60 lines
1.5 KiB
C++
60 lines
1.5 KiB
C++
#include <xgboost/tree_updater.h>
|
|
#include <xgboost/tree_model.h>
|
|
#include <gtest/gtest.h>
|
|
|
|
#include "../helpers.h"
|
|
|
|
namespace xgboost {
|
|
class UpdaterTreeStatTest : public ::testing::Test {
|
|
protected:
|
|
std::shared_ptr<DMatrix> p_dmat_;
|
|
HostDeviceVector<GradientPair> gpairs_;
|
|
size_t constexpr static kRows = 10;
|
|
size_t constexpr static kCols = 10;
|
|
|
|
protected:
|
|
void SetUp() override {
|
|
p_dmat_ = RandomDataGenerator(kRows, kCols, .5f).GenerateDMatrix(true);
|
|
auto g = GenerateRandomGradients(kRows);
|
|
gpairs_.Resize(kRows);
|
|
gpairs_.Copy(g);
|
|
}
|
|
|
|
void RunTest(std::string updater) {
|
|
auto tparam = CreateEmptyGenericParam(0);
|
|
auto up = std::unique_ptr<TreeUpdater>{
|
|
TreeUpdater::Create(updater, &tparam, ObjInfo{ObjInfo::kRegression})};
|
|
up->Configure(Args{});
|
|
RegTree tree;
|
|
tree.param.num_feature = kCols;
|
|
up->Update(&gpairs_, p_dmat_.get(), {&tree});
|
|
|
|
tree.WalkTree([&tree](bst_node_t nidx) {
|
|
if (tree[nidx].IsLeaf()) {
|
|
// 1.0 is the default `min_child_weight`.
|
|
CHECK_GE(tree.Stat(nidx).sum_hess, 1.0);
|
|
}
|
|
return true;
|
|
});
|
|
}
|
|
};
|
|
|
|
#if defined(XGBOOST_USE_CUDA)
|
|
TEST_F(UpdaterTreeStatTest, GpuHist) {
|
|
this->RunTest("grow_gpu_hist");
|
|
}
|
|
#endif // defined(XGBOOST_USE_CUDA)
|
|
|
|
TEST_F(UpdaterTreeStatTest, Hist) {
|
|
this->RunTest("grow_quantile_histmaker");
|
|
}
|
|
|
|
TEST_F(UpdaterTreeStatTest, Exact) {
|
|
this->RunTest("grow_colmaker");
|
|
}
|
|
|
|
TEST_F(UpdaterTreeStatTest, Approx) {
|
|
this->RunTest("grow_histmaker");
|
|
}
|
|
} // namespace xgboost
|