e089e16e3d
* Pass pointer to model parameters. This PR de-duplicates most of the model parameters except the one in `tree_model.h`. One difficulty is `base_score` is a model property but can be changed at runtime by objective function. Hence when performing model IO, we need to save the one provided by users, instead of the one transformed by objective. Here we created an immutable version of `LearnerModelParam` that represents the value of model parameter after configuration.
76 lines
2.1 KiB
C++
76 lines
2.1 KiB
C++
/*!
|
|
* Copyright 2018-2019 by Contributors
|
|
*/
|
|
#include <xgboost/linear_updater.h>
|
|
#include <xgboost/gbm.h>
|
|
|
|
#include "../helpers.h"
|
|
|
|
#include "../../../src/gbm/gblinear_model.h"
|
|
|
|
namespace xgboost {
|
|
|
|
TEST(Linear, shotgun) {
|
|
size_t constexpr kRows = 10;
|
|
size_t constexpr kCols = 10;
|
|
|
|
auto pp_dmat = xgboost::CreateDMatrix(kRows, kCols, 0);
|
|
auto p_fmat {*pp_dmat};
|
|
|
|
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
|
|
LearnerModelParam mparam;
|
|
mparam.num_feature = kCols;
|
|
mparam.num_output_group = 1;
|
|
mparam.base_score = 0.5;
|
|
|
|
{
|
|
auto updater = std::unique_ptr<xgboost::LinearUpdater>(
|
|
xgboost::LinearUpdater::Create("shotgun", &lparam));
|
|
updater->Configure({{"eta", "1."}});
|
|
xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
|
|
p_fmat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
|
|
xgboost::gbm::GBLinearModel model{&mparam};
|
|
model.LazyInitModel();
|
|
updater->Update(&gpair, p_fmat.get(), &model, gpair.Size());
|
|
|
|
ASSERT_EQ(model.bias()[0], 5.0f);
|
|
|
|
}
|
|
{
|
|
auto updater = std::unique_ptr<xgboost::LinearUpdater>(
|
|
xgboost::LinearUpdater::Create("shotgun", &lparam));
|
|
EXPECT_ANY_THROW(updater->Configure({{"feature_selector", "random"}}));
|
|
}
|
|
|
|
delete pp_dmat;
|
|
}
|
|
|
|
TEST(Linear, coordinate) {
|
|
size_t constexpr kRows = 10;
|
|
size_t constexpr kCols = 10;
|
|
|
|
auto pp_dmat = xgboost::CreateDMatrix(kRows, kCols, 0);
|
|
auto p_fmat {*pp_dmat};
|
|
|
|
auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
|
|
LearnerModelParam mparam;
|
|
mparam.num_feature = kCols;
|
|
mparam.num_output_group = 1;
|
|
mparam.base_score = 0.5;
|
|
|
|
auto updater = std::unique_ptr<xgboost::LinearUpdater>(
|
|
xgboost::LinearUpdater::Create("coord_descent", &lparam));
|
|
updater->Configure({{"eta", "1."}});
|
|
xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
|
|
p_fmat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
|
|
xgboost::gbm::GBLinearModel model{&mparam};
|
|
model.LazyInitModel();
|
|
updater->Update(&gpair, p_fmat.get(), &model, gpair.Size());
|
|
|
|
ASSERT_EQ(model.bias()[0], 5.0f);
|
|
|
|
delete pp_dmat;
|
|
}
|
|
|
|
} // namespace xgboost
|