325fae8fbbc16b3c1ca40559bb2a9c783efaf440,libact/query_strategies/active_learning_by_learning.py,ActiveLearningByLearning,make_query,#ActiveLearningByLearning#,161

Before Change

    def make_query(self):
        Except for the initial query, it returns the id of the data albl
        wants to query.
        if self.queried_hist_ == []:
            // initial query
            q = self.exp4p_.next(-1, None, None)
            ask_idx = np.random.choice(
                        np.arange(len(self.unlabeled_invert_id_idx)), size=1, p=q
                    )[0]
            ask_id = self.unlabeled_entry_ids[ask_idx]
            self.W.append(1./q[ask_idx])
            self.queried_hist_.append(ask_id)
        return self.queried_hist_[-1]


class Exp4P():

After Change

                    )[0]
            ask_id = self.unlabeled_entry_ids[ask_idx]

            if ask_id in unlabeled_entry_ids:
                self.budget_used += 1
                return ask_id
            else:
                self.update(ask_id, dataset.data[ask_id][1])


        raise ValueError("Out of query budget")


class Exp4P():

Instances