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Do not initialise data structures to maximum possible tree size. (#7919)

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Rory Mitchell 2022-05-19 19:45:53 +02:00 committed by GitHub
parent 6f424d8d6c
commit f6babc814c
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2 changed files with 24 additions and 8 deletions
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15
src/tree/split_evaluator.h
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@ -13,6 +13,7 @@
#include <utility> #include <utility>
#include <vector> #include <vector>
#include <limits> #include <limits>
#include <algorithm>
#include "xgboost/tree_model.h" #include "xgboost/tree_model.h"
#include "xgboost/host_device_vector.h" #include "xgboost/host_device_vector.h"
@ -49,8 +50,9 @@ class TreeEvaluator {
} else { } else {
monotone_.HostVector() = p.monotone_constraints; monotone_.HostVector() = p.monotone_constraints;
monotone_.HostVector().resize(n_features, 0); monotone_.HostVector().resize(n_features, 0);
lower_bounds_.Resize(p.MaxNodes(), -std::numeric_limits<float>::max()); // Initialised to some small size, can grow if needed
upper_bounds_.Resize(p.MaxNodes(), std::numeric_limits<float>::max()); lower_bounds_.Resize(256, -std::numeric_limits<float>::max());
upper_bounds_.Resize(256, std::numeric_limits<float>::max());
has_constraint_ = true; has_constraint_ = true;
} }
@ -157,6 +159,15 @@ class TreeEvaluator {
if (!has_constraint_) { if (!has_constraint_) {
return; return;
} }
auto max_nidx = std::max(leftid, rightid);
if (lower_bounds_.Size() <= max_nidx) {
lower_bounds_.Resize(max_nidx * 2 + 1, -std::numeric_limits<float>::max());
}
if (upper_bounds_.Size() <= max_nidx) {
upper_bounds_.Resize(max_nidx * 2 + 1, std::numeric_limits<float>::max());
}
common::Transform<>::Init( common::Transform<>::Init(
[=] XGBOOST_DEVICE(size_t, common::Span<float> lower, [=] XGBOOST_DEVICE(size_t, common::Span<float> lower,
common::Span<float> upper, common::Span<float> upper,

17
src/tree/updater_gpu_hist.cu
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@ -223,7 +223,7 @@ struct GPUHistMakerDevice {
// Copy assigning an empty vector causes an exception in MSVC debug builds // Copy assigning an empty vector causes an exception in MSVC debug builds
monotone_constraints = param.monotone_constraints; monotone_constraints = param.monotone_constraints;
} }
node_sum_gradients.resize(param.MaxNodes()); node_sum_gradients.resize(256);
// Init histogram // Init histogram
hist.Init(ctx_->gpu_id, page->Cuts().TotalBins()); hist.Init(ctx_->gpu_id, page->Cuts().TotalBins());
@ -614,12 +614,17 @@ struct GPUHistMakerDevice {
} }
evaluator_.ApplyTreeSplit(candidate, p_tree); evaluator_.ApplyTreeSplit(candidate, p_tree);
node_sum_gradients[tree[candidate.nid].LeftChild()] = candidate.split.left_sum; const auto& parent = tree[candidate.nid];
node_sum_gradients[tree[candidate.nid].RightChild()] = candidate.split.right_sum; std::size_t max_nidx = std::max(parent.LeftChild(), parent.RightChild());
// Grow as needed
if (node_sum_gradients.size() <= max_nidx) {
node_sum_gradients.resize(max_nidx * 2 + 1);
}
node_sum_gradients[parent.LeftChild()] = candidate.split.left_sum;
node_sum_gradients[parent.RightChild()] = candidate.split.right_sum;
interaction_constraints.Split(candidate.nid, tree[candidate.nid].SplitIndex(), interaction_constraints.Split(candidate.nid, parent.SplitIndex(), parent.LeftChild(),
tree[candidate.nid].LeftChild(), parent.RightChild());
tree[candidate.nid].RightChild());
} }
GPUExpandEntry InitRoot(RegTree* p_tree, dh::AllReducer* reducer) { GPUExpandEntry InitRoot(RegTree* p_tree, dh::AllReducer* reducer) {