplearn/components/dynamic_common.py

@@ -3,7 +3,7 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 import logging
-from typing import Dict, Hashable, List, Tuple, Optional, Any, Set
+from typing import Dict, List, Tuple, Optional, Any, Set
 
 import numpy as np
 from overrides import overrides
@@ -32,8 +32,8 @@ class DynamicConstraintsComponent(Component):
         assert isinstance(classifier, Classifier)
         self.threshold_prototype: Threshold = threshold
         self.classifier_prototype: Classifier = classifier
-        self.classifiers: Dict[Hashable, Classifier] = {}
-        self.thresholds: Dict[Hashable, Threshold] = {}
+        self.classifiers: Dict[str, Classifier] = {}
+        self.thresholds: Dict[str, Threshold] = {}
         self.known_cids: List[str] = []
         self.attr = attr
 
@@ -42,14 +42,14 @@ class DynamicConstraintsComponent(Component):
         instance: Optional[Instance],
         sample: Sample,
     ) -> Tuple[
-        Dict[Hashable, List[List[float]]],
-        Dict[Hashable, List[List[bool]]],
-        Dict[Hashable, List[str]],
+        Dict[str, List[List[float]]],
+        Dict[str, List[List[bool]]],
+        Dict[str, List[str]],
     ]:
         assert instance is not None
-        x: Dict[Hashable, List[List[float]]] = {}
-        y: Dict[Hashable, List[List[bool]]] = {}
-        cids: Dict[Hashable, List[str]] = {}
+        x: Dict[str, List[List[float]]] = {}
+        y: Dict[str, List[List[bool]]] = {}
+        cids: Dict[str, List[str]] = {}
         constr_categories_dict = instance.get_constraint_categories()
         constr_features_dict = instance.get_constraint_features()
         instance_features = sample.get("instance_features_user")
@@ -111,8 +111,8 @@ class DynamicConstraintsComponent(Component):
         self,
         instance: Instance,
         sample: Sample,
-    ) -> List[Hashable]:
-        pred: List[Hashable] = []
+    ) -> List[str]:
+        pred: List[str] = []
         if len(self.known_cids) == 0:
             logger.info("Classifiers not fitted. Skipping.")
             return pred
@@ -137,8 +137,8 @@ class DynamicConstraintsComponent(Component):
     @overrides
     def fit_xy(
         self,
-        x: Dict[Hashable, np.ndarray],
-        y: Dict[Hashable, np.ndarray],
+        x: Dict[str, np.ndarray],
+        y: Dict[str, np.ndarray],
     ) -> None:
         for category in x.keys():
             self.classifiers[category] = self.classifier_prototype.clone()
@@ -153,14 +153,14 @@ class DynamicConstraintsComponent(Component):
         self,
         instance: Instance,
         sample: Sample,
-    ) -> Dict[Hashable, Dict[str, float]]:
+    ) -> Dict[str, Dict[str, float]]:
         actual = sample.get(self.attr)
         assert actual is not None
         pred = set(self.sample_predict(instance, sample))
-        tp: Dict[Hashable, int] = {}
-        tn: Dict[Hashable, int] = {}
-        fp: Dict[Hashable, int] = {}
-        fn: Dict[Hashable, int] = {}
+        tp: Dict[str, int] = {}
+        tn: Dict[str, int] = {}
+        fp: Dict[str, int] = {}
+        fn: Dict[str, int] = {}
         constr_categories_dict = instance.get_constraint_categories()
         for cid in self.known_cids:
             if cid not in constr_categories_dict: