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/**
* Copyright 2018-2023 by XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <xgboost/data.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/learner.h>
#include <xgboost/tree_updater.h>
#include <memory>
#include <string>
#include <vector>
#include "../../../src/tree/param.h" // for TrainParam
#include "../helpers.h"
namespace xgboost::tree {
TEST(Updater, Prune) {
int constexpr kCols = 16;
std::vector<std::pair<std::string, std::string>> cfg;
cfg.emplace_back("num_feature", std::to_string(kCols));
cfg.emplace_back("min_split_loss", "10");
Context ctx;
// These data are just place holders.
linalg::Matrix<GradientPair> gpair
{{ {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f},
{0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f} }, {8, 1}, ctx.Device()};
std::shared_ptr<DMatrix> p_dmat{RandomDataGenerator{32, 10, 0}.GenerateDMatrix()};
// prepare tree
RegTree tree = RegTree{1u, kCols};
std::vector<RegTree*> trees {&tree};
// prepare pruner
TrainParam param;
param.UpdateAllowUnknown(cfg);
ObjInfo task{ObjInfo::kRegression};
std::unique_ptr<TreeUpdater> pruner(TreeUpdater::Create("prune", &ctx, &task));
// loss_chg < min_split_loss;
std::vector<HostDeviceVector<bst_node_t>> position(trees.size());
tree.ExpandNode(0, 0, 0, true, 0.0f, 0.3f, 0.4f, 0.0f, 0.0f,
/*left_sum=*/0.0f, /*right_sum=*/0.0f);
pruner->Update(¶m, &gpair, p_dmat.get(), position, trees);
ASSERT_EQ(tree.NumExtraNodes(), 0);
// loss_chg > min_split_loss;
tree.ExpandNode(0, 0, 0, true, 0.0f, 0.3f, 0.4f, 11.0f, 0.0f,
/*left_sum=*/0.0f, /*right_sum=*/0.0f);
pruner->Update(¶m, &gpair, p_dmat.get(), position, trees);
ASSERT_EQ(tree.NumExtraNodes(), 2);
// loss_chg == min_split_loss;
tree.Stat(0).loss_chg = 10;
pruner->Update(¶m, &gpair, p_dmat.get(), position, trees);
ASSERT_EQ(tree.NumExtraNodes(), 2);
// Test depth
// loss_chg > min_split_loss
tree.ExpandNode(tree[0].LeftChild(),
0, 0.5f, true, 0.3, 0.4, 0.5,
/*loss_chg=*/18.0f, 0.0f,
/*left_sum=*/0.0f, /*right_sum=*/0.0f);
tree.ExpandNode(tree[0].RightChild(),
0, 0.5f, true, 0.3, 0.4, 0.5,
/*loss_chg=*/19.0f, 0.0f,
/*left_sum=*/0.0f, /*right_sum=*/0.0f);
cfg.emplace_back("max_depth", "1");
param.UpdateAllowUnknown(cfg);
pruner->Update(¶m, &gpair, p_dmat.get(), position, trees);
ASSERT_EQ(tree.NumExtraNodes(), 2);
tree.ExpandNode(tree[0].LeftChild(),
0, 0.5f, true, 0.3, 0.4, 0.5,
/*loss_chg=*/18.0f, 0.0f,
/*left_sum=*/0.0f, /*right_sum=*/0.0f);
cfg.emplace_back("min_split_loss", "0");
param.UpdateAllowUnknown(cfg);
pruner->Update(¶m, &gpair, p_dmat.get(), position, trees);
ASSERT_EQ(tree.NumExtraNodes(), 2);
}
} // namespace xgboost::tree
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