scikit-learn · NicolasHug · Apr 9, 2020 · Apr 9, 2020 · Apr 9, 2020 · Apr 10, 2020
diff --git a/sklearn/decomposition/_sparse_pca.py b/sklearn/decomposition/_sparse_pca.py
@@ -233,9 +233,10 @@ def transform(self, X):
         return U
 
     def _more_tags(self):
+        from sklearn.utils.estimator_checks import check_methods_subset_invariance  # noqa
         return {
             '_xfail_checks': {
-                "check_methods_subset_invariance":
+                check_methods_subset_invariance:
                 "fails for the transform method"
             }
         }

diff --git a/sklearn/dummy.py b/sklearn/dummy.py
@@ -356,10 +356,11 @@ def predict_log_proba(self, X):
             return [np.log(p) for p in proba]
 
     def _more_tags(self):
+        from sklearn.utils.estimator_checks import check_methods_subset_invariance  # noqa
         return {
             'poor_score': True, 'no_validation': True,
             '_xfail_checks': {
-                'check_methods_subset_invariance':
+                check_methods_subset_invariance:
                 'fails for the predict method'
             }
         }

diff --git a/sklearn/neural_network/_rbm.py b/sklearn/neural_network/_rbm.py
@@ -374,9 +374,10 @@ def fit(self, X, y=None):
         return self
 
     def _more_tags(self):
+        from sklearn.utils.estimator_checks import check_methods_subset_invariance  # noqa
         return {
             '_xfail_checks': {
-                'check_methods_subset_invariance':
+                check_methods_subset_invariance:
                 'fails for the decision_function method'
             }
         }
diff --git a/sklearn/svm/_classes.py b/sklearn/svm/_classes.py
@@ -854,11 +854,13 @@ def __init__(self, nu=0.5, kernel='rbf', degree=3, gamma='scale',
             random_state=random_state)
 
     def _more_tags(self):
+        from ..utils.estimator_checks import check_class_weight_classifiers  # noqa
+        from ..utils.estimator_checks import check_methods_subset_invariance  # noqa
         return {
             '_xfail_checks': {
-                'check_methods_subset_invariance':
+                check_methods_subset_invariance:
                 'fails for the decision_function method',
-                'check_class_weight_classifiers': 'class_weight is ignored.'
+                check_class_weight_classifiers: 'class_weight is ignored.'
             }
         }
 

diff --git a/sklearn/tests/test_gonna_be_removed_dont_worry.py b/sklearn/tests/test_gonna_be_removed_dont_worry.py
@@ -0,0 +1,59 @@
+# Should be in test_estimator_checks. Putting this here temporarily because I'm
+# too lazy to make it work without pytest.
+
+# import functools
+import pytest
+from sklearn.linear_model import LogisticRegression
+from sklearn.exceptions import SkipTestWarning
+from sklearn.utils.estimator_checks import check_estimator
+# from sklearn.utils.estimator_checks import some_strict_check
+# from sklearn.utils.estimator_checks import some_partially_strict_check
+
+
+def test_strict_mode(capsys):
+
+    est = LogisticRegression()
+    with pytest.warns(SkipTestWarning, match='strict mode is off'):
+        check_estimator(est, strict_mode=False)
+
+    expected_out = 'in non-strict part of some_partially_strict_check\n'
+    assert capsys.readouterr().out == expected_out
+
+    check_estimator(est, strict_mode=True)
+    expected_output = (
+        "in some_strict_check\n"
+        "in non-strict part of some_partially_strict_check\n"
+        "in strict part of some_partially_strict_check\n"
+    )
+    assert capsys.readouterr().out == expected_output
+
+
+# class LR1(LogisticRegression):
+#     def _more_tags(self):
+#         return {
+#             '_xfail_checks': {
+#                 some_strict_check: 'whatever reason',
+#                 some_partially_strict_check: 'whatever reason',
+#             }
+#         }
+
+
+# class LR2(LogisticRegression):
+#     def _more_tags(self):
+#         return {
+#             '_xfail_checks': {
+#                 functools.partial(some_strict_check): 'whatever reason',
+#                 functools.partial(some_partially_strict_check): 'whatever reason',  # noqa
+#             }
+#         }
+
+
+# @pytest.mark.parametrize('est, expected_output', (
+#     (LR1(), ""),
+#     # (LR2(), ""),
+#     )
+# )
+# def test_xfail_tag_is_partial_func(est, expected_output, capsys):
+
+#     check_estimator(est, strict_mode=True)
+    # assert capsys.readouterr().out == expected_output