fix-parallel-quantile (#1605)

* fix-parallel-quantile

* Update serial_tree_learner.cpp

src/treelearner/serial_tree_learner.cpp

@@ -774,6 +774,7 @@ void SerialTreeLearner::Split(Tree* tree, int best_leaf, int* left_leaf, int* ri
   }
 }
 
+
 void SerialTreeLearner::RenewTreeOutput(Tree* tree, const ObjectiveFunction* obj, const double* prediction,
                                         data_size_t total_num_data, const data_size_t* bag_indices, data_size_t bag_cnt) const {
   if (obj != nullptr && obj->IsRenewTreeOutput()) {
@@ -783,15 +784,21 @@ void SerialTreeLearner::RenewTreeOutput(Tree* tree, const ObjectiveFunction* obj
       CHECK(bag_cnt == num_data_);
       bag_mapper = bag_indices;
     }
+    std::vector<int> n_nozeroworker_perleaf(tree->num_leaves(), 1);
     #pragma omp parallel for schedule(static)
     for (int i = 0; i < tree->num_leaves(); ++i) {
       const double output = static_cast<double>(tree->LeafOutput(i));
       data_size_t cnt_leaf_data = 0;
       auto index_mapper = data_partition_->GetIndexOnLeaf(i, &cnt_leaf_data);
-      CHECK(cnt_leaf_data > 0);
+      if (cnt_leaf_data > 0) {
         // bag_mapper[index_mapper[i]]
         const double new_output = obj->RenewTreeOutput(output, prediction, index_mapper, bag_mapper, cnt_leaf_data);
         tree->SetLeafOutput(i, new_output);
+      } else {
+        CHECK(Network::num_machines() > 1);
+        tree->SetLeafOutput(i, 0.0);
+        n_nozeroworker_perleaf[i] = 0;
+      }
     }
     if (Network::num_machines() > 1) {
       std::vector<double> outputs(tree->num_leaves());
@@ -799,8 +806,9 @@ void SerialTreeLearner::RenewTreeOutput(Tree* tree, const ObjectiveFunction* obj
         outputs[i] = static_cast<double>(tree->LeafOutput(i));
       }
       Network::GlobalSum(outputs);
+      Network::GlobalSum(n_nozeroworker_perleaf);
       for (int i = 0; i < tree->num_leaves(); ++i) {
-        tree->SetLeafOutput(i, outputs[i] / Network::num_machines());
+        tree->SetLeafOutput(i, outputs[i] / n_nozeroworker_perleaf[i]);
       }
     } 
   }