FIX make pipeline memory compatible with older joblib version (#687)

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

Author: chkoar

doc/whats_new/v0.7.rst

@@ -1,11 +1,18 @@
 .. _changes_0_7:
 
-Version 0.7.0 (under development)
-=================================
+Version 0.7.0
+=============
 
 Changelog
 ---------
 
+Maintenance
+...........
+
+- Ensure that :class:`imblearn.pipeline.Pipeline` is working when `memory`
+  is activated and `joblib==0.11`.
+  :pr:`687` by :user:`Christos Aridas <chkoar>`.
+
 Changed models
 ..............
 

imblearn/pipeline.py

@@ -213,22 +213,15 @@ def _fit(self, X, y=None, **fit_params):
                 with _print_elapsed_time('Pipeline',
                                          self._log_message(step_idx)):
                     continue
-            if hasattr(memory, "location"):
+
+            try:
                 # joblib >= 0.12
-                if memory.location is None:
-                    # we do not clone when caching is disabled to
-                    # preserve backward compatibility
-                    cloned_transformer = transformer
-                else:
-                    cloned_transformer = clone(transformer)
-            elif hasattr(memory, "cachedir"):
-                # joblib <= 0.11
-                if memory.cachedir is None:
-                    # we do not clone when caching is disabled to
-                    # preserve backward compatibility
-                    cloned_transformer = transformer
-            else:
-                cloned_transformer = clone(transformer)
+                mem = memory.location
+            except AttributeError:
+                mem = memory.cachedir
+            finally:
+                cloned_transformer = clone(transformer) if mem else transformer
+
             # Fit or load from cache the current transfomer
             if hasattr(cloned_transformer, "transform") or hasattr(
                 cloned_transformer, "fit_transform"

imblearn/tests/test_pipeline.py

@@ -1342,3 +1342,22 @@ def test_pipeline_score_samples_pca_lof():
     # Check the values
     lof.fit(pca.fit_transform(X))
     assert_allclose(pipe.score_samples(X), lof.score_samples(pca.transform(X)))
+
+
+def test_pipeline_old_joblib_memory(monkeypatch):
+    """Test that Pipeline works with old versions of joblib"""
+
+    monkeypatch.setattr(Memory, "cachedir", "foo", raising=False)
+    monkeypatch.setattr(Memory, "cache", lambda self, x: x, raising=False)
+    memory = Memory()
+
+    del memory.location  # Older versions do not have the location parameter
+
+    iris = load_iris()
+    X = iris.data
+    y = iris.target
+
+    cached_pipe = Pipeline(
+        [("transf", DummyTransf()), ("svc", SVC(gamma="scale"))], memory=memory
+    )
+    cached_pipe.fit(X, y)