Define bin type. (#7850)

include/xgboost/base.h

@@ -121,6 +121,8 @@ using bst_float = float;  // NOLINT
 using bst_cat_t = int32_t;  // NOLINT
 /*! \brief Type for data column (feature) index. */
 using bst_feature_t = uint32_t;  // NOLINT
+/*! \brief Type for histogram bin index. */
+using bst_bin_t = int32_t;  // NOLINT
 /*! \brief Type for data row index.
  *
  * Be careful `std::size_t' is implementation-defined.  Meaning that the binary

src/common/column_matrix.h

@@ -34,8 +34,8 @@ class Column {
  public:
   static constexpr int32_t kMissingId = -1;
 
-  Column(ColumnType type, common::Span<const BinIdxType> index, const uint32_t index_base)
-      : type_(type), index_(index), index_base_(index_base) {}
+  Column(ColumnType type, common::Span<const BinIdxType> index, const bst_bin_t index_base)
+      : type_(type), index_(index), index_base_{index_base} {}
 
   virtual ~Column() = default;
 
@@ -60,19 +60,19 @@ class Column {
   /* bin indexes in range [0, max_bins - 1] */
   common::Span<const BinIdxType> index_;
   /* bin index offset for specific feature */
-  const uint32_t index_base_;
+  bst_bin_t const index_base_;
 };
 
 template <typename BinIdxType>
 class SparseColumn : public Column<BinIdxType> {
  public:
-  SparseColumn(ColumnType type, common::Span<const BinIdxType> index, uint32_t index_base,
+  SparseColumn(ColumnType type, common::Span<const BinIdxType> index, bst_bin_t index_base,
                common::Span<const size_t> row_ind)
       : Column<BinIdxType>(type, index, index_base), row_ind_(row_ind) {}
 
   const size_t* GetRowData() const { return row_ind_.data(); }
 
-  int32_t GetBinIdx(size_t rid, size_t* state) const {
+  bst_bin_t GetBinIdx(size_t rid, size_t* state) const {
     const size_t column_size = this->Size();
     if (!((*state) < column_size)) {
       return this->kMissingId;

src/common/hist_util.h

@@ -40,8 +40,6 @@ class HistogramCuts {
   float max_cat_{-1.0f};
 
  protected:
-  using BinIdx = uint32_t;
-
   void Swap(HistogramCuts&& that) noexcept(true) {
     std::swap(cut_values_, that.cut_values_);
     std::swap(cut_ptrs_, that.cut_ptrs_);
@@ -110,31 +108,31 @@ class HistogramCuts {
 
   // Return the index of a cut point that is strictly greater than the input
   // value, or the last available index if none exists
-  BinIdx SearchBin(float value, bst_feature_t column_id, std::vector<uint32_t> const& ptrs,
-                   std::vector<float> const& values) const {
+  bst_bin_t SearchBin(float value, bst_feature_t column_id, std::vector<uint32_t> const& ptrs,
+                      std::vector<float> const& values) const {
     auto end = ptrs[column_id + 1];
     auto beg = ptrs[column_id];
     auto it = std::upper_bound(values.cbegin() + beg, values.cbegin() + end, value);
-    BinIdx idx = it - values.cbegin();
+    bst_bin_t idx = it - values.cbegin();
     idx -= !!(idx == end);
     return idx;
   }
 
-  BinIdx SearchBin(float value, bst_feature_t column_id) const {
+  bst_bin_t SearchBin(float value, bst_feature_t column_id) const {
     return this->SearchBin(value, column_id, Ptrs(), Values());
   }
 
   /**
    * \brief Search the bin index for numerical feature.
    */
-  BinIdx SearchBin(Entry const& e) const {
+  bst_bin_t SearchBin(Entry const& e) const {
     return SearchBin(e.fvalue, e.index);
   }
 
   /**
    * \brief Search the bin index for categorical feature.
    */
-  BinIdx SearchCatBin(Entry const &e) const {
+  bst_bin_t SearchCatBin(Entry const &e) const {
     auto const &ptrs = this->Ptrs();
     auto const &vals = this->Values();
     auto end = ptrs.at(e.index + 1) + vals.cbegin();
@@ -296,10 +294,10 @@ struct Index {
 };
 
 template <typename GradientIndex>
-int32_t XGBOOST_HOST_DEV_INLINE BinarySearchBin(size_t begin, size_t end,
-                                                GradientIndex const &data,
-                                                uint32_t const fidx_begin,
-                                                uint32_t const fidx_end) {
+bst_bin_t XGBOOST_HOST_DEV_INLINE BinarySearchBin(size_t begin, size_t end,
+                                                  GradientIndex const& data,
+                                                  uint32_t const fidx_begin,
+                                                  uint32_t const fidx_end) {
   size_t previous_middle = std::numeric_limits<size_t>::max();
   while (end != begin) {
     size_t middle = begin + (end - begin) / 2;
@@ -324,8 +322,6 @@ int32_t XGBOOST_HOST_DEV_INLINE BinarySearchBin(size_t begin, size_t end,
   return -1;
 }
 
-class ColumnMatrix;
-
 template<typename GradientSumT>
 using GHistRow = Span<xgboost::detail::GradientPairInternal<GradientSumT> >;
 

src/data/gradient_index.h

@@ -14,6 +14,10 @@
 #include "xgboost/data.h"
 
 namespace xgboost {
+namespace common {
+class ColumnMatrix;
+}  // namespace common
+
 /*!
  * \brief preprocessed global index matrix, in CSR format
  *
@@ -80,13 +84,13 @@ class GHistIndexMatrix {
       for (bst_uint j = 0; j < inst.size(); ++j) {
         auto e = inst[j];
         if (common::IsCat(ft, e.index)) {
-          auto bin_idx = cut.SearchCatBin(e);
+          bst_bin_t bin_idx = cut.SearchCatBin(e);
           index_data[ibegin + j] = get_offset(bin_idx, j);
           ++hit_count_tloc_[tid * nbins + bin_idx];
         } else {
-          uint32_t idx = cut.SearchBin(e.fvalue, e.index, ptrs, values);
-          index_data[ibegin + j] = get_offset(idx, j);
-          ++hit_count_tloc_[tid * nbins + idx];
+          bst_bin_t bin_idx = cut.SearchBin(e.fvalue, e.index, ptrs, values);
+          index_data[ibegin + j] = get_offset(bin_idx, j);
+          ++hit_count_tloc_[tid * nbins + bin_idx];
         }
       }
     });