merge latest changes

src/tree/gpu_hist/histogram.cu

@@ -318,7 +318,6 @@ void BuildGradientHistogram(CUDAContext const* ctx, EllpackDeviceAccessor const&
     grid_size = std::min(common::DivRoundUp(grid_size, num_groups), static_cast<std::uint32_t>(
                                         common::DivRoundUp(items_per_group, kMinItemsPerBlock)));
 #endif
-
     dh::LaunchKernel {dim3(grid_size, num_groups), static_cast<uint32_t>(kBlockThreads), smem_size,
                      ctx->Stream()} (kernel, matrix, feature_groups, d_ridx, histogram.data(),
                                      gpair.data(), rounding);

src/tree/hist/evaluate_splits.h

@@ -730,6 +730,9 @@ class HistMultiEvaluator {
 
     std::size_t n_nodes = p_tree->Size();
     gain_.resize(n_nodes);
+    // Re-calculate weight without learning rate.
+    CalcWeight(*param_, left_sum, left_weight);
+    CalcWeight(*param_, right_sum, right_weight);
     gain_[left_child] = CalcGainGivenWeight(*param_, left_sum, left_weight);
     gain_[right_child] = CalcGainGivenWeight(*param_, right_sum, right_weight);
 

src/tree/multi_target_tree_model.cc

@@ -195,8 +195,9 @@ void MultiTargetTree::Expand(bst_node_t nidx, bst_feature_t split_idx, float spl
   split_index_.resize(n);
   split_index_[nidx] = split_idx;
 
-  split_conds_.resize(n);
+  split_conds_.resize(n, std::numeric_limits<float>::quiet_NaN());
   split_conds_[nidx] = split_cond;
+
   default_left_.resize(n);
   default_left_[nidx] = static_cast<std::uint8_t>(default_left);
 

src/tree/updater_quantile_hist.cc

@@ -149,6 +149,9 @@ class MultiTargetHistBuilder {
   }
 
   void InitData(DMatrix *p_fmat, RegTree const *p_tree) {
+    if (collective::IsDistributed()) {
+      LOG(FATAL) << "Distributed training for vector-leaf is not yet supported.";
+    }
     monitor_->Start(__func__);
 
     p_last_fmat_ = p_fmat;