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Remove leaf vector, add tree serialisation test, fix Windows tests (#3989)

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Rory Mitchell 2018-12-13 10:28:38 +13:00 committed by GitHub
parent 84a3af8dc0
commit 3d81c48d3f
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9 changed files with 95 additions and 36 deletions
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18
include/xgboost/tree_model.h
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@ -198,8 +198,6 @@ class TreeModel {
std::vector<int> deleted_nodes_;
// stats of nodes
std::vector<TNodeStat> stats_;
// leaf vector, that is used to store additional information
std::vector<bst_float> leaf_vector_;
// allocate a new node,
// !!!!!! NOTE: may cause BUG here, nodes.resize
inline int AllocNode() {
@ -214,7 +212,6 @@ class TreeModel {
<< "number of nodes in the tree exceed 2^31";
nodes_.resize(param.num_nodes);
stats_.resize(param.num_nodes);
leaf_vector_.resize(param.num_nodes * param.size_leaf_vector);
return nd;
}
// delete a tree node, keep the parent field to allow trace back
@ -284,22 +281,11 @@ class TreeModel {
inline const NodeStat& Stat(int nid) const {
return stats_[nid];
}
/*! \brief get leaf vector given nid */
inline bst_float* Leafvec(int nid) {
if (leaf_vector_.size() == 0) return nullptr;
return& leaf_vector_[nid * param.size_leaf_vector];
}
/*! \brief get leaf vector given nid */
inline const bst_float* Leafvec(int nid) const {
if (leaf_vector_.size() == 0) return nullptr;
return& leaf_vector_[nid * param.size_leaf_vector];
}
/*! \brief initialize the model */
inline void InitModel() {
param.num_nodes = param.num_roots;
nodes_.resize(param.num_nodes);
stats_.resize(param.num_nodes);
leaf_vector_.resize(param.num_nodes * param.size_leaf_vector, 0.0f);
for (int i = 0; i < param.num_nodes; i ++) {
nodes_[i].SetLeaf(0.0f);
nodes_[i].SetParent(-1);
@ -318,9 +304,6 @@ class TreeModel {
sizeof(Node) * nodes_.size());
CHECK_EQ(fi->Read(dmlc::BeginPtr(stats_), sizeof(NodeStat) * stats_.size()),
sizeof(NodeStat) * stats_.size());
if (param.size_leaf_vector != 0) {
CHECK(fi->Read(&leaf_vector_));
}
// chg deleted nodes
deleted_nodes_.resize(0);
for (int i = param.num_roots; i < param.num_nodes; ++i) {
@ -339,7 +322,6 @@ class TreeModel {
CHECK_NE(param.num_nodes, 0);
fo->Write(dmlc::BeginPtr(nodes_), sizeof(Node) * nodes_.size());
fo->Write(dmlc::BeginPtr(stats_), sizeof(NodeStat) * nodes_.size());
if (param.size_leaf_vector != 0) fo->Write(leaf_vector_);
}
/*!
* \brief add child nodes to node

2
src/tree/param.h
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@ -408,8 +408,6 @@ template <typename ParamT>
}
/*! \return whether the statistics is not used yet */
inline bool Empty() const { return sum_hess == 0.0; }
/*! \brief set leaf vector value based on statistics */
inline void SetLeafVec(const TrainParam& param, bst_float* vec) const {}
// constructor to allow inheritance
GradStats() = default;
/*! \brief add statistics to the data */

1
src/tree/updater_colmaker.cc
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@ -130,7 +130,6 @@ class ColMaker: public TreeUpdater {
p_tree->Stat(nid).loss_chg = snode_[nid].best.loss_chg;
p_tree->Stat(nid).base_weight = snode_[nid].weight;
p_tree->Stat(nid).sum_hess = static_cast<float>(snode_[nid].stats.sum_hess);
snode_[nid].stats.SetLeafVec(param_, p_tree->Leafvec(nid));
}
}

1
src/tree/updater_histmaker.cc
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@ -263,7 +263,6 @@ class HistMaker: public BaseMaker {
inline void SetStats(RegTree *p_tree, int nid, const TStats &node_sum) {
p_tree->Stat(nid).base_weight = static_cast<bst_float>(node_sum.CalcWeight(param_));
p_tree->Stat(nid).sum_hess = static_cast<bst_float>(node_sum.sum_hess);
node_sum.SetLeafVec(param_, p_tree->Leafvec(nid));
}
};

1
src/tree/updater_quantile_hist.cc
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@ -203,7 +203,6 @@ void QuantileHistMaker::Builder::Update(const GHistIndexMatrix& gmat,
p_tree->Stat(nid).loss_chg = snode_[nid].best.loss_chg;
p_tree->Stat(nid).base_weight = snode_[nid].weight;
p_tree->Stat(nid).sum_hess = static_cast<float>(snode_[nid].stats.sum_hess);
snode_[nid].stats.SetLeafVec(param_, p_tree->Leafvec(nid));
}
pruner_->Update(gpair, p_fmat, std::vector<RegTree*>{p_tree});

1
src/tree/updater_refresh.cc
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@ -127,7 +127,6 @@ class TreeRefresher: public TreeUpdater {
RegTree &tree = *p_tree;
tree.Stat(nid).base_weight = static_cast<bst_float>(gstats[nid].CalcWeight(param_));
tree.Stat(nid).sum_hess = static_cast<bst_float>(gstats[nid].sum_hess);
gstats[nid].SetLeafVec(param_, tree.Leafvec(nid));
if (tree[nid].IsLeaf()) {
if (param_.refresh_leaf) {
tree[nid].SetLeaf(tree.Stat(nid).base_weight * param_.learning_rate);

4
src/tree/updater_skmaker.cc
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@ -128,9 +128,6 @@ class SketchMaker: public BaseMaker {
inline static void Reduce(SKStats &a, const SKStats &b) { // NOLINT(*)
a.Add(b);
}
/*! \brief set leaf vector value based on statistics */
inline void SetLeafVec(const TrainParam &param, bst_float *vec) const {
}
};
inline void BuildSketch(const std::vector<GradientPair> &gpair,
DMatrix *p_fmat,
@ -303,7 +300,6 @@ class SketchMaker: public BaseMaker {
inline void SetStats(int nid, const SKStats &node_sum, RegTree *p_tree) {
p_tree->Stat(nid).base_weight = static_cast<bst_float>(node_sum.CalcWeight(param_));
p_tree->Stat(nid).sum_hess = static_cast<bst_float>(node_sum.sum_hess);
node_sum.SetLeafVec(param_, p_tree->Leafvec(nid));
}
inline void EnumerateSplit(const WXQSketch::Summary &pos_grad,
const WXQSketch::Summary &neg_grad,

16
tests/cpp/tree/test_quantile_hist.cc
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@ -48,14 +48,14 @@ class QuantileHistMock : public QuantileHistMaker {
BuildHist(gpair, row_set_collection_[nid],
gmat, quantile_index_block, hist_[nid]);
std::vector<GradientPairPrecise> solution {
{0.27, 0.29}, {0.27, 0.29}, {0.47, 0.49},
{0.27, 0.29}, {0.57, 0.59}, {0.26, 0.27},
{0.37, 0.39}, {0.23, 0.24}, {0.37, 0.39},
{0.27, 0.28}, {0.27, 0.29}, {0.37, 0.39},
{0.26, 0.27}, {0.23, 0.24}, {0.57, 0.59},
{0.47, 0.49}, {0.47, 0.49}, {0.37, 0.39},
{0.26, 0.27}, {0.23, 0.24}, {0.27, 0.28},
{0.57, 0.59}, {0.23, 0.24}, {0.47, 0.49}};
{0.27f, 0.29f}, {0.27f, 0.29f}, {0.47f, 0.49f},
{0.27f, 0.29f}, {0.57f, 0.59f}, {0.26f, 0.27f},
{0.37f, 0.39f}, {0.23f, 0.24f}, {0.37f, 0.39f},
{0.27f, 0.28f}, {0.27f, 0.29f}, {0.37f, 0.39f},
{0.26f, 0.27f}, {0.23f, 0.24f}, {0.57f, 0.59f},
{0.47f, 0.49f}, {0.47f, 0.49f}, {0.37f, 0.39f},
{0.26f, 0.27f}, {0.23f, 0.24f}, {0.27f, 0.28f},
{0.57f, 0.59f}, {0.23f, 0.24f}, {0.47f, 0.49f}};
for (size_t i = 0; i < hist_[nid].size; ++i) {
GradientPairPrecise sol = solution[i];

87
tests/cpp/tree/test_tree_model.cc Normal file
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@ -0,0 +1,87 @@
// Copyright by Contributors
#include <gtest/gtest.h>
#include <xgboost/tree_model.h>
#include "../helpers.h"
#include "dmlc/filesystem.h"
namespace xgboost {
// Manually construct tree in binary format
// Do not use structs in case they change
// We want to preserve backwards compatibility
TEST(Tree, Load) {
dmlc::TemporaryDirectory tempdir;
const std::string tmp_file = tempdir.path + "/tree.model";
std::unique_ptr<dmlc::Stream> fo(dmlc::Stream::Create(tmp_file.c_str(), "w"));
// Write params
EXPECT_EQ(sizeof(TreeParam), (31 + 6) * sizeof(int));
int num_roots = 1;
int num_nodes = 2;
int num_deleted = 0;
int max_depth = 1;
int num_feature = 0;
int size_leaf_vector = 0;
int reserved[31];
fo->Write(&num_roots, sizeof(int));
fo->Write(&num_nodes, sizeof(int));
fo->Write(&num_deleted, sizeof(int));
fo->Write(&max_depth, sizeof(int));
fo->Write(&num_feature, sizeof(int));
fo->Write(&size_leaf_vector, sizeof(int));
fo->Write(reserved, sizeof(int) * 31);
// Write 2 nodes
EXPECT_EQ(sizeof(RegTree::Node),
3 * sizeof(int) + 1 * sizeof(unsigned) + sizeof(float));
int parent = -1;
int cleft = 1;
int cright = -1;
unsigned sindex = 5;
float split_or_weight = 0.5;
fo->Write(&parent, sizeof(int));
fo->Write(&cleft, sizeof(int));
fo->Write(&cright, sizeof(int));
fo->Write(&sindex, sizeof(unsigned));
fo->Write(&split_or_weight, sizeof(float));
parent = 0;
cleft = -1;
cright = -1;
sindex = 2;
split_or_weight = 0.1;
fo->Write(&parent, sizeof(int));
fo->Write(&cleft, sizeof(int));
fo->Write(&cright, sizeof(int));
fo->Write(&sindex, sizeof(unsigned));
fo->Write(&split_or_weight, sizeof(float));
// Write 2x node stats
EXPECT_EQ(sizeof(RTreeNodeStat), 3 * sizeof(float) + sizeof(int));
bst_float loss_chg = 5.0;
bst_float sum_hess = 1.0;
bst_float base_weight = 3.0;
int leaf_child_cnt = 0;
fo->Write(&loss_chg, sizeof(float));
fo->Write(&sum_hess, sizeof(float));
fo->Write(&base_weight, sizeof(float));
fo->Write(&leaf_child_cnt, sizeof(int));
loss_chg = 50.0;
sum_hess = 10.0;
base_weight = 30.0;
leaf_child_cnt = 0;
fo->Write(&loss_chg, sizeof(float));
fo->Write(&sum_hess, sizeof(float));
fo->Write(&base_weight, sizeof(float));
fo->Write(&leaf_child_cnt, sizeof(int));
fo.reset();
std::unique_ptr<dmlc::Stream> fi(dmlc::Stream::Create(tmp_file.c_str(), "r"));
xgboost::RegTree tree;
tree.Load(fi.get());
EXPECT_EQ(tree.GetDepth(1), 1);
EXPECT_EQ(tree[0].SplitCond(), 0.5f);
EXPECT_EQ(tree[0].SplitIndex(), 5);
EXPECT_EQ(tree[1].LeafValue(), 0.1f);
EXPECT_TRUE(tree[1].IsLeaf());
}
} // namespace xgboost