better performance for reset parameters

src/boosting/gbdt.cpp

@@ -100,8 +100,8 @@ void GBDT::ResetTrainingData(const BoostingConfig* config, const Dataset* train_
     num_data_ = train_data->num_data();
     // create buffer for gradients and hessians
     if (object_function_ != nullptr) {
-      gradients_ = std::vector<score_t>(num_data_ * num_class_);
-      hessians_ = std::vector<score_t>(num_data_ * num_class_);
+      gradients_.resize(num_data_ * num_class_);
+      hessians_.resize(num_data_ * num_class_);
     }
     // get max feature index
     max_feature_idx_ = train_data->num_total_features() - 1;
@@ -114,8 +114,8 @@ void GBDT::ResetTrainingData(const BoostingConfig* config, const Dataset* train_
       || (gbdt_config_->bagging_fraction != new_config->bagging_fraction)) {
     // if need bagging, create buffer
     if (new_config->bagging_fraction < 1.0 && new_config->bagging_freq > 0) {
-      out_of_bag_data_indices_ = std::vector<data_size_t>(num_data_);
-      bag_data_indices_ = std::vector<data_size_t>(num_data_);
+      out_of_bag_data_indices_.resize(num_data_);
+      bag_data_indices_.resize(num_data_);
     } else {
       out_of_bag_data_cnt_ = 0;
       out_of_bag_data_indices_.clear();

src/treelearner/data_partition.hpp

@@ -16,8 +16,8 @@ namespace LightGBM {
 */
 class DataPartition {
 public:
-  DataPartition(data_size_t num_data, int num_leafs)
-    :num_data_(num_data), num_leaves_(num_leafs) {
+  DataPartition(data_size_t num_data, int num_leaves)
+    :num_data_(num_data), num_leaves_(num_leaves) {
     leaf_begin_.resize(num_leaves_);
     leaf_count_.resize(num_leaves_);
     indices_.resize(num_data_);
@@ -35,6 +35,13 @@ public:
     left_write_pos_buf_.resize(num_threads_);
     right_write_pos_buf_.resize(num_threads_);
   }
+
+  void ResetLeaves(int num_leaves) {
+    num_leaves_ = num_leaves;
+    leaf_begin_.resize(num_leaves_);
+    leaf_count_.resize(num_leaves_);
+  }
+
   ~DataPartition() {
 
   }

src/treelearner/feature_histogram.hpp

@@ -364,9 +364,9 @@ public:
     }
     is_enough_ = (cache_size_ == total_size_);
     if (!is_enough_) {
-      mapper_ = std::vector<int>(total_size_);
-      inverse_mapper_ = std::vector<int>(cache_size_);
-      last_used_time_ = std::vector<int>(cache_size_);
+      mapper_.resize(total_size_);
+      inverse_mapper_.resize(cache_size_);
+      last_used_time_.resize(cache_size_);
       ResetMap();
     }
   }

src/treelearner/serial_tree_learner.cpp

@@ -105,7 +105,7 @@ void SerialTreeLearner::ResetConfig(const TreeConfig* tree_config) {
 
     // push split information for all leaves
     best_split_per_leaf_.resize(tree_config_->num_leaves);
-    data_partition_.reset(new DataPartition(num_data_, tree_config_->num_leaves));
+    data_partition_->ResetLeaves(tree_config_->num_leaves);
   } else {
     tree_config_ = tree_config;
   }