Further sklearn version checks in compatibility test

tests/backwardscompat/test_models.py

@@ -25,11 +25,16 @@ def test_regression_model_backward_compatibility_v0_2_0(pickle_file, diabetesReg
     Tests for compatibility with models created with v0.2.0 using create_test_models.py
     """
     sklearn_version = Version(sklearn)
+
     if not sklearn_version.is_at_most(1, 0, 2):
         # NOTE: sklearn is breaking persisted objects with newer versions (e.g. OneHotEncoder),
         # so we can only run this test with the correct sklearn version
         pytest.skip("This test is only compatible with sklearn <= 1.0.2")
+
+    if "RandomForest" in pickle_file:
+        if not sklearn_version.is_equal(1, 0, 2):
+            pytest.skip("This test is only compatible with sklearn == 1.0.2")
+
     d = load_pickle(pickle_file)
     r2, model = d["R2"], d["model"]
     diabetesRegressionTestCase.testMinR2(model, r2-0.02, fit=False)
-

tox.ini

@@ -61,10 +61,10 @@ deps =
 ;     and lead to non-ending builds (2.5h+) on github. This dependency should be installable with pip install sensai[torch] though...
     pytorch-lightning>=1.1
 ; No pinned requirements included except sklearn, so relaxed versions created by setup.py apply.
-; We use sklearn version 1.0.2, because it is the latest version that is still compatible with the lowest version we support.
+; We use sklearn version 1.0.2, because it was used to persist the v0.2.0 compatibility test models.
     scikit-learn==1.0.2
 extras =
-    full
+    torch
 
 [testenv:docs]
 commands =