implement doctests cleanup

Author: voorhs

autointent/modules/scoring/_description/description.py

@@ -42,13 +42,20 @@ class DescriptionScorer(ScoringModule):
 
     Examples
     --------
+    .. testsetup::
+
+        db_dir = "doctests-db"
+
     .. testcode::
 
         from autointent.modules import DescriptionScorer
         utterances = ["what is your name?", "how old are you?"]
         labels = [0, 1]
         descriptions = ["greeting", "age-related question"]
-        scorer = DescriptionScorer(embedder_name="sergeyzh/rubert-tiny-turbo", temperature=1.0)
+        scorer = DescriptionScorer(
+            embedder_name="sergeyzh/rubert-tiny-turbo",
+            db_dir=db_dir
+        )
         scorer.fit(utterances, labels, descriptions)
         scores = scorer.predict(["tell me about your age?"])
         print(scores)  # Outputs similarity scores for the utterance against all descriptions
@@ -57,6 +64,11 @@ class DescriptionScorer(ScoringModule):
 
         [[0.47210786 0.5278922 ]]
 
+    .. testcleanup::
+
+        import shutil
+        shutil.rmtree(db_dir)
+
     """
 
     weights_file_name: str = "description_vectors.npy"

autointent/modules/scoring/_dnnc/dnnc.py

@@ -57,6 +57,10 @@ class DNNCScorer(ScoringModule):
 
     Examples
     --------
+    .. testsetup::
+
+        db_dir = "doctests-db"
+
     .. testcode::
 
         from autointent.modules.scoring import DNNCScorer
@@ -66,6 +70,7 @@ class DNNCScorer(ScoringModule):
             cross_encoder_name="cross-encoder/ms-marco-MiniLM-L-6-v2",
             embedder_name="sergeyzh/rubert-tiny-turbo",
             k=5,
+            db_dir=db_dir,
         )
         scorer.fit(utterances, labels)
 
@@ -79,6 +84,11 @@ class DNNCScorer(ScoringModule):
         [[-8.90408421  0.        ]
          [-8.10923195  0.        ]]
 
+    .. testcleanup::
+
+        import shutil
+        shutil.rmtree(db_dir)
+
     """
 
     name = "dnnc"

autointent/modules/scoring/_knn/knn.py

@@ -47,6 +47,10 @@ class KNNScorer(ScoringModule):
 
     Examples
     --------
+    .. testsetup::
+
+        db_dir = "doctests-db"
+
     .. testcode::
 
         from autointent.modules.scoring import KNNScorer
@@ -55,6 +59,7 @@ class KNNScorer(ScoringModule):
         scorer = KNNScorer(
             embedder_name="sergeyzh/rubert-tiny-turbo",
             k=5,
+            db_dir=db_dir,
         )
         scorer.fit(utterances, labels)
         test_utterances = ["hi", "what's up?"]
@@ -66,6 +71,11 @@ class KNNScorer(ScoringModule):
         [[0.67297815 0.32702185]
          [0.44031678 0.55968322]]
 
+    .. testcleanup::
+
+        import shutil
+        shutil.rmtree(db_dir)
+
     """
 
     weights: WEIGHT_TYPES

autointent/modules/scoring/_linear.py

@@ -69,7 +69,7 @@ def __init__(
         self,
         embedder_name: str,
         cv: int = 3,
-        n_jobs: int = -1,
+        n_jobs: int | None = None,
         device: str = "cpu",
         seed: int = 0,
         batch_size: int = 32,

autointent/modules/scoring/_mlknn/mlknn.py

@@ -59,6 +59,10 @@ class MLKnnScorer(ScoringModule):
 
     Example
     --------
+    .. testsetup::
+
+        db_dir = "doctests-db"
+
     .. testcode::
 
         from autointent.modules.scoring import MLKnnScorer
@@ -67,6 +71,7 @@ class MLKnnScorer(ScoringModule):
         scorer = MLKnnScorer(
             k=5,
             embedder_name="sergeyzh/rubert-tiny-turbo",
+            db_dir=db_dir,
         )
         scorer.fit(utterances, labels)
         test_utterances = ["Hi!", "What's up?"]
@@ -78,6 +83,11 @@ class MLKnnScorer(ScoringModule):
         [[0.5 0.5]
          [0.5 0.5]]
 
+    .. testcleanup::
+
+        import shutil
+        shutil.rmtree(db_dir)
+
     """
 
     arrays_filename: str = "probs.npz"