only stop training when all classes are finshed in multi-class.

src/boosting/gbdt.cpp

@@ -162,7 +162,6 @@ void GBDT::ResetTrainingData(const BoostingConfig* config, const Dataset* train_
   if (train_data_ != nullptr) {
     // reset config for tree learner
     tree_learner_->ResetConfig(&new_config->tree_config);
-    is_class_end_ = std::vector<bool>(num_class_, false);
   }
   gbdt_config_.reset(new_config.release());
 }
@@ -284,7 +283,7 @@ void GBDT::UpdateScoreOutOfBag(const Tree* tree, const int curr_class) {
 #ifdef TIMETAG
   auto start_time = std::chrono::steady_clock::now();
 #endif
-  // we need to predict out-of-bag socres of data for boosting
+  // we need to predict out-of-bag scores of data for boosting
   if (num_data_ - bag_data_cnt_ > 0 && !is_use_subset_) {
     train_score_updater_->AddScore(tree, bag_data_indices_.data() + bag_data_cnt_, num_data_ - bag_data_cnt_, curr_class);
   }
@@ -351,7 +350,7 @@ bool GBDT::TrainOneIter(const score_t* gradient, const score_t* hessian, bool is
     // get sub gradients
     for (int curr_class = 0; curr_class < num_class_; ++curr_class) {
       auto bias = curr_class * num_data_;
-      // cannot multi-threding
+      // cannot multi-threading
       for (int i = 0; i < bag_data_cnt_; ++i) {
         gradients_[bias + i] = gradient[bias + bag_data_indices_[i]];
         hessians_[bias + i] = hessian[bias + bag_data_indices_[i]];
@@ -369,10 +368,8 @@ bool GBDT::TrainOneIter(const score_t* gradient, const score_t* hessian, bool is
     start_time = std::chrono::steady_clock::now();
   #endif
     std::unique_ptr<Tree> new_tree(new Tree(2));
-    if (!is_class_end_[curr_class]) {
-      // train a new tree
-      new_tree.reset(tree_learner_->Train(gradient + curr_class * num_data_, hessian + curr_class * num_data_));
-    }
+    // train a new tree
+    new_tree.reset(tree_learner_->Train(gradient + curr_class * num_data_, hessian + curr_class * num_data_));
   #ifdef TIMETAG
     tree_time += std::chrono::steady_clock::now() - start_time;
   #endif
@@ -384,10 +381,7 @@ bool GBDT::TrainOneIter(const score_t* gradient, const score_t* hessian, bool is
       // update score
       UpdateScore(new_tree.get(), curr_class);
       UpdateScoreOutOfBag(new_tree.get(), curr_class);
-    } else {
-      is_class_end_[curr_class] = true;
     }
-
     // add model
     models_.push_back(std::move(new_tree));
   }
@@ -423,7 +417,6 @@ void GBDT::RollbackOneIter() {
   for (int curr_class = 0; curr_class < num_class_; ++curr_class) {
     models_.pop_back();
   }
-  is_class_end_ = std::vector<bool>(num_class_, false);
   --iter_;
 }
 

src/boosting/gbdt.h

@@ -344,7 +344,6 @@ protected:
   std::vector<data_size_t> right_write_pos_buf_;
   std::unique_ptr<Dataset> tmp_subset_;
   bool is_use_subset_;
-  std::vector<bool> is_class_end_;
   bool boost_from_average_;
 };