[MRG] add _pairwise property to BaseSearchCV

sklearn/model_selection/_search.py

@@ -398,6 +398,11 @@ def __init__(self, estimator, scoring=None, n_jobs=None, iid='deprecated',
     def _estimator_type(self):
         return self.estimator._estimator_type
 
+    @property
+    def _pairwise(self):
+        # allows cross-validation to see 'precomputed' metrics
+        return getattr(self.estimator, '_pairwise', False)
+
     def score(self, X, y=None):
         """Returns the score on the given data, if the estimator has been refit.
 

sklearn/model_selection/tests/test_search.py

@@ -1787,3 +1787,30 @@ def get_n_splits(self, *args, **kw):
                              'inconsistent results. Expected \\d+ '
                              'splits, got \\d+'):
         ridge.fit(X[:train_size], y[:train_size])
+
+
+def test_search_cv__pairwise_property():
+    """
+    Test implementation of BaseSearchCV has the _pairwise property
+    which matches the _pairwise property of its estimator.
+    """
+
+    class PairwiseCV(BaseSearchCV):
+        def __init__(self, estimator, **kwargs):
+            super().__init__(estimator, **kwargs)
+
+    # simple estimator with _pairwise property
+    est = BaseEstimator()
+
+    attr_message = "BaseSearchCV _pairwise property must match estimator"
+
+    # check estimator with and without _pairwise
+    for _pairwise_setting in [True, False]:
+        setattr(est, '_pairwise', _pairwise_setting)
+        cv = PairwiseCV(est)
+
+        # check if cv is pairwise
+        cv_is_pairwise = getattr(cv, '_pairwise', False)
+
+        # verity the _pairwise property in cv matches est
+        assert _pairwise_setting == cv_is_pairwise, attr_message