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Partitioner for multi-target tree. (#8922)

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This commit is contained in:
Jiaming Yuan
2023-03-16 18:49:34 +08:00
committed by GitHub
parent 26209a42a5
commit a093770f36
8 changed files with 239 additions and 178 deletions
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49
tests/cpp/tree/test_quantile_hist.cc
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@@ -1,25 +1,29 @@
/*!
* Copyright 2018-2022 by XGBoost Contributors
/**
* Copyright 2018-2023 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/tree_updater.h>
#include <algorithm>
#include <cstddef> // for size_t
#include <string>
#include <vector>
#include "../../../src/tree/common_row_partitioner.h"
#include "../../../src/tree/hist/expand_entry.h" // for MultiExpandEntry, CPUExpandEntry
#include "../../../src/tree/param.h"
#include "../../../src/tree/split_evaluator.h"
#include "../../../src/tree/common_row_partitioner.h"
#include "../helpers.h"
#include "test_partitioner.h"
#include "xgboost/data.h"
namespace xgboost {
namespace tree {
TEST(QuantileHist, Partitioner) {
size_t n_samples = 1024, n_features = 1, base_rowid = 0;
namespace xgboost::tree {
template <typename ExpandEntry>
void TestPartitioner(bst_target_t n_targets) {
std::size_t n_samples = 1024, base_rowid = 0;
bst_feature_t n_features = 1;
Context ctx;
ctx.InitAllowUnknown(Args{});
@@ -29,7 +33,7 @@ TEST(QuantileHist, Partitioner) {
ASSERT_EQ(partitioner.Partitions()[0].Size(), n_samples);
auto Xy = RandomDataGenerator{n_samples, n_features, 0}.GenerateDMatrix(true);
std::vector<CPUExpandEntry> candidates{{0, 0}};
std::vector<ExpandEntry> candidates{{0, 0}};
candidates.front().split.loss_chg = 0.4;
auto cuts = common::SketchOnDMatrix(Xy.get(), 64, ctx.Threads());
@@ -41,9 +45,13 @@ TEST(QuantileHist, Partitioner) {
column_indices.InitFromSparse(page, gmat, 0.5, ctx.Threads());
{
auto min_value = gmat.cut.MinValues()[split_ind];
RegTree tree;
RegTree tree{n_targets, n_features};
CommonRowPartitioner partitioner{&ctx, n_samples, base_rowid, false};
GetSplit(&tree, min_value, &candidates);
if constexpr (std::is_same<ExpandEntry, CPUExpandEntry>::value) {
GetSplit(&tree, min_value, &candidates);
} else {
GetMultiSplitForTest(&tree, min_value, &candidates);
}
partitioner.UpdatePosition<false, true>(&ctx, gmat, column_indices, candidates, &tree);
ASSERT_EQ(partitioner.Size(), 3);
ASSERT_EQ(partitioner[1].Size(), 0);
@@ -53,9 +61,13 @@ TEST(QuantileHist, Partitioner) {
CommonRowPartitioner partitioner{&ctx, n_samples, base_rowid, false};
auto ptr = gmat.cut.Ptrs()[split_ind + 1];
float split_value = gmat.cut.Values().at(ptr / 2);
RegTree tree;
GetSplit(&tree, split_value, &candidates);
auto left_nidx = tree[RegTree::kRoot].LeftChild();
RegTree tree{n_targets, n_features};
if constexpr (std::is_same<ExpandEntry, CPUExpandEntry>::value) {
GetSplit(&tree, split_value, &candidates);
} else {
GetMultiSplitForTest(&tree, split_value, &candidates);
}
auto left_nidx = tree.LeftChild(RegTree::kRoot);
partitioner.UpdatePosition<false, true>(&ctx, gmat, column_indices, candidates, &tree);
auto elem = partitioner[left_nidx];
@@ -65,14 +77,17 @@ TEST(QuantileHist, Partitioner) {
auto value = gmat.cut.Values().at(gmat.index[*it]);
ASSERT_LE(value, split_value);
}
auto right_nidx = tree[RegTree::kRoot].RightChild();
auto right_nidx = tree.RightChild(RegTree::kRoot);
elem = partitioner[right_nidx];
for (auto it = elem.begin; it != elem.end; ++it) {
auto value = gmat.cut.Values().at(gmat.index[*it]);
ASSERT_GT(value, split_value) << *it;
ASSERT_GT(value, split_value);
}
}
}
}
} // namespace tree
} // namespace xgboost
TEST(QuantileHist, Partitioner) { TestPartitioner<CPUExpandEntry>(1); }
TEST(QuantileHist, MultiPartitioner) { TestPartitioner<MultiExpandEntry>(3); }
} // namespace xgboost::tree