1 files changed, 18 insertions, 18 deletions
diff --git a/vowpalwabbit/topk.cc b/vowpalwabbit/topk.cc
index 445bdb23..52f03ad9 100644
--- a/vowpalwabbit/topk.cc
+++ b/vowpalwabbit/topk.cc
@@ -16,15 +16,12 @@ namespace TOPK {
   struct compare_scored_examples
   {
     bool operator()(scored_example const& a, scored_example const& b) const
-    {
-      return a.first > b.first;
-    }
+    { return a.first > b.first; }
   };
   
   struct topk{
     uint32_t B; //rec number
     priority_queue<scored_example, vector<scored_example>, compare_scored_examples > pr_queue;
-    vw* all;
   };
 
   void print_result(int f, priority_queue<scored_example, vector<scored_example>, compare_scored_examples > &pr_queue)
@@ -72,43 +69,46 @@ namespace TOPK {
     if (example_is_newline(ec))
       for (int* sink = all.final_prediction_sink.begin; sink != all.final_prediction_sink.end; sink++)
         TOPK::print_result(*sink, d.pr_queue);
-       
+    
     print_update(all, ec);
   }
-
+  
   template <bool is_learn>
   void predict_or_learn(topk& d, LEARNER::base_learner& base, example& ec)
   {
     if (example_is_newline(ec)) return;//do not predict newline
-
+    
     if (is_learn)
       base.learn(ec);
     else
       base.predict(ec);
-
+    
     if(d.pr_queue.size() < d.B)      
       d.pr_queue.push(make_pair(ec.pred.scalar, ec.tag));
-
+    
     else if(d.pr_queue.top().first < ec.pred.scalar)
-    {
-      d.pr_queue.pop();
-      d.pr_queue.push(make_pair(ec.pred.scalar, ec.tag));
-    }
+      {
+	d.pr_queue.pop();
+	d.pr_queue.push(make_pair(ec.pred.scalar, ec.tag));
+      }
   }
-
+  
   void finish_example(vw& all, topk& d, example& ec)
   {
     TOPK::output_example(all, d, ec);
     VW::finish_example(all, &ec);
   }
 
-  LEARNER::base_learner* setup(vw& all, po::variables_map& vm)
+  LEARNER::base_learner* setup(vw& all)
   {
+    new_options(all, "TOP K options")
+      ("top", po::value<size_t>(), "top k recommendation");
+    if(missing_required(all)) return NULL;
+
     topk& data = calloc_or_die<topk>();
-    data.B = (uint32_t)vm["top"].as<size_t>();
-    data.all = &all;
+    data.B = (uint32_t)all.vm["top"].as<size_t>();
 
-    LEARNER::learner<topk>& l = init_learner(&data, all.l, predict_or_learn<true>, 
+    LEARNER::learner<topk>& l = init_learner(&data, setup_base(all), predict_or_learn<true>, 
 					     predict_or_learn<false>);
     l.set_finish_example(finish_example);