Uniq top kps.

app.py

@@ -216,8 +216,8 @@ def second_stage_ranked_docs(selected_query_kps, first_stage_pids, pid2abstract,
     for i, pid in enumerate(first_stage_pids):
         sent_reps = pid2sent_reps_cand[pid]
         pair_dists = distance.cdist(query_kp_values, sent_reps)
-        kp_ind, sent_ind = np.unravel_index(np.argsort(pair_dists, axis=None), pair_dists.shape)
-        kp_ind = list(set(kp_ind[:topk].tolist()))
+        # Pick the topk unique profile concepts.
+        kp_ind = np.argsort(pair_dists.min(axis=1))[:topk]
         sub_pair_dists = pair_dists[kp_ind, :]
         # sub_kp_reps = query_kp_values[kp_ind, :]
         a_distr = special.softmax(-1*np.min(sub_pair_dists, axis=1))