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Requires setting leaf stat when expanding tree. (#5501)

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* Fix GPU Hist feature importance.
This commit is contained in:
Jiaming Yuan
2020-04-10 12:27:03 +08:00
committed by GitHub
parent dc2950fd90
commit 7d52c0b8c2
11 changed files with 179 additions and 50 deletions
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52
include/xgboost/tree_model.h
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@@ -22,6 +22,7 @@
#include <cstring>
#include <algorithm>
#include <tuple>
#include <stack>
namespace xgboost {
@@ -88,6 +89,10 @@ struct RTreeNodeStat {
bst_float base_weight;
/*! \brief number of child that is leaf node known up to now */
int leaf_child_cnt {0};
RTreeNodeStat() = default;
RTreeNodeStat(float loss_chg, float sum_hess, float weight) :
loss_chg{loss_chg}, sum_hess{sum_hess}, base_weight{weight} {}
bool operator==(const RTreeNodeStat& b) const {
return loss_chg == b.loss_chg && sum_hess == b.sum_hess &&
base_weight == b.base_weight && leaf_child_cnt == b.leaf_child_cnt;
@@ -101,8 +106,9 @@ struct RTreeNodeStat {
class RegTree : public Model {
public:
using SplitCondT = bst_float;
static constexpr int32_t kInvalidNodeId {-1};
static constexpr bst_node_t kInvalidNodeId {-1};
static constexpr uint32_t kDeletedNodeMarker = std::numeric_limits<uint32_t>::max();
static constexpr bst_node_t kRoot { 0 };
/*! \brief tree node */
class Node {
@@ -321,6 +327,31 @@ class RegTree : public Model {
return nodes_ == b.nodes_ && stats_ == b.stats_ &&
deleted_nodes_ == b.deleted_nodes_ && param == b.param;
}
/* \brief Iterate through all nodes in this tree.
*
* \param Function that accepts a node index, and returns false when iteration should
* stop, otherwise returns true.
*/
template <typename Func> void WalkTree(Func func) const {
std::stack<bst_node_t> nodes;
nodes.push(kRoot);
auto &self = *this;
while (!nodes.empty()) {
auto nidx = nodes.top();
nodes.pop();
if (!func(nidx)) {
return;
}
auto left = self[nidx].LeftChild();
auto right = self[nidx].RightChild();
if (left != RegTree::kInvalidNodeId) {
nodes.push(left);
}
if (right != RegTree::kInvalidNodeId) {
nodes.push(right);
}
}
}
/*!
* \brief Compares whether 2 trees are equal from a user's perspective. The equality
* compares only non-deleted nodes.
@@ -341,13 +372,16 @@ class RegTree : public Model {
* \param right_leaf_weight The right leaf weight for prediction, modified by learning rate.
* \param loss_change The loss change.
* \param sum_hess The sum hess.
* \param leaf_right_child The right child index of leaf, by default kInvalidNodeId,
* some updaters use the right child index of leaf as a marker
* \param left_sum The sum hess of left leaf.
* \param right_sum The sum hess of right leaf.
* \param leaf_right_child The right child index of leaf, by default kInvalidNodeId,
* some updaters use the right child index of leaf as a marker
*/
void ExpandNode(int nid, unsigned split_index, bst_float split_value,
bool default_left, bst_float base_weight,
bst_float left_leaf_weight, bst_float right_leaf_weight,
bst_float loss_change, float sum_hess,
bst_float loss_change, float sum_hess, float left_sum,
float right_sum,
bst_node_t leaf_right_child = kInvalidNodeId) {
int pleft = this->AllocNode();
int pright = this->AllocNode();
@@ -363,9 +397,9 @@ class RegTree : public Model {
nodes_[pleft].SetLeaf(left_leaf_weight, leaf_right_child);
nodes_[pright].SetLeaf(right_leaf_weight, leaf_right_child);
this->Stat(nid).loss_chg = loss_change;
this->Stat(nid).base_weight = base_weight;
this->Stat(nid).sum_hess = sum_hess;
this->Stat(nid) = {loss_change, sum_hess, base_weight};
this->Stat(pleft) = {0.0f, left_sum, left_leaf_weight};
this->Stat(pright) = {0.0f, right_sum, right_leaf_weight};
}
/*!
@@ -402,6 +436,10 @@ class RegTree : public Model {
return param.num_nodes - 1 - param.num_deleted;
}
/* \brief Count number of leaves in tree. */
bst_node_t GetNumLeaves() const;
bst_node_t GetNumSplitNodes() const;
/*!
* \brief dense feature vector that can be taken by RegTree
* and can be construct from sparse feature vector.