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Remove omp_get_max_threads in data. (#7588)

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This commit is contained in:
Jiaming Yuan
2022-01-24 02:44:07 +08:00
committed by GitHub
parent f84291c1e1
commit 5817840858
18 changed files with 97 additions and 92 deletions
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42
tests/cpp/common/test_hist_util.cc
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@@ -1,5 +1,5 @@
/*!
* Copyright 2019-2021 by XGBoost Contributors
* Copyright 2019-2022 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <vector>
@@ -188,7 +188,7 @@ 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);
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0));
auto cuts_from_sketch = cuts.Values();
EXPECT_LT(cuts.MinValues()[0], x_sorted.front());
EXPECT_GT(cuts_from_sketch.front(), x_sorted.front());
@@ -207,7 +207,7 @@ TEST(HistUtil, DenseCutsAccuracyTest) {
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);
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0));
ValidateCuts(cuts, dmat.get(), num_bins);
}
}
@@ -224,11 +224,13 @@ TEST(HistUtil, DenseCutsAccuracyTestWeights) {
dmat->Info().weights_.HostVector() = w;
for (auto num_bins : bin_sizes) {
{
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, true);
HistogramCuts cuts =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), true);
ValidateCuts(cuts, dmat.get(), num_bins);
}
{
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, false);
HistogramCuts cuts =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), false);
ValidateCuts(cuts, dmat.get(), num_bins);
}
}
@@ -249,13 +251,15 @@ void TestQuantileWithHessian(bool use_sorted) {
dmat->Info().weights_.HostVector() = w;
for (auto num_bins : bin_sizes) {
HistogramCuts cuts_hess = SketchOnDMatrix(dmat.get(), num_bins, use_sorted, hessian);
HistogramCuts cuts_hess =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), 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, use_sorted);
HistogramCuts cuts_wh =
SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0), use_sorted);
ValidateCuts(cuts_wh, dmat.get(), num_bins);
ASSERT_EQ(cuts_hess.Values().size(), cuts_wh.Values().size());
@@ -283,7 +287,7 @@ TEST(HistUtil, DenseCutsExternalMemory) {
auto dmat =
GetExternalMemoryDMatrixFromData(x, num_rows, num_columns, 50, tmpdir);
for (auto num_bins : bin_sizes) {
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins);
HistogramCuts cuts = SketchOnDMatrix(dmat.get(), num_bins, common::OmpGetNumThreads(0));
ValidateCuts(cuts, dmat.get(), num_bins);
}
}
@@ -303,7 +307,7 @@ TEST(HistUtil, IndexBinBound) {
for (auto max_bin : bin_sizes) {
auto p_fmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
GHistIndexMatrix hmat(p_fmat.get(), max_bin, false);
GHistIndexMatrix hmat(p_fmat.get(), max_bin, false, common::OmpGetNumThreads(0));
EXPECT_EQ(hmat.index.Size(), kRows*kCols);
EXPECT_EQ(expected_bin_type_sizes[bin_id++], hmat.index.GetBinTypeSize());
}
@@ -326,7 +330,7 @@ TEST(HistUtil, IndexBinData) {
for (auto max_bin : kBinSizes) {
auto p_fmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
GHistIndexMatrix hmat(p_fmat.get(), max_bin, false);
GHistIndexMatrix hmat(p_fmat.get(), max_bin, false, common::OmpGetNumThreads(0));
uint32_t* offsets = hmat.index.Offset();
EXPECT_EQ(hmat.index.Size(), kRows*kCols);
switch (max_bin) {
@@ -351,7 +355,7 @@ void TestSketchFromWeights(bool with_group) {
size_t constexpr kGroups = 10;
auto m =
RandomDataGenerator{kRows, kCols, 0}.Device(0).GenerateDMatrix();
common::HistogramCuts cuts = SketchOnDMatrix(m.get(), kBins);
common::HistogramCuts cuts = SketchOnDMatrix(m.get(), kBins, common::OmpGetNumThreads(0));
MetaInfo info;
auto& h_weights = info.weights_.HostVector();
@@ -385,7 +389,7 @@ void TestSketchFromWeights(bool with_group) {
ValidateCuts(cuts, m.get(), kBins);
if (with_group) {
HistogramCuts non_weighted = SketchOnDMatrix(m.get(), kBins);
HistogramCuts non_weighted = SketchOnDMatrix(m.get(), kBins, common::OmpGetNumThreads(0));
for (size_t i = 0; i < cuts.Values().size(); ++i) {
EXPECT_EQ(cuts.Values()[i], non_weighted.Values()[i]);
}
@@ -404,14 +408,12 @@ TEST(HistUtil, SketchFromWeights) {
}
TEST(HistUtil, SketchCategoricalFeatures) {
TestCategoricalSketch(1000, 256, 32, false,
[](DMatrix *p_fmat, int32_t num_bins) {
return SketchOnDMatrix(p_fmat, num_bins);
});
TestCategoricalSketch(1000, 256, 32, true,
[](DMatrix *p_fmat, int32_t num_bins) {
return SketchOnDMatrix(p_fmat, num_bins);
});
TestCategoricalSketch(1000, 256, 32, false, [](DMatrix* p_fmat, int32_t num_bins) {
return SketchOnDMatrix(p_fmat, num_bins, common::OmpGetNumThreads(0));
});
TestCategoricalSketch(1000, 256, 32, true, [](DMatrix* p_fmat, int32_t num_bins) {
return SketchOnDMatrix(p_fmat, num_bins, common::OmpGetNumThreads(0));
});
}
} // namespace common
} // namespace xgboost