Define core multi-target regression tree structure.

R-package/src/Makevars.in

@@ -61,6 +61,7 @@ OBJECTS= \
     $(PKGROOT)/src/tree/fit_stump.o \
     $(PKGROOT)/src/tree/tree_model.o \
     $(PKGROOT)/src/tree/tree_updater.o \
+    $(PKGROOT)/src/tree/multi_target_tree_model.o \
     $(PKGROOT)/src/tree/updater_approx.o \
     $(PKGROOT)/src/tree/updater_colmaker.o \
     $(PKGROOT)/src/tree/updater_prune.o \

R-package/src/Makevars.win

@@ -60,6 +60,7 @@ OBJECTS= \
     $(PKGROOT)/src/tree/param.o \
     $(PKGROOT)/src/tree/fit_stump.o \
     $(PKGROOT)/src/tree/tree_model.o \
+    $(PKGROOT)/src/tree/multi_target_tree_model.o \
     $(PKGROOT)/src/tree/tree_updater.o \
     $(PKGROOT)/src/tree/updater_approx.o \
     $(PKGROOT)/src/tree/updater_colmaker.o \

include/xgboost/base.h

@@ -110,11 +110,11 @@ using bst_bin_t = int32_t;  // NOLINT
  */
 using bst_row_t = std::size_t;   // NOLINT
 /*! \brief Type for tree node index. */
-using bst_node_t = int32_t;      // NOLINT
+using bst_node_t = std::int32_t;      // NOLINT
 /*! \brief Type for ranking group index. */
-using bst_group_t = uint32_t;    // NOLINT
-/*! \brief Type for indexing target variables. */
-using bst_target_t = std::size_t;  // NOLINT
+using bst_group_t = std::uint32_t;      // NOLINT
+/*! \brief Type for indexing into output targets. */
+using bst_target_t = std::uint32_t;  // NOLINT
 
 namespace detail {
 /*! \brief Implementation of gradient statistics pair. Template specialisation

include/xgboost/multi_target_tree_model.h

@@ -0,0 +1,96 @@
+/**
+ * Copyright 2023 by XGBoost contributors
+ *
+ * \brief Core data structure for multi-target trees.
+ */
+#ifndef XGBOOST_MULTI_TARGET_TREE_MODEL_H_
+#define XGBOOST_MULTI_TARGET_TREE_MODEL_H_
+#include <xgboost/base.h>     // for bst_node_t, bst_target_t, bst_feature_t
+#include <xgboost/context.h>  // for Context
+#include <xgboost/linalg.h>   // for VectorView
+#include <xgboost/model.h>    // for Model
+#include <xgboost/span.h>     // for Span
+
+#include <cinttypes>          // for uint8_t
+#include <cstddef>            // for size_t
+#include <vector>             // for vector
+
+namespace xgboost {
+struct TreeParam;
+/**
+ * \brief Tree structure for multi-target model.
+ */
+class MultiTargetTree : public Model {
+ public:
+  static bst_node_t constexpr InvalidNodeId() { return -1; }
+
+ private:
+  TreeParam const* param_;
+  std::vector<bst_node_t> left_;
+  std::vector<bst_node_t> right_;
+  std::vector<bst_node_t> parent_;
+  std::vector<bst_feature_t> split_index_;
+  std::vector<std::uint8_t> default_left_;
+  std::vector<float> split_conds_;
+  std::vector<float> weights_;
+
+  [[nodiscard]] linalg::VectorView<float const> NodeWeight(bst_node_t nidx) const {
+    auto beg = nidx * this->NumTarget();
+    auto v = common::Span<float const>{weights_}.subspan(beg, this->NumTarget());
+    return linalg::MakeTensorView(Context::kCpuId, v, v.size());
+  }
+  [[nodiscard]] linalg::VectorView<float> NodeWeight(bst_node_t nidx) {
+    auto beg = nidx * this->NumTarget();
+    auto v = common::Span<float>{weights_}.subspan(beg, this->NumTarget());
+    return linalg::MakeTensorView(Context::kCpuId, v, v.size());
+  }
+
+ public:
+  explicit MultiTargetTree(TreeParam const* param);
+  /**
+   * \brief Set the weight for a leaf.
+   */
+  void SetLeaf(bst_node_t nidx, linalg::VectorView<float const> weight);
+  /**
+   * \brief Expand a leaf into split node.
+   */
+  void Expand(bst_node_t nidx, bst_feature_t split_idx, float split_cond, bool default_left,
+              linalg::VectorView<float const> base_weight,
+              linalg::VectorView<float const> left_weight,
+              linalg::VectorView<float const> right_weight);
+
+  [[nodiscard]] bool IsLeaf(bst_node_t nidx) const { return left_[nidx] == InvalidNodeId(); }
+  [[nodiscard]] bst_node_t Parent(bst_node_t nidx) const { return parent_.at(nidx); }
+  [[nodiscard]] bst_node_t LeftChild(bst_node_t nidx) const { return left_.at(nidx); }
+  [[nodiscard]] bst_node_t RightChild(bst_node_t nidx) const { return right_.at(nidx); }
+
+  [[nodiscard]] bst_feature_t SplitIndex(bst_node_t nidx) const { return split_index_[nidx]; }
+  [[nodiscard]] float SplitCond(bst_node_t nidx) const { return split_conds_[nidx]; }
+  [[nodiscard]] bool DefaultLeft(bst_node_t nidx) const { return default_left_[nidx]; }
+  [[nodiscard]] bst_node_t DefaultChild(bst_node_t nidx) const {
+    return this->DefaultLeft(nidx) ? this->LeftChild(nidx) : this->RightChild(nidx);
+  }
+
+  [[nodiscard]] bst_target_t NumTarget() const;
+
+  [[nodiscard]] std::size_t Size() const;
+
+  [[nodiscard]] bst_node_t Depth(bst_node_t nidx) const {
+    bst_node_t depth{0};
+    while (Parent(nidx) != InvalidNodeId()) {
+      ++depth;
+      nidx = Parent(nidx);
+    }
+    return depth;
+  }
+
+  [[nodiscard]] linalg::VectorView<float const> LeafValue(bst_node_t nidx) const {
+    CHECK(IsLeaf(nidx));
+    return this->NodeWeight(nidx);
+  }
+
+  void LoadModel(Json const& in) override;
+  void SaveModel(Json* out) const override;
+};
+}  // namespace xgboost
+#endif  // XGBOOST_MULTI_TARGET_TREE_MODEL_H_