diff --git a/vowpalwabbit/gen_cs_example.cc b/vowpalwabbit/gen_cs_example.cc
index 8fe85b46696..97eb548269c 100644
--- a/vowpalwabbit/gen_cs_example.cc
+++ b/vowpalwabbit/gen_cs_example.cc
@@ -115,26 +115,27 @@ void gen_cs_example_ips(cb_to_cs& c, CB::label& ld, COST_SENSITIVE::label& cs_ld
   //this implements the inverse propensity score method, where cost are importance weighted by the probability of the chosen action
   //generate cost-sensitive example
   cs_ld.costs.clear();
-  if (ld.costs.size() == 1 || ld.costs.size() == 0)   //this is a typical example where we can perform all actions
-  {
-    //in this case generate cost-sensitive example with all actions
-    for (uint32_t i = 1; i <= c.num_actions; i++)
+  if (ld.costs.size() == 0 || (ld.costs.size() == 1 && ld.costs[0].cost != FLT_MAX))
+    //this is a typical example where we can perform all actions
     {
-      COST_SENSITIVE::wclass wc = {0.,i,0.,0.};
-      if (c.known_cost != nullptr && i == c.known_cost->action)
-      {
-        wc.x = c.known_cost->cost / safe_probability(c.known_cost->probability); //use importance weighted cost for observed action, 0 otherwise
-        //ips can be thought as the doubly robust method with a fixed regressor that predicts 0 costs for everything
-        //update the loss of this regressor
-        c.nb_ex_regressors++;
-        c.avg_loss_regressors += (1.0f / c.nb_ex_regressors)*((c.known_cost->cost)*(c.known_cost->cost) - c.avg_loss_regressors);
-        c.last_pred_reg = 0;
-        c.last_correct_cost = c.known_cost->cost;
-      }
-
-      cs_ld.costs.push_back(wc);
+      //in this case generate cost-sensitive example with all actions
+      for (uint32_t i = 1; i <= c.num_actions; i++)
+        {
+          COST_SENSITIVE::wclass wc = {0.,i,0.,0.};
+          if (c.known_cost != nullptr && i == c.known_cost->action)
+            {
+              wc.x = c.known_cost->cost / safe_probability(c.known_cost->probability); //use importance weighted cost for observed action, 0 otherwise
+              //ips can be thought as the doubly robust method with a fixed regressor that predicts 0 costs for everything
+              //update the loss of this regressor
+              c.nb_ex_regressors++;
+              c.avg_loss_regressors += (1.0f / c.nb_ex_regressors)*((c.known_cost->cost)*(c.known_cost->cost) - c.avg_loss_regressors);
+              c.last_pred_reg = 0;
+              c.last_correct_cost = c.known_cost->cost;
+            }
+
+          cs_ld.costs.push_back(wc);
+        }
     }
-  }
   else   //this is an example where we can only perform a subset of the actions
   {
     //in this case generate cost-sensitive example with only allowed actions
diff --git a/vowpalwabbit/gen_cs_example.h b/vowpalwabbit/gen_cs_example.h
index d9e9865ecdc..f60bf9821cf 100644
--- a/vowpalwabbit/gen_cs_example.h
+++ b/vowpalwabbit/gen_cs_example.h
@@ -57,7 +57,7 @@ void gen_cs_example_dm(cb_to_cs& c, example& ec, COST_SENSITIVE::label& cs_ld)
   cs_ld.costs.clear();
   c.pred_scores.costs.clear();
 
-  if (ld.costs.size() == 1 || ld.costs.size() == 0)   //this is a typical example where we can perform all actions
+  if (ld.costs.size() == 0 || (ld.costs.size() == 1 && ld.costs[0].cost != FLT_MAX) )   //this is a typical example where we can perform all actions
   { //in this case generate cost-sensitive example with all actions
     for (uint32_t i = 1; i <= c.num_actions; i++)
     { COST_SENSITIVE::wclass wc = {0., i, 0., 0.};
@@ -139,7 +139,8 @@ void gen_cs_example_dr(cb_to_cs& c, example& ec, CB::label& ld, COST_SENSITIVE::
       COST_SENSITIVE::wclass temp = { FLT_MAX, i, 0., 0. };
       cs_ld.costs.push_back(temp);
     }
-  else if (ld.costs.size() == 1 || ld.costs.size() == 0) //this is a typical example where we can perform all actions
+  else if (ld.costs.size() == 0 || (ld.costs.size() == 1 && ld.costs[0].cost != FLT_MAX) )
+    //this is a typical example where we can perform all actions
     //in this case generate cost-sensitive example with all actions
     for (uint32_t i = 1; i <= c.num_actions; i++)
       gen_cs_label<is_learn>(c, ec, cs_ld, i);
diff --git a/vowpalwabbit/parser.cc b/vowpalwabbit/parser.cc
index 1b2a9b06834..eb01605f920 100644
--- a/vowpalwabbit/parser.cc
+++ b/vowpalwabbit/parser.cc
@@ -190,7 +190,7 @@ uint32_t cache_numbits(io_buf* buf, int filepointer)
     version_struct v_tmp(t.begin());
     if ( v_tmp != version )
     {
-      cout << "cache has possibly incompatible version, rebuilding" << endl;
+      //      cout << "cache has possibly incompatible version, rebuilding" << endl;
       t.delete_v();
       return 0;
     }