Fix filtering callable objects in skl xgb param.

python-package/xgboost/sklearn.py

@@ -398,7 +398,7 @@ def get_xgb_params(self):
             'importance_type', 'kwargs', 'missing', 'n_estimators', 'use_label_encoder'}
         filtered = dict()
         for k, v in params.items():
-            if k not in wrapper_specific:
+            if k not in wrapper_specific and not callable(v):
                 filtered[k] = v
         return filtered
 

tests/python/test_with_sklearn.py

@@ -399,6 +399,21 @@ def dummy_objective(y_true, y_preds):
         X, y
     )
 
+    cls = xgb.XGBClassifier(use_label_encoder=False, n_estimators=1)
+    cls.fit(X, y)
+
+    is_called = [False]
+
+    def wrapped(y, p):
+        is_called[0] = True
+        return logregobj(y, p)
+
+    cls.set_params(objective=wrapped)
+    cls.predict(X)              # no throw
+    cls.fit(X, y)
+
+    assert is_called[0]
+
 
 def test_sklearn_api():
     from sklearn.datasets import load_iris