From 9aa3e34184360c671159cb1ee4bae3f3c712a063 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ale=C5=A1=20Erjavec?= <ales.erjavec@fri.uni-lj.si>
Date: Wed, 16 Oct 2024 10:20:34 +0200
Subject: [PATCH] owcalibratedlearner: Never return base_learner instance from
 create_learner

The instance's name is modified in place after.

Replace IdentityWrapper (which did not work) with copy.deepcopy of the instance.
---
 Orange/widgets/model/owcalibratedlearner.py          | 12 ++++++------
 .../widgets/model/tests/test_owcalibratedlearner.py  |  2 +-
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/Orange/widgets/model/owcalibratedlearner.py b/Orange/widgets/model/owcalibratedlearner.py
index 7b4009573e9..549d5b2bb2d 100644
--- a/Orange/widgets/model/owcalibratedlearner.py
+++ b/Orange/widgets/model/owcalibratedlearner.py
@@ -1,3 +1,5 @@
+import copy
+
 from Orange.classification import CalibratedLearner, ThresholdLearner, \
     NaiveBayesLearner
 from Orange.data import Table
@@ -65,7 +67,6 @@ def set_learner(self, learner):
         self.learner = self.model = None
 
     def _set_default_name(self):
-
         if self.base_learner is None:
             self.set_default_learner_name("")
         else:
@@ -80,10 +81,6 @@ def calibration_options_changed(self):
         self.apply()
 
     def create_learner(self):
-        class IdentityWrapper(Learner):
-            def fit_storage(self, data):
-                return self.base_learner.fit_storage(data)
-
         if self.base_learner is None:
             return None
         learner = self.base_learner
@@ -95,8 +92,11 @@ def fit_storage(self, data):
                                        self.ThresholdMap[self.threshold])
         if self.preprocessors:
             if learner is self.base_learner:
-                learner = IdentityWrapper()
+                learner = copy.deepcopy(learner)
             learner.preprocessors = (self.preprocessors, )
+        if learner is self.base_learner:
+            learner = copy.deepcopy(learner)
+        assert learner is not self.base_learner
         return learner
 
     def get_learner_parameters(self):
diff --git a/Orange/widgets/model/tests/test_owcalibratedlearner.py b/Orange/widgets/model/tests/test_owcalibratedlearner.py
index 27dcf378bc6..2058d73db6f 100644
--- a/Orange/widgets/model/tests/test_owcalibratedlearner.py
+++ b/Orange/widgets/model/tests/test_owcalibratedlearner.py
@@ -95,7 +95,7 @@ def test_create_learner(self):
         widget.calibration = widget.NoCalibration
         widget.threshold = widget.NoThresholdOptimization
         learner = self.widget.create_learner()
-        self.assertIs(learner, self.widget.base_learner)
+        self.assertIsNot(learner, self.widget.base_learner)
 
         widget.calibration = widget.SigmoidCalibration
         widget.threshold = widget.OptimizeF1