@@ -77,7 +77,7 @@ class BalancingLearner(BaseLearner):

         # pickle the whole learner.

         self.function = partial(dispatch, [l.function for l in self.learners])

-        self._points = {}

+        self._ask_cache = {}

         self._loss = {}

         self._pending_loss = {}

         self._cdims_default = cdims

@@ -122,10 +122,10 @@ class BalancingLearner(BaseLearner):

             points_per_learner = []

             for index, learner in enumerate(self.learners):

                 # Take the points from the cache

-                if index not in self._points:

-                    self._points[index] = learner.ask(

+                if index not in self._ask_cache:

+                    self._ask_cache[index] = learner.ask(

                         n=1, tell_pending=False)

-                points, loss_improvements = self._points[index]

+                points, loss_improvements = self._ask_cache[index]

                 priority = (loss_improvements[0], -npoints[index])

                 improvements_per_learner.append(priority)

@@ -154,9 +154,9 @@ class BalancingLearner(BaseLearner):

             npoints[index] += 1

             # Take the points from the cache

-            if index not in self._points:

-                self._points[index] = self.learners[index].ask(n=1)

-            points, loss_improvements = self._points[index]

+            if index not in self._ask_cache:

+                self._ask_cache[index] = self.learners[index].ask(n=1)

+            points, loss_improvements = self._ask_cache[index]

             chosen_points.append((index, points[0]))

             chosen_loss_improvements.append(loss_improvements[0])

@@ -171,9 +171,9 @@ class BalancingLearner(BaseLearner):

         while n_left > 0:

             index = np.argmin(npoints)

             # Take the points from the cache

-            if index not in self._points:

-                self._points[index] = self.learners[index].ask(n=1)

-            points, loss_improvements = self._points[index]

+            if index not in self._ask_cache:

+                self._ask_cache[index] = self.learners[index].ask(n=1)

+            points, loss_improvements = self._ask_cache[index]

             npoints[index] += 1

             n_left -= 1

             chosen_points.append((index, points[0]))

@@ -190,14 +190,14 @@ class BalancingLearner(BaseLearner):

     def tell(self, x, y):

         index, x = x

-        self._points.pop(index, None)

+        self._ask_cache.pop(index, None)

         self._loss.pop(index, None)

         self._pending_loss.pop(index, None)

         self.learners[index].tell(x, y)

     def tell_pending(self, x):

         index, x = x

-        self._points.pop(index, None)

+        self._ask_cache.pop(index, None)

         self._loss.pop(index, None)

         self.learners[index].tell_pending(x)