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CPU evaluation for cat data. (#7393)

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* Implementation for one hot based.
* Implementation for partition based. (LightGBM)
This commit is contained in:
Jiaming Yuan
2021-11-06 14:41:35 +08:00
committed by GitHub
parent 6ede12412c
commit d7d1b6e3a6
15 changed files with 540 additions and 166 deletions
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37
tests/cpp/common/test_quantile.cu
View File

@@ -5,6 +5,13 @@
#include "../../../src/common/quantile.cuh"
namespace xgboost {
namespace {
struct IsSorted {
XGBOOST_DEVICE bool operator()(common::SketchEntry const& a, common::SketchEntry const& b) const {
return a.value < b.value;
}
};
}
namespace common {
TEST(GPUQuantile, Basic) {
constexpr size_t kRows = 1000, kCols = 100, kBins = 256;
@@ -52,9 +59,15 @@ void TestSketchUnique(float sparsity) {
ASSERT_EQ(sketch.Data().size(), h_columns_ptr.back());
sketch.Unique();
ASSERT_TRUE(thrust::is_sorted(thrust::device, sketch.Data().data(),
sketch.Data().data() + sketch.Data().size(),
detail::SketchUnique{}));
std::vector<SketchEntry> h_data(sketch.Data().size());
thrust::copy(dh::tcbegin(sketch.Data()), dh::tcend(sketch.Data()), h_data.begin());
for (size_t i = 1; i < h_columns_ptr.size(); ++i) {
auto begin = h_columns_ptr[i - 1];
auto column = common::Span<SketchEntry>(h_data).subspan(begin, h_columns_ptr[i] - begin);
ASSERT_TRUE(std::is_sorted(column.begin(), column.end(), IsSorted{}));
}
});
}
@@ -84,8 +97,7 @@ void TestQuantileElemRank(int32_t device, Span<SketchEntry const> in,
if (with_error) {
ASSERT_GE(in_column[idx].rmin + in_column[idx].rmin * kRtEps,
prev_rmin);
ASSERT_GE(in_column[idx].rmax + in_column[idx].rmin * kRtEps,
prev_rmax);
ASSERT_GE(in_column[idx].rmax + in_column[idx].rmin * kRtEps, prev_rmax);
ASSERT_GE(in_column[idx].rmax + in_column[idx].rmin * kRtEps,
rmin_next);
} else {
@@ -169,7 +181,7 @@ TEST(GPUQuantile, MergeEmpty) {
TEST(GPUQuantile, MergeBasic) {
constexpr size_t kRows = 1000, kCols = 100;
RunWithSeedsAndBins(kRows, [=](int32_t seed, size_t n_bins, MetaInfo const& info) {
RunWithSeedsAndBins(kRows, [=](int32_t seed, size_t n_bins, MetaInfo const &info) {
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_0(ft, n_bins, kCols, kRows, 0);
HostDeviceVector<float> storage_0;
@@ -265,9 +277,16 @@ void TestMergeDuplicated(int32_t n_bins, size_t cols, size_t rows, float frac) {
ASSERT_EQ(h_columns_ptr.back(), sketch_1.Data().size() + size_before_merge);
sketch_0.Unique();
ASSERT_TRUE(thrust::is_sorted(thrust::device, sketch_0.Data().data(),
sketch_0.Data().data() + sketch_0.Data().size(),
detail::SketchUnique{}));
columns_ptr = sketch_0.ColumnsPtr();
dh::CopyDeviceSpanToVector(&h_columns_ptr, columns_ptr);
std::vector<SketchEntry> h_data(sketch_0.Data().size());
dh::CopyDeviceSpanToVector(&h_data, sketch_0.Data());
for (size_t i = 1; i < h_columns_ptr.size(); ++i) {
auto begin = h_columns_ptr[i - 1];
auto column = Span<SketchEntry> {h_data}.subspan(begin, h_columns_ptr[i] - begin);
ASSERT_TRUE(std::is_sorted(column.begin(), column.end(), IsSorted{}));
}
}
TEST(GPUQuantile, MergeDuplicated) {

4
tests/cpp/common/test_quantile.h
View File

@@ -48,7 +48,9 @@ template <typename Fn> void RunWithSeedsAndBins(size_t rows, Fn fn) {
std::vector<MetaInfo> infos(2);
auto& h_weights = infos.front().weights_.HostVector();
h_weights.resize(rows);
std::generate(h_weights.begin(), h_weights.end(), [&]() { return dist(&lcg); });
SimpleRealUniformDistribution<float> weight_dist(0, 10);
std::generate(h_weights.begin(), h_weights.end(), [&]() { return weight_dist(&lcg); });
for (auto seed : seeds) {
for (auto n_bin : bins) {