fix subset bug (#2748)

* fix subset bug

* typo

* add fixme tag

* bin mapper

* fix test
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

include/LightGBM/feature_group.h

@@ -46,19 +46,21 @@ class FeatureGroup {
       num_total_bin_ += num_bin;
       bin_offsets_.emplace_back(num_total_bin_);
     }
-    if (is_multi_val_) {
-      multi_bin_data_.clear();
-      for (int i = 0; i < num_feature_; ++i) {
-        int addi = bin_mappers_[i]->GetMostFreqBin() == 0 ? 0 : 1;
-        if (bin_mappers_[i]->sparse_rate() >= kSparseThreshold) {
-          multi_bin_data_.emplace_back(Bin::CreateSparseBin(num_data, bin_mappers_[i]->num_bin() + addi));
-        } else {
-          multi_bin_data_.emplace_back(Bin::CreateDenseBin(num_data, bin_mappers_[i]->num_bin() + addi));
-        }
-      }
-    } else {
-      bin_data_.reset(Bin::CreateDenseBin(num_data, num_total_bin_));
+    CreateBinData(num_data, is_multi_val_, true, false);
+  }
+
+  FeatureGroup(const FeatureGroup& other, int num_data) {
+    num_feature_ = other.num_feature_;
+    is_multi_val_ = other.is_multi_val_;
+    is_sparse_ = other.is_sparse_;
+    num_total_bin_ = other.num_total_bin_;
+    bin_offsets_ = other.bin_offsets_;
+
+    bin_mappers_.reserve(other.bin_mappers_.size());
+    for (auto& bin_mapper : other.bin_mappers_) {
+      bin_mappers_.emplace_back(new BinMapper(*bin_mapper));
     }
+    CreateBinData(num_data, is_multi_val_, !is_sparse_, is_sparse_);
   }
 
   FeatureGroup(std::vector<std::unique_ptr<BinMapper>>* bin_mappers,
@@ -76,13 +78,7 @@ class FeatureGroup {
       num_total_bin_ += num_bin;
       bin_offsets_.emplace_back(num_total_bin_);
     }
-    if (bin_mappers_[0]->sparse_rate() >= kSparseThreshold) {
-      is_sparse_ = true;
-      bin_data_.reset(Bin::CreateSparseBin(num_data, num_total_bin_));
-    } else {
-      is_sparse_ = false;
-      bin_data_.reset(Bin::CreateDenseBin(num_data, num_total_bin_));
-    }
+    CreateBinData(num_data, false, false, false);
   }
 
   /*!
@@ -167,6 +163,16 @@ class FeatureGroup {
     }
   }
 
+  void ReSize(int num_data) {
+    if (!is_multi_val_) {
+      bin_data_->ReSize(num_data);
+    } else {
+      for (int i = 0; i < num_feature_; ++i) {
+        multi_bin_data_[i]->ReSize(num_data);
+      }
+    }
+  }
+
   inline void CopySubset(const FeatureGroup* full_feature, const data_size_t* used_indices, data_size_t num_used_indices) {
     if (!is_multi_val_) {
       bin_data_->CopySubset(full_feature->bin_data_.get(), used_indices, num_used_indices);
@@ -327,6 +333,34 @@ class FeatureGroup {
   }
 
  private:
+
+  void CreateBinData(int num_data, bool is_multi_val, bool force_dense, bool force_sparse) {
+    if (is_multi_val) {
+      multi_bin_data_.clear();
+      for (int i = 0; i < num_feature_; ++i) {
+        int addi = bin_mappers_[i]->GetMostFreqBin() == 0 ? 0 : 1;
+        if (bin_mappers_[i]->sparse_rate() >= kSparseThreshold) {
+          multi_bin_data_.emplace_back(Bin::CreateSparseBin(
+              num_data, bin_mappers_[i]->num_bin() + addi));
+        } else {
+          multi_bin_data_.emplace_back(
+              Bin::CreateDenseBin(num_data, bin_mappers_[i]->num_bin() + addi));
+        }
+      }
+      is_multi_val_ = true;
+    } else {
+      if (force_sparse || (!force_dense && num_feature_ == 1 &&
+                           bin_mappers_[0]->sparse_rate() >= kSparseThreshold)) {
+        is_sparse_ = true;
+        bin_data_.reset(Bin::CreateSparseBin(num_data, num_total_bin_));
+      } else {
+        is_sparse_ = false;
+        bin_data_.reset(Bin::CreateDenseBin(num_data, num_total_bin_));
+      }
+      is_multi_val_ = false;
+    }
+  }
+
   /*! \brief Number of features */
   int num_feature_;
   /*! \brief Bin mapper for sub features */

src/io/dataset.cpp

@@ -720,15 +720,7 @@ void Dataset::CopyFeatureMapperFrom(const Dataset* dataset) {
   num_groups_ = dataset->num_groups_;
   // copy feature bin mapper data
   for (int i = 0; i < num_groups_; ++i) {
-    std::vector<std::unique_ptr<BinMapper>> bin_mappers;
-    for (int j = 0; j < dataset->feature_groups_[i]->num_feature_; ++j) {
-      bin_mappers.emplace_back(new BinMapper(*(dataset->feature_groups_[i]->bin_mappers_[j])));
-    }
-    feature_groups_.emplace_back(new FeatureGroup(
-      dataset->feature_groups_[i]->num_feature_,
-      dataset->feature_groups_[i]->is_multi_val_,
-      &bin_mappers,
-      num_data_));
+    feature_groups_.emplace_back(new FeatureGroup(*dataset->feature_groups_[i], num_data_));
   }
   feature_groups_.shrink_to_fit();
   used_feature_map_ = dataset->used_feature_map_;
@@ -806,7 +798,7 @@ void Dataset::ReSize(data_size_t num_data) {
     #pragma omp parallel for schedule(static)
     for (int group = 0; group < num_groups_; ++group) {
       OMP_LOOP_EX_BEGIN();
-      feature_groups_[group]->bin_data_->ReSize(num_data_);
+      feature_groups_[group]->ReSize(num_data_);
       OMP_LOOP_EX_END();
     }
     OMP_THROW_EX();
@@ -1399,6 +1391,8 @@ void Dataset::AddFeaturesFrom(Dataset* other) {
   PushVector(&group_feature_cnt_, other->group_feature_cnt_);
   PushVector(&forced_bin_bounds_, other->forced_bin_bounds_);
   feature_groups_.reserve(other->feature_groups_.size());
+  // FIXME: fix the multiple multi-val feature groups, they need to be merged
+  // into one multi-val group
   for (auto& fg : other->feature_groups_) {
     feature_groups_.emplace_back(new FeatureGroup(*fg));
   }