a96039141a
* Use sparse page as singular CSR matrix representation * Simplify dmatrix methods * Reduce statefullness of batch iterators * BREAKING CHANGE: Remove prob_buffer_row parameter. Users are instead recommended to sample their dataset as a preprocessing step before using XGBoost.
44 lines
1.6 KiB
C++
44 lines
1.6 KiB
C++
// Copyright by Contributors
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#include <xgboost/linear_updater.h>
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#include "../helpers.h"
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#include "xgboost/gbm.h"
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typedef std::pair<std::string, std::string> arg;
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TEST(Linear, shotgun) {
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typedef std::pair<std::string, std::string> arg;
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auto mat = CreateDMatrix(10, 10, 0);
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std::vector<bool> enabled(mat->Info().num_col_, true);
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mat->InitColAccess(1 << 16, false);
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auto updater = std::unique_ptr<xgboost::LinearUpdater>(
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xgboost::LinearUpdater::Create("shotgun"));
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updater->Init({{"eta", "1."}});
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xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
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mat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
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xgboost::gbm::GBLinearModel model;
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model.param.num_feature = mat->Info().num_col_;
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model.param.num_output_group = 1;
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model.LazyInitModel();
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updater->Update(&gpair, mat.get(), &model, gpair.Size());
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ASSERT_EQ(model.bias()[0], 5.0f);
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}
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TEST(Linear, coordinate) {
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typedef std::pair<std::string, std::string> arg;
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auto mat = CreateDMatrix(10, 10, 0);
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std::vector<bool> enabled(mat->Info().num_col_, true);
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mat->InitColAccess(1 << 16, false);
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auto updater = std::unique_ptr<xgboost::LinearUpdater>(
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xgboost::LinearUpdater::Create("coord_descent"));
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updater->Init({{"eta", "1."}});
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xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
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mat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
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xgboost::gbm::GBLinearModel model;
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model.param.num_feature = mat->Info().num_col_;
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model.param.num_output_group = 1;
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model.LazyInitModel();
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updater->Update(&gpair, mat.get(), &model, gpair.Size());
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ASSERT_EQ(model.bias()[0], 5.0f);
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} |