[breaking] Drop single precision histogram (#7892)

Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>

src/tree/hist/evaluate_splits.h

@@ -22,7 +22,8 @@
 namespace xgboost {
 namespace tree {
 
-template <typename GradientSumT, typename ExpandEntry> class HistEvaluator {
+template <typename ExpandEntry>
+class HistEvaluator {
  private:
   struct NodeEntry {
     /*! \brief statics for node entry */
@@ -57,7 +58,7 @@ template <typename GradientSumT, typename ExpandEntry> class HistEvaluator {
   // a non-missing value for the particular feature fid.
   template <int d_step, SplitType split_type>
   GradStats EnumerateSplit(common::HistogramCuts const &cut, common::Span<size_t const> sorted_idx,
-                           const common::GHistRow<GradientSumT> &hist, bst_feature_t fidx,
+                           const common::GHistRow &hist, bst_feature_t fidx,
                            bst_node_t nidx,
                            TreeEvaluator::SplitEvaluator<TrainParam> const &evaluator,
                            SplitEntry *p_best) const {
@@ -197,10 +198,8 @@ template <typename GradientSumT, typename ExpandEntry> class HistEvaluator {
   }
 
  public:
-  void EvaluateSplits(const common::HistCollection<GradientSumT> &hist,
-                      common::HistogramCuts const &cut,
-                      common::Span<FeatureType const> feature_types,
-                      const RegTree &tree,
+  void EvaluateSplits(const common::HistCollection &hist, common::HistogramCuts const &cut,
+                      common::Span<FeatureType const> feature_types, const RegTree &tree,
                       std::vector<ExpandEntry> *p_entries) {
     auto& entries = *p_entries;
     // All nodes are on the same level, so we can store the shared ptr.
@@ -377,10 +376,10 @@ template <typename GradientSumT, typename ExpandEntry> class HistEvaluator {
  *
  * \param p_last_tree The last tree being updated by tree updater
  */
-template <typename Partitioner, typename GradientSumT, typename ExpandEntry>
+template <typename Partitioner, typename ExpandEntry>
 void UpdatePredictionCacheImpl(GenericParameter const *ctx, RegTree const *p_last_tree,
                                std::vector<Partitioner> const &partitioner,
-                               HistEvaluator<GradientSumT, ExpandEntry> const &hist_evaluator,
+                               HistEvaluator<ExpandEntry> const &hist_evaluator,
                                TrainParam const &param, linalg::VectorView<float> out_preds) {
   CHECK_GT(out_preds.Size(), 0U);
 

src/tree/hist/histogram.h

@@ -16,17 +16,15 @@
 
 namespace xgboost {
 namespace tree {
-template <typename GradientSumT, typename ExpandEntry> class HistogramBuilder {
-  using GradientPairT = xgboost::detail::GradientPairInternal<GradientSumT>;
-  using GHistRowT = common::GHistRow<GradientSumT>;
-
+template <typename ExpandEntry>
+class HistogramBuilder {
   /*! \brief culmulative histogram of gradients. */
-  common::HistCollection<GradientSumT> hist_;
+  common::HistCollection hist_;
   /*! \brief culmulative local parent histogram of gradients. */
-  common::HistCollection<GradientSumT> hist_local_worker_;
-  common::GHistBuilder<GradientSumT> builder_;
-  common::ParallelGHistBuilder<GradientSumT> buffer_;
-  rabit::Reducer<GradientPairT, GradientPairT::Reduce> reducer_;
+  common::HistCollection hist_local_worker_;
+  common::GHistBuilder builder_;
+  common::ParallelGHistBuilder buffer_;
+  rabit::Reducer<GradientPairPrecise, GradientPairPrecise::Reduce> reducer_;
   BatchParam param_;
   int32_t n_threads_{-1};
   size_t n_batches_{0};
@@ -51,8 +49,10 @@ template <typename GradientSumT, typename ExpandEntry> class HistogramBuilder {
     hist_.Init(total_bins);
     hist_local_worker_.Init(total_bins);
     buffer_.Init(total_bins);
-    builder_ = common::GHistBuilder<GradientSumT>(total_bins);
+    builder_ = common::GHistBuilder(total_bins);
     is_distributed_ = is_distributed;
+    // Workaround s390x gcc 7.5.0
+    auto DMLC_ATTRIBUTE_UNUSED __force_instantiation = &GradientPairPrecise::Reduce;
   }
 
   template <bool any_missing>
@@ -64,7 +64,7 @@ template <typename GradientSumT, typename ExpandEntry> class HistogramBuilder {
     const size_t n_nodes = nodes_for_explicit_hist_build.size();
     CHECK_GT(n_nodes, 0);
 
-    std::vector<GHistRowT> target_hists(n_nodes);
+    std::vector<common::GHistRow> target_hists(n_nodes);
     for (size_t i = 0; i < n_nodes; ++i) {
       const int32_t nid = nodes_for_explicit_hist_build[i].nid;
       target_hists[i] = hist_[nid];
@@ -243,9 +243,7 @@ template <typename GradientSumT, typename ExpandEntry> class HistogramBuilder {
 
  public:
   /* Getters for tests. */
-  common::HistCollection<GradientSumT> const& Histogram() {
-    return hist_;
-  }
+  common::HistCollection const &Histogram() { return hist_; }
   auto& Buffer() { return buffer_; }
 
  private:

src/tree/hist/param.cc

@@ -1,10 +0,0 @@
-/*!
- * Copyright 2022 XGBoost contributors
- */
-#include "param.h"
-
-namespace xgboost {
-namespace tree {
-DMLC_REGISTER_PARAMETER(CPUHistMakerTrainParam);
-}  // namespace tree
-}  // namespace xgboost

src/tree/hist/param.h

@@ -1,23 +0,0 @@
-/*!
- * Copyright 2021 XGBoost contributors
- */
-#ifndef XGBOOST_TREE_HIST_PARAM_H_
-#define XGBOOST_TREE_HIST_PARAM_H_
-#include "xgboost/parameter.h"
-
-namespace xgboost {
-namespace tree {
-// training parameters specific to this algorithm
-struct CPUHistMakerTrainParam
-    : public XGBoostParameter<CPUHistMakerTrainParam> {
-  bool single_precision_histogram;
-  // declare parameters
-  DMLC_DECLARE_PARAMETER(CPUHistMakerTrainParam) {
-    DMLC_DECLARE_FIELD(single_precision_histogram).set_default(false).describe(
-        "Use single precision to build histograms.");
-  }
-};
-}  // namespace tree
-}  // namespace xgboost
-
-#endif  // XGBOOST_TREE_HIST_PARAM_H_