Partitioner for multi-target tree. (#8922)

dmlc · Mar 16, 2023 · a093770 · a093770
1 parent 26209a4
commit a093770
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Showing 8 changed files with 239 additions and 178 deletions.
diff --git a/src/common/partition_builder.h b/src/common/partition_builder.h
@@ -1,5 +1,5 @@
-/*!
- * Copyright 2021-2022 by Contributors
+/**
+ * Copyright 2021-2023 by Contributors
  * \file row_set.h
  * \brief Quick Utility to compute subset of rows
  * \author Philip Cho, Tianqi Chen
@@ -10,6 +10,7 @@
 #include <xgboost/data.h>
 
 #include <algorithm>
+#include <cstddef>  // for size_t
 #include <limits>
 #include <memory>
 #include <utility>
@@ -21,9 +22,7 @@
 #include "xgboost/context.h"
 #include "xgboost/tree_model.h"
 
-namespace xgboost {
-namespace common {
-
+namespace xgboost::common {
 // The builder is required for samples partition to left and rights children for set of nodes
 // Responsible for:
 // 1) Effective memory allocation for intermediate results for multi-thread work
@@ -109,18 +108,17 @@ class PartitionBuilder {
     return {nleft_elems, nright_elems};
   }
 
-  template <typename BinIdxType, bool any_missing, bool any_cat>
-  void Partition(const size_t node_in_set, std::vector<xgboost::tree::CPUExpandEntry> const &nodes,
-                 const common::Range1d range,
-                 const bst_bin_t split_cond, GHistIndexMatrix const& gmat,
-                 const common::ColumnMatrix& column_matrix,
+  template <typename BinIdxType, bool any_missing, bool any_cat, typename ExpandEntry>
+  void Partition(const size_t node_in_set, std::vector<ExpandEntry> const& nodes,
+                 const common::Range1d range, const bst_bin_t split_cond,
+                 GHistIndexMatrix const& gmat, const common::ColumnMatrix& column_matrix,
                  const RegTree& tree, const size_t* rid) {
     common::Span<const size_t> rid_span(rid + range.begin(), rid + range.end());
     common::Span<size_t> left = GetLeftBuffer(node_in_set, range.begin(), range.end());
     common::Span<size_t> right = GetRightBuffer(node_in_set, range.begin(), range.end());
     std::size_t nid = nodes[node_in_set].nid;
-    bst_feature_t fid = tree[nid].SplitIndex();
-    bool default_left = tree[nid].DefaultLeft();
+    bst_feature_t fid = tree.SplitIndex(nid);
+    bool default_left = tree.DefaultLeft(nid);
     bool is_cat = tree.GetSplitTypes()[nid] == FeatureType::kCategorical;
     auto node_cats = tree.NodeCats(nid);
     auto const& cut_values = gmat.cut.Values();
@@ -190,10 +188,10 @@ class PartitionBuilder {
    * worker, so we go through all the rows and mark the bit vectors on whether the decision is made
    * to go right, or if the feature value used for the split is missing.
    */
-  void MaskRows(const size_t node_in_set, std::vector<xgboost::tree::CPUExpandEntry> const &nodes,
+  template <typename ExpandEntry>
+  void MaskRows(const size_t node_in_set, std::vector<ExpandEntry> const& nodes,
                 const common::Range1d range, GHistIndexMatrix const& gmat,
-                const common::ColumnMatrix& column_matrix,
-                const RegTree& tree, const size_t* rid,
+                const common::ColumnMatrix& column_matrix, const RegTree& tree, const size_t* rid,
                 BitVector* decision_bits, BitVector* missing_bits) {
     common::Span<const size_t> rid_span(rid + range.begin(), rid + range.end());
     std::size_t nid = nodes[node_in_set].nid;
@@ -228,8 +226,8 @@ class PartitionBuilder {
    * @brief Once we've aggregated the decision and missing bits from all the workers, we can then
    * use them to partition the rows accordingly.
    */
-  void PartitionByMask(const size_t node_in_set,
-                       std::vector<xgboost::tree::CPUExpandEntry> const& nodes,
+  template <typename ExpandEntry>
+  void PartitionByMask(const size_t node_in_set, std::vector<ExpandEntry> const& nodes,
                        const common::Range1d range, GHistIndexMatrix const& gmat,
                        const common::ColumnMatrix& column_matrix, const RegTree& tree,
                        const size_t* rid, BitVector const& decision_bits,
@@ -293,11 +291,11 @@ class PartitionBuilder {
   }
 
 
-  size_t GetNLeftElems(int nid) const {
+  [[nodiscard]] std::size_t GetNLeftElems(int nid) const {
     return left_right_nodes_sizes_[nid].first;
   }
 
-  size_t GetNRightElems(int nid) const {
+  [[nodiscard]] std::size_t GetNRightElems(int nid) const {
     return left_right_nodes_sizes_[nid].second;
   }
 
@@ -349,7 +347,7 @@ class PartitionBuilder {
       if (node.node_id < 0) {
         return;
       }
-      CHECK(tree[node.node_id].IsLeaf());
+      CHECK(tree.IsLeaf(node.node_id));
       if (node.begin) {  // guard for empty node.
         size_t ptr_offset = node.end - p_begin;
         CHECK_LE(ptr_offset, row_set.Data()->size()) << node.node_id;
@@ -384,8 +382,5 @@ class PartitionBuilder {
   std::vector<std::shared_ptr<BlockInfo>> mem_blocks_;
   size_t max_n_tasks_ = 0;
 };
-
-}  // namespace common
-}  // namespace xgboost
-
+}  // namespace xgboost::common
 #endif  // XGBOOST_COMMON_PARTITION_BUILDER_H_
diff --git a/src/learner.cc b/src/learner.cc
@@ -343,8 +343,8 @@ struct LearnerTrainParam : public XGBoostParameter<LearnerTrainParam> {
         .add_enum("monolithic", MultiStrategy::kMonolithic)
         .set_default(MultiStrategy::kComposite)
         .describe(
-            "Strategy used for training multi-target models. `mono` means building one single tree "
-            "for all targets.");
+            "Strategy used for training multi-target models. `monolithic` means building one "
+            "single tree for all targets.");
   }
 };
 

diff --git a/src/tree/common_row_partitioner.h b/src/tree/common_row_partitioner.h
@@ -1,22 +1,26 @@
-/*!
- * Copyright 2021-2022 XGBoost contributors
+/**
+ * Copyright 2021-2023 XGBoost contributors
  * \file common_row_partitioner.h
  * \brief Common partitioner logic for hist and approx methods.
  */
 #ifndef XGBOOST_TREE_COMMON_ROW_PARTITIONER_H_
 #define XGBOOST_TREE_COMMON_ROW_PARTITIONER_H_
 
+#include <algorithm>  // std::all_of
+#include <cinttypes>  // std::uint32_t
 #include <limits>  // std::numeric_limits
 #include <vector>
 
 #include "../collective/communicator-inl.h"
+#include "../common/linalg_op.h"  // cbegin
 #include "../common/numeric.h"  // Iota
 #include "../common/partition_builder.h"
 #include "hist/expand_entry.h"  // CPUExpandEntry
+#include "xgboost/base.h"
 #include "xgboost/context.h"    // Context
+#include "xgboost/linalg.h"       // TensorView
 
-namespace xgboost {
-namespace tree {
+namespace xgboost::tree {
 
 static constexpr size_t kPartitionBlockSize = 2048;
 
@@ -34,9 +38,10 @@ class ColumnSplitHelper {
     missing_bits_ = BitVector(common::Span<BitVector::value_type>(missing_storage_));
   }
 
+  template <typename ExpandEntry>
   void Partition(common::BlockedSpace2d const& space, std::int32_t n_threads,
                  GHistIndexMatrix const& gmat, common::ColumnMatrix const& column_matrix,
-                 std::vector<CPUExpandEntry> const& nodes, RegTree const* p_tree) {
+                 std::vector<ExpandEntry> const& nodes, RegTree const* p_tree) {
     // When data is split by column, we don't have all the feature values in the local worker, so
     // we first collect all the decisions and whether the feature is missing into bit vectors.
     std::fill(decision_storage_.begin(), decision_storage_.end(), 0);
@@ -97,17 +102,18 @@ class CommonRowPartitioner {
     }
   }
 
-  void FindSplitConditions(const std::vector<CPUExpandEntry>& nodes, const RegTree& tree,
+  template <typename ExpandEntry>
+  void FindSplitConditions(const std::vector<ExpandEntry>& nodes, const RegTree& tree,
                            const GHistIndexMatrix& gmat, std::vector<int32_t>* split_conditions) {
     auto const& ptrs = gmat.cut.Ptrs();
     auto const& vals = gmat.cut.Values();
 
     for (std::size_t i = 0; i < nodes.size(); ++i) {
-      bst_node_t const nid = nodes[i].nid;
-      bst_feature_t const fid = tree[nid].SplitIndex();
-      const float split_pt = tree[nid].SplitCond();
-      const uint32_t lower_bound = ptrs[fid];
-      const uint32_t upper_bound = ptrs[fid + 1];
+      bst_node_t const nidx = nodes[i].nid;
+      bst_feature_t const fidx = tree.SplitIndex(nidx);
+      float const split_pt = tree.SplitCond(nidx);
+      std::uint32_t const lower_bound = ptrs[fidx];
+      std::uint32_t const upper_bound = ptrs[fidx + 1];
       bst_bin_t split_cond = -1;
       // convert floating-point split_pt into corresponding bin_id
       // split_cond = -1 indicates that split_pt is less than all known cut points
@@ -121,20 +127,22 @@ class CommonRowPartitioner {
     }
   }
 
-  void AddSplitsToRowSet(const std::vector<CPUExpandEntry>& nodes, RegTree const* p_tree) {
+  template <typename ExpandEntry>
+  void AddSplitsToRowSet(const std::vector<ExpandEntry>& nodes, RegTree const* p_tree) {
     const size_t n_nodes = nodes.size();
     for (unsigned int i = 0; i < n_nodes; ++i) {
-      const int32_t nid = nodes[i].nid;
+      const int32_t nidx = nodes[i].nid;
       const size_t n_left = partition_builder_.GetNLeftElems(i);
       const size_t n_right = partition_builder_.GetNRightElems(i);
-      CHECK_EQ((*p_tree)[nid].LeftChild() + 1, (*p_tree)[nid].RightChild());
-      row_set_collection_.AddSplit(nid, (*p_tree)[nid].LeftChild(), (*p_tree)[nid].RightChild(),
-                                   n_left, n_right);
+      CHECK_EQ(p_tree->LeftChild(nidx) + 1, p_tree->RightChild(nidx));
+      row_set_collection_.AddSplit(nidx, p_tree->LeftChild(nidx), p_tree->RightChild(nidx), n_left,
+                                   n_right);
     }
   }
 
+  template <typename ExpandEntry>
   void UpdatePosition(Context const* ctx, GHistIndexMatrix const& gmat,
-                      std::vector<CPUExpandEntry> const& nodes, RegTree const* p_tree) {
+                      std::vector<ExpandEntry> const& nodes, RegTree const* p_tree) {
     auto const& column_matrix = gmat.Transpose();
     if (column_matrix.IsInitialized()) {
       if (gmat.cut.HasCategorical()) {
@@ -152,44 +160,32 @@ class CommonRowPartitioner {
     }
   }
 
-  template <bool any_cat>
+  template <bool any_cat, typename ExpandEntry>
   void UpdatePosition(Context const* ctx, GHistIndexMatrix const& gmat,
                       const common::ColumnMatrix& column_matrix,
-                      std::vector<CPUExpandEntry> const& nodes, RegTree const* p_tree) {
+                      std::vector<ExpandEntry> const& nodes, RegTree const* p_tree) {
     if (column_matrix.AnyMissing()) {
       this->template UpdatePosition<true, any_cat>(ctx, gmat, column_matrix, nodes, p_tree);
     } else {
       this->template UpdatePosition<false, any_cat>(ctx, gmat, column_matrix, nodes, p_tree);
     }
   }
 
-  template <bool any_missing, bool any_cat>
+  template <bool any_missing, bool any_cat, typename ExpandEntry>
   void UpdatePosition(Context const* ctx, GHistIndexMatrix const& gmat,
                       const common::ColumnMatrix& column_matrix,
-                      std::vector<CPUExpandEntry> const& nodes, RegTree const* p_tree) {
-    switch (column_matrix.GetTypeSize()) {
-      case common::kUint8BinsTypeSize:
-        this->template UpdatePosition<uint8_t, any_missing, any_cat>(ctx, gmat, column_matrix,
-                                                                     nodes, p_tree);
-        break;
-      case common::kUint16BinsTypeSize:
-        this->template UpdatePosition<uint16_t, any_missing, any_cat>(ctx, gmat, column_matrix,
-                                                                      nodes, p_tree);
-        break;
-      case common::kUint32BinsTypeSize:
-        this->template UpdatePosition<uint32_t, any_missing, any_cat>(ctx, gmat, column_matrix,
-                                                                      nodes, p_tree);
-        break;
-      default:
-        // no default behavior
-        CHECK(false) << column_matrix.GetTypeSize();
-    }
+                      std::vector<ExpandEntry> const& nodes, RegTree const* p_tree) {
+    common::DispatchBinType(column_matrix.GetTypeSize(), [&](auto t) {
+      using T = decltype(t);
+      this->template UpdatePosition<T, any_missing, any_cat>(ctx, gmat, column_matrix, nodes,
+                                                             p_tree);
+    });
   }
 
-  template <typename BinIdxType, bool any_missing, bool any_cat>
+  template <typename BinIdxType, bool any_missing, bool any_cat, typename ExpandEntry>
   void UpdatePosition(Context const* ctx, GHistIndexMatrix const& gmat,
                       const common::ColumnMatrix& column_matrix,
-                      std::vector<CPUExpandEntry> const& nodes, RegTree const* p_tree) {
+                      std::vector<ExpandEntry> const& nodes, RegTree const* p_tree) {
     // 1. Find split condition for each split
     size_t n_nodes = nodes.size();
 
@@ -251,9 +247,9 @@ class CommonRowPartitioner {
     AddSplitsToRowSet(nodes, p_tree);
   }
 
-  auto const& Partitions() const { return row_set_collection_; }
+  [[nodiscard]] auto const& Partitions() const { return row_set_collection_; }
 
-  size_t Size() const {
+  [[nodiscard]] std::size_t Size() const {
     return std::distance(row_set_collection_.begin(), row_set_collection_.end());
   }
 
@@ -266,12 +262,29 @@ class CommonRowPartitioner {
                                      [&](size_t idx) -> bool { return hess[idx] - .0f == .0f; });
   }
 
+  void LeafPartition(Context const* ctx, RegTree const& tree,
+                     linalg::TensorView<GradientPair const, 2> gpair,
+                     std::vector<bst_node_t>* p_out_position) const {
+    if (gpair.Shape(1) > 1) {
+      partition_builder_.LeafPartition(
+          ctx, tree, this->Partitions(), p_out_position, [&](std::size_t idx) -> bool {
+            auto sample = gpair.Slice(idx, linalg::All());
+            return std::all_of(linalg::cbegin(sample), linalg::cend(sample),
+                               [](GradientPair const& g) { return g.GetHess() - .0f == .0f; });
+          });
+    } else {
+      auto s = gpair.Slice(linalg::All(), 0);
+      partition_builder_.LeafPartition(
+          ctx, tree, this->Partitions(), p_out_position,
+          [&](std::size_t idx) -> bool { return s(idx).GetHess() - .0f == .0f; });
+    }
+  }
   void LeafPartition(Context const* ctx, RegTree const& tree,
                      common::Span<GradientPair const> gpair,
                      std::vector<bst_node_t>* p_out_position) const {
     partition_builder_.LeafPartition(
         ctx, tree, this->Partitions(), p_out_position,
-        [&](size_t idx) -> bool { return gpair[idx].GetHess() - .0f == .0f; });
+        [&](std::size_t idx) -> bool { return gpair[idx].GetHess() - .0f == .0f; });
   }
 
  private:
@@ -281,6 +294,5 @@ class CommonRowPartitioner {
   ColumnSplitHelper column_split_helper_;
 };
 
-}  // namespace tree
-}  // namespace xgboost
+}  // namespace xgboost::tree
 #endif  // XGBOOST_TREE_COMMON_ROW_PARTITIONER_H_
diff --git a/tests/cpp/common/test_partition_builder.cc b/tests/cpp/common/test_partition_builder.cc
@@ -1,15 +1,17 @@
+/**
+ * Copyright 2020-2023 by XGBoost contributors
+ */
 #include <gtest/gtest.h>
-#include <vector>
+
 #include <string>
 #include <utility>
+#include <vector>
 
-#include "../../../src/common/row_set.h"
 #include "../../../src/common/partition_builder.h"
+#include "../../../src/common/row_set.h"
 #include "../helpers.h"
 
-namespace xgboost {
-namespace common {
-
+namespace xgboost::common {
 TEST(PartitionBuilder, BasicTest) {
   constexpr size_t kBlockSize = 16;
   constexpr size_t kNodes = 5;
@@ -74,6 +76,4 @@ TEST(PartitionBuilder, BasicTest) {
     ASSERT_EQ(n_right, (kBlockSize - rows_for_left_node[nid]) * tasks[nid]);
   }
 }
-
-}  // namespace common
-}  // namespace xgboost
+}  // namespace xgboost::common