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Support categorical data in GPU sketching. (#6137)

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This commit is contained in:
Jiaming Yuan
2020-09-21 13:53:06 +08:00
committed by GitHub
parent c932fb50a1
commit 210c131ce7
6 changed files with 196 additions and 62 deletions
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43
tests/cpp/common/test_hist_util.cu
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@@ -108,7 +108,7 @@ TEST(HistUtil, DeviceSketchDeterminism) {
}
}
TEST(HistUtil, DeviceSketchCategorical) {
TEST(HistUtil, DeviceSketchCategoricalAsNumeric) {
int categorical_sizes[] = {2, 6, 8, 12};
int num_bins = 256;
int sizes[] = {25, 100, 1000};
@@ -122,6 +122,33 @@ TEST(HistUtil, DeviceSketchCategorical) {
}
}
void TestCategoricalSketch(size_t n, size_t num_categories, int32_t num_bins) {
auto x = GenerateRandomCategoricalSingleColumn(n, num_categories);
auto dmat = GetDMatrixFromData(x, n, 1);
dmat->Info().feature_types.HostVector().push_back(FeatureType::kCategorical);
ASSERT_EQ(dmat->Info().feature_types.Size(), 1);
auto cuts = DeviceSketch(0, dmat.get(), num_bins);
std::sort(x.begin(), x.end());
auto n_uniques = std::unique(x.begin(), x.end()) - x.begin();
ASSERT_NE(n_uniques, x.size());
ASSERT_EQ(cuts.TotalBins(), n_uniques);
ASSERT_EQ(n_uniques, num_categories);
auto& values = cuts.cut_values_.HostVector();
ASSERT_TRUE(std::is_sorted(values.cbegin(), values.cend()));
auto is_unique = (std::unique(values.begin(), values.end()) - values.begin()) == n_uniques;
ASSERT_TRUE(is_unique);
x.resize(n_uniques);
for (size_t i = 0; i < n_uniques; ++i) {
ASSERT_EQ(x[i], values[i]);
}
}
TEST(HistUtil, DeviceSketchCategoricalFeatures) {
TestCategoricalSketch(1000, 256, 32);
}
TEST(HistUtil, DeviceSketchMultipleColumns) {
int bin_sizes[] = {2, 16, 256, 512};
int sizes[] = {100, 1000, 1500};
@@ -237,7 +264,8 @@ TEST(HistUtil, DeviceSketchExternalMemoryWithWeights) {
template <typename Adapter>
auto MakeUnweightedCutsForTest(Adapter adapter, int32_t num_bins, float missing, size_t batch_size = 0) {
common::HistogramCuts batched_cuts;
SketchContainer sketch_container(num_bins, adapter.NumColumns(), adapter.NumRows(), 0);
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, num_bins, adapter.NumColumns(), adapter.NumRows(), 0);
MetaInfo info;
AdapterDeviceSketch(adapter.Value(), num_bins, info, std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
@@ -305,7 +333,8 @@ TEST(HistUtil, AdapterSketchSlidingWindowMemory) {
dh::GlobalMemoryLogger().Clear();
ConsoleLogger::Configure({{"verbosity", "3"}});
common::HistogramCuts batched_cuts;
SketchContainer sketch_container(num_bins, num_columns, num_rows, 0);
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, num_bins, num_columns, num_rows, 0);
AdapterDeviceSketch(adapter.Value(), num_bins, info, std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
HistogramCuts cuts;
@@ -332,10 +361,12 @@ TEST(HistUtil, AdapterSketchSlidingWindowWeightedMemory) {
dh::GlobalMemoryLogger().Clear();
ConsoleLogger::Configure({{"verbosity", "3"}});
common::HistogramCuts batched_cuts;
SketchContainer sketch_container(num_bins, num_columns, num_rows, 0);
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, num_bins, num_columns, num_rows, 0);
AdapterDeviceSketch(adapter.Value(), num_bins, info,
std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
HistogramCuts cuts;
sketch_container.MakeCuts(&cuts);
ConsoleLogger::Configure({{"verbosity", "0"}});
@@ -477,9 +508,11 @@ void TestAdapterSketchFromWeights(bool with_group) {
data::CupyAdapter adapter(m);
auto const& batch = adapter.Value();
SketchContainer sketch_container(kBins, kCols, kRows, 0);
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, kBins, kCols, kRows, 0);
AdapterDeviceSketch(adapter.Value(), kBins, info, std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
common::HistogramCuts cuts;
sketch_container.MakeCuts(&cuts);