xgboost/tests/cpp/linear/test_linear.cu
Jiaming Yuan fffb1fca52
Calculate base_score based on input labels for mae. (#8107)
Fit an intercept as base score for abs loss.
2022-09-20 20:53:54 +08:00

36 lines
1.0 KiB
Plaintext

// Copyright by Contributors
#include <xgboost/linear_updater.h>
#include <xgboost/gbm.h>
#include "../helpers.h"
#include "test_json_io.h"
#include "../../../src/gbm/gblinear_model.h"
namespace xgboost {
TEST(Linear, GPUCoordinate) {
size_t constexpr kRows = 10;
size_t constexpr kCols = 10;
auto mat = xgboost::RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
auto ctx = CreateEmptyGenericParam(GPUIDX);
LearnerModelParam mparam{MakeMP(kCols, .5, 1)};
auto updater = std::unique_ptr<xgboost::LinearUpdater>(
xgboost::LinearUpdater::Create("gpu_coord_descent", &ctx));
updater->Configure({{"eta", "1."}});
xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
mat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
xgboost::gbm::GBLinearModel model{&mparam};
model.LazyInitModel();
updater->Update(&gpair, mat.get(), &model, gpair.Size());
ASSERT_EQ(model.Bias()[0], 5.0f);
}
TEST(GPUCoordinate, JsonIO) {
TestUpdaterJsonIO("gpu_coord_descent");
}
} // namespace xgboost