08ce495b5d
- Pass context from booster to DMatrix. - Use context instead of integer for `n_threads`. - Check the consistency configuration for `max_bin`. - Test for all combinations of initialization options.
94 lines
3.4 KiB
C++
94 lines
3.4 KiB
C++
/**
|
|
* 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 "../helpers.h"
|
|
#include "test_partitioner.h"
|
|
#include "xgboost/data.h"
|
|
|
|
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{});
|
|
|
|
CommonRowPartitioner partitioner{&ctx, n_samples, base_rowid, false};
|
|
ASSERT_EQ(partitioner.base_rowid, base_rowid);
|
|
ASSERT_EQ(partitioner.Size(), 1);
|
|
ASSERT_EQ(partitioner.Partitions()[0].Size(), n_samples);
|
|
|
|
auto Xy = RandomDataGenerator{n_samples, n_features, 0}.GenerateDMatrix(true);
|
|
std::vector<ExpandEntry> candidates{{0, 0}};
|
|
candidates.front().split.loss_chg = 0.4;
|
|
|
|
auto cuts = common::SketchOnDMatrix(&ctx, Xy.get(), 64);
|
|
|
|
for (auto const& page : Xy->GetBatches<SparsePage>()) {
|
|
GHistIndexMatrix gmat(page, {}, cuts, 64, true, 0.5, ctx.Threads());
|
|
bst_feature_t const split_ind = 0;
|
|
common::ColumnMatrix column_indices;
|
|
column_indices.InitFromSparse(page, gmat, 0.5, ctx.Threads());
|
|
{
|
|
auto min_value = gmat.cut.MinValues()[split_ind];
|
|
RegTree tree{n_targets, n_features};
|
|
CommonRowPartitioner partitioner{&ctx, n_samples, base_rowid, false};
|
|
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);
|
|
ASSERT_EQ(partitioner[2].Size(), n_samples);
|
|
}
|
|
{
|
|
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{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];
|
|
ASSERT_LT(elem.Size(), n_samples);
|
|
ASSERT_GT(elem.Size(), 1);
|
|
for (auto it = elem.begin; it != elem.end; ++it) {
|
|
auto value = gmat.cut.Values().at(gmat.index[*it]);
|
|
ASSERT_LE(value, split_value);
|
|
}
|
|
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);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST(QuantileHist, Partitioner) { TestPartitioner<CPUExpandEntry>(1); }
|
|
|
|
TEST(QuantileHist, MultiPartitioner) { TestPartitioner<MultiExpandEntry>(3); }
|
|
} // namespace xgboost::tree
|