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Consistent use of context to specify number of threads. (#8733)

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- Use context in all tests.
- Use context in R.
- Use context in C API DMatrix initialization. (0 threads is used as dft).
This commit is contained in:
Jiaming Yuan
2023-01-30 15:25:31 +08:00
committed by GitHub
parent 21a28f2cc5
commit 3760cede0f
24 changed files with 212 additions and 152 deletions
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44
tests/cpp/common/test_hist_util.cc
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@@ -1,5 +1,5 @@
/*!
* Copyright 2019-2022 by XGBoost Contributors
/**
* Copyright 2019-2023 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <vector>
@@ -14,15 +14,13 @@
namespace xgboost {
namespace common {
size_t GetNThreads() { return common::OmpGetNumThreads(0); }
void ParallelGHistBuilderReset() {
constexpr size_t kBins = 10;
constexpr size_t kNodes = 5;
constexpr size_t kNodesExtended = 10;
constexpr size_t kTasksPerNode = 10;
constexpr double kValue = 1.0;
const size_t nthreads = GetNThreads();
const size_t nthreads = AllThreadsForTest();
HistCollection collection;
collection.Init(kBins);
@@ -78,7 +76,7 @@ void ParallelGHistBuilderReduceHist(){
constexpr size_t kNodes = 5;
constexpr size_t kTasksPerNode = 10;
constexpr double kValue = 1.0;
const size_t nthreads = GetNThreads();
const size_t nthreads = AllThreadsForTest();
HistCollection collection;
collection.Init(kBins);
@@ -167,7 +165,7 @@ TEST(HistUtil, DenseCutsCategorical) {
std::vector<float> x_sorted(x);
std::sort(x_sorted.begin(), x_sorted.end());
auto dmat = GetDMatrixFromData(x, n, 1);
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0));
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, AllThreadsForTest());
auto cuts_from_sketch = cuts.Values();
EXPECT_LT(cuts.MinValues()[0], x_sorted.front());
EXPECT_GT(cuts_from_sketch.front(), x_sorted.front());
@@ -180,13 +178,12 @@ TEST(HistUtil, DenseCutsCategorical) {
TEST(HistUtil, DenseCutsAccuracyTest) {
int bin_sizes[] = {2, 16, 256, 512};
int sizes[] = {100};
// omp_set_num_threads(1);
int num_columns = 5;
for (auto num_rows : sizes) {
auto x = GenerateRandom(num_rows, num_columns);
auto dmat = GetDMatrixFromData(x, num_rows, num_columns);
for (auto num_bins : bin_sizes) {
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0));
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, AllThreadsForTest());
ValidateCuts(cuts, dmat.get(), num_bins);
}
}
@@ -203,13 +200,11 @@ TEST(HistUtil, DenseCutsAccuracyTestWeights) {
dmat->Info().weights_.HostVector() = w;
for (auto num_bins : bin_sizes) {
{
HistogramCuts cuts =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), true);
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, AllThreadsForTest(), true);
ValidateCuts(cuts, dmat.get(), num_bins);
}
{
HistogramCuts cuts =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), false);
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, AllThreadsForTest(), false);
ValidateCuts(cuts, dmat.get(), num_bins);
}
}
@@ -231,14 +226,14 @@ void TestQuantileWithHessian(bool use_sorted) {
for (auto num_bins : bin_sizes) {
HistogramCuts cuts_hess =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), use_sorted, hessian);
SketchOnDMatrix(dmat.get(), num_bins, AllThreadsForTest(), use_sorted, hessian);
for (size_t i = 0; i < w.size(); ++i) {
dmat->Info().weights_.HostVector()[i] = w[i] * hessian[i];
}
ValidateCuts(cuts_hess, dmat.get(), num_bins);
HistogramCuts cuts_wh =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), use_sorted);
SketchOnDMatrix(dmat.get(), num_bins, AllThreadsForTest(), use_sorted);
ValidateCuts(cuts_wh, dmat.get(), num_bins);
ASSERT_EQ(cuts_hess.Values().size(), cuts_wh.Values().size());
@@ -265,7 +260,7 @@ TEST(HistUtil, DenseCutsExternalMemory) {
dmlc::TemporaryDirectory tmpdir;
auto dmat = GetExternalMemoryDMatrixFromData(x, num_rows, num_columns, tmpdir);
for (auto num_bins : bin_sizes) {
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0));
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, AllThreadsForTest());
ValidateCuts(cuts, dmat.get(), num_bins);
}
}
@@ -285,7 +280,7 @@ TEST(HistUtil, IndexBinBound) {
for (auto max_bin : bin_sizes) {
auto p_fmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
GHistIndexMatrix hmat(p_fmat.get(), max_bin, 0.5, false, common::OmpGetNumThreads(0));
GHistIndexMatrix hmat(p_fmat.get(), max_bin, 0.5, false, AllThreadsForTest());
EXPECT_EQ(hmat.index.Size(), kRows*kCols);
EXPECT_EQ(expected_bin_type_sizes[bin_id++], hmat.index.GetBinTypeSize());
}
@@ -308,7 +303,7 @@ TEST(HistUtil, IndexBinData) {
for (auto max_bin : kBinSizes) {
auto p_fmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
GHistIndexMatrix hmat(p_fmat.get(), max_bin, 0.5, false, common::OmpGetNumThreads(0));
GHistIndexMatrix hmat(p_fmat.get(), max_bin, 0.5, false, AllThreadsForTest());
uint32_t const* offsets = hmat.index.Offset();
EXPECT_EQ(hmat.index.Size(), kRows*kCols);
switch (max_bin) {
@@ -331,9 +326,8 @@ TEST(HistUtil, IndexBinData) {
void TestSketchFromWeights(bool with_group) {
size_t constexpr kRows = 300, kCols = 20, kBins = 256;
size_t constexpr kGroups = 10;
auto m =
RandomDataGenerator{kRows, kCols, 0}.Device(0).GenerateDMatrix();
common::HistogramCuts cuts = SketchOnDMatrix(m.get(), kBins, common::OmpGetNumThreads(0));
auto m = RandomDataGenerator{kRows, kCols, 0}.Device(0).GenerateDMatrix();
common::HistogramCuts cuts = SketchOnDMatrix(m.get(), kBins, AllThreadsForTest());
MetaInfo info;
Context ctx;
@@ -369,7 +363,7 @@ void TestSketchFromWeights(bool with_group) {
if (with_group) {
m->Info().weights_ = decltype(m->Info().weights_)(); // remove weight
HistogramCuts non_weighted = SketchOnDMatrix(m.get(), kBins, common::OmpGetNumThreads(0));
HistogramCuts non_weighted = SketchOnDMatrix(m.get(), kBins, AllThreadsForTest());
for (size_t i = 0; i < cuts.Values().size(); ++i) {
EXPECT_EQ(cuts.Values()[i], non_weighted.Values()[i]);
}
@@ -388,7 +382,7 @@ void TestSketchFromWeights(bool with_group) {
for (size_t i = 0; i < h_weights.size(); ++i) {
h_weights[i] = static_cast<float>(i + 1) / static_cast<float>(kGroups);
}
HistogramCuts weighted = SketchOnDMatrix(m.get(), kBins, common::OmpGetNumThreads(0));
HistogramCuts weighted = SketchOnDMatrix(m.get(), kBins, AllThreadsForTest());
ValidateCuts(weighted, m.get(), kBins);
}
}
@@ -400,10 +394,10 @@ TEST(HistUtil, SketchFromWeights) {
TEST(HistUtil, SketchCategoricalFeatures) {
TestCategoricalSketch(1000, 256, 32, false, [](DMatrix* p_fmat, int32_t num_bins) {
return SketchOnDMatrix(p_fmat, num_bins, common::OmpGetNumThreads(0));
return SketchOnDMatrix(p_fmat, num_bins, AllThreadsForTest());
});
TestCategoricalSketch(1000, 256, 32, true, [](DMatrix* p_fmat, int32_t num_bins) {
return SketchOnDMatrix(p_fmat, num_bins, common::OmpGetNumThreads(0));
return SketchOnDMatrix(p_fmat, num_bins, AllThreadsForTest());
});
}
} // namespace common