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/**
* Copyright 2022-2023 XGBoost contributors
*/
#include <gtest/gtest.h>
#include "../../../src/data/adapter.h"
#include "../../../src/data/simple_dmatrix.h"
#include "../helpers.h"
#include "xgboost/context.h"
namespace xgboost {
namespace {
class DMatrixForTest : public data::SimpleDMatrix {
size_t n_regen_{0};
public:
using SimpleDMatrix::SimpleDMatrix;
BatchSet<GHistIndexMatrix> GetGradientIndex(Context const* ctx,
const BatchParam& param) override {
auto backup = this->gradient_index_;
auto iter = SimpleDMatrix::GetGradientIndex(ctx, param);
n_regen_ += (backup != this->gradient_index_);
return iter;
}
BatchSet<EllpackPage> GetEllpackBatches(Context const* ctx, const BatchParam& param) override {
auto backup = this->ellpack_page_;
auto iter = SimpleDMatrix::GetEllpackBatches(ctx, param);
n_regen_ += (backup != this->ellpack_page_);
return iter;
}
auto NumRegen() const { return n_regen_; }
void Reset() {
this->gradient_index_.reset();
this->ellpack_page_.reset();
n_regen_ = 0;
}
};
/**
* \brief Test for whether the gradient index is correctly regenerated.
*/
class RegenTest : public ::testing::Test {
protected:
std::shared_ptr<DMatrix> p_fmat_;
void SetUp() override {
size_t constexpr kRows = 256, kCols = 10;
HostDeviceVector<float> storage;
auto dense = RandomDataGenerator{kRows, kCols, 0.5}.GenerateArrayInterface(&storage);
auto adapter = data::ArrayAdapter(StringView{dense});
p_fmat_ = std::shared_ptr<DMatrix>(
new DMatrixForTest{&adapter, std::numeric_limits<float>::quiet_NaN(), AllThreadsForTest()});
p_fmat_->Info().labels.Reshape(256, 1);
auto labels = p_fmat_->Info().labels.Data();
RandomDataGenerator{kRows, 1, 0}.GenerateDense(labels);
}
auto constexpr Iter() const { return 4; }
template <typename Page>
size_t TestTreeMethod(Context const* ctx, std::string tree_method, std::string obj,
bool reset = true) const {
auto learner = std::unique_ptr<Learner>{Learner::Create({p_fmat_})};
learner->SetParam("device", ctx->DeviceName());
learner->SetParam("tree_method", tree_method);
learner->SetParam("objective", obj);
learner->Configure();
for (auto i = 0; i < Iter(); ++i) {
learner->UpdateOneIter(i, p_fmat_);
}
auto for_test = dynamic_cast<DMatrixForTest*>(p_fmat_.get());
CHECK(for_test);
auto backup = for_test->NumRegen();
for_test->GetBatches<Page>(p_fmat_->Ctx(), BatchParam{});
CHECK_EQ(for_test->NumRegen(), backup);
if (reset) {
for_test->Reset();
}
return backup;
}
};
} // anonymous namespace
TEST_F(RegenTest, Approx) {
Context ctx;
auto n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "approx", "reg:squarederror");
ASSERT_EQ(n, 1);
n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "approx", "reg:logistic");
ASSERT_EQ(n, this->Iter());
}
TEST_F(RegenTest, Hist) {
Context ctx;
auto n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "hist", "reg:squarederror");
ASSERT_EQ(n, 1);
n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "hist", "reg:logistic");
ASSERT_EQ(n, 1);
}
TEST_F(RegenTest, Mixed) {
Context ctx;
auto n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "hist", "reg:squarederror", false);
ASSERT_EQ(n, 1);
n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "approx", "reg:logistic", true);
ASSERT_EQ(n, this->Iter() + 1);
n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "approx", "reg:logistic", false);
ASSERT_EQ(n, this->Iter());
n = this->TestTreeMethod<GHistIndexMatrix>(&ctx, "hist", "reg:squarederror", true);
ASSERT_EQ(n, this->Iter() + 1);
}
#if defined(XGBOOST_USE_CUDA)
TEST_F(RegenTest, GpuApprox) {
auto ctx = MakeCUDACtx(0);
auto n = this->TestTreeMethod<EllpackPage>(&ctx, "approx", "reg:squarederror", true);
ASSERT_EQ(n, 1);
n = this->TestTreeMethod<EllpackPage>(&ctx, "approx", "reg:logistic", false);
ASSERT_EQ(n, this->Iter());
n = this->TestTreeMethod<EllpackPage>(&ctx, "approx", "reg:logistic", true);
ASSERT_EQ(n, this->Iter() * 2);
}
TEST_F(RegenTest, GpuHist) {
auto ctx = MakeCUDACtx(0);
auto n = this->TestTreeMethod<EllpackPage>(&ctx, "hist", "reg:squarederror", true);
ASSERT_EQ(n, 1);
n = this->TestTreeMethod<EllpackPage>(&ctx, "hist", "reg:logistic", false);
ASSERT_EQ(n, 1);
{
Context ctx;
n = this->TestTreeMethod<EllpackPage>(&ctx, "hist", "reg:logistic");
ASSERT_EQ(n, 2);
}
}
TEST_F(RegenTest, GpuMixed) {
auto ctx = MakeCUDACtx(0);
auto n = this->TestTreeMethod<EllpackPage>(&ctx, "hist", "reg:squarederror", false);
ASSERT_EQ(n, 1);
n = this->TestTreeMethod<EllpackPage>(&ctx, "approx", "reg:logistic", true);
ASSERT_EQ(n, this->Iter() + 1);
n = this->TestTreeMethod<EllpackPage>(&ctx, "approx", "reg:logistic", false);
ASSERT_EQ(n, this->Iter());
n = this->TestTreeMethod<EllpackPage>(&ctx, "hist", "reg:squarederror", true);
ASSERT_EQ(n, this->Iter() + 1);
}
#endif // defined(XGBOOST_USE_CUDA)
} // namespace xgboost
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