d9a47794a5
* Fix CPU hist init for sparse dataset. * Implement sparse histogram cut. * Allow empty features. * Fix windows build, don't use sparse in distributed environment. * Comments. * Smaller threshold. * Fix windows omp. * Fix msvc lambda capture. * Fix MSVC macro. * Fix MSVC initialization list. * Fix MSVC initialization list x2. * Preserve categorical feature behavior. * Rename matrix to sparse cuts. * Reuse UseGroup. * Check for categorical data when adding cut. Co-Authored-By: Philip Hyunsu Cho <chohyu01@cs.washington.edu> * Sanity check. * Fix comments. * Fix comment.
65 lines
1.8 KiB
C++
65 lines
1.8 KiB
C++
/*!
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* Copyright 2018-2019 by Contributors
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*/
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#include "../helpers.h"
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#include "../../../src/common/host_device_vector.h"
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#include <xgboost/tree_updater.h>
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#include <gtest/gtest.h>
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#include <vector>
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#include <string>
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#include <memory>
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namespace xgboost {
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namespace tree {
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TEST(Updater, Prune) {
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int constexpr kNCols = 16;
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std::vector<std::pair<std::string, std::string>> cfg;
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cfg.emplace_back(std::pair<std::string, std::string>(
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"num_feature", std::to_string(kNCols)));
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cfg.emplace_back(std::pair<std::string, std::string>(
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"min_split_loss", "10"));
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cfg.emplace_back(std::pair<std::string, std::string>(
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"silent", "1"));
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// These data are just place holders.
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HostDeviceVector<GradientPair> gpair =
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{ {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f},
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{0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f} };
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auto dmat = CreateDMatrix(32, 16, 0.4, 3);
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auto lparam = CreateEmptyGenericParam(0, 0);
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// prepare tree
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RegTree tree = RegTree();
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tree.param.InitAllowUnknown(cfg);
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std::vector<RegTree*> trees {&tree};
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// prepare pruner
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std::unique_ptr<TreeUpdater> pruner(TreeUpdater::Create("prune", &lparam));
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pruner->Init(cfg);
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// loss_chg < min_split_loss;
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tree.ExpandNode(0, 0, 0, true, 0.0f, 0.3f, 0.4f, 0.0f, 0.0f);
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pruner->Update(&gpair, dmat->get(), trees);
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ASSERT_EQ(tree.NumExtraNodes(), 0);
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// loss_chg > min_split_loss;
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tree.ExpandNode(0, 0, 0, true, 0.0f, 0.3f, 0.4f, 11.0f, 0.0f);
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pruner->Update(&gpair, dmat->get(), trees);
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ASSERT_EQ(tree.NumExtraNodes(), 2);
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// loss_chg == min_split_loss;
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tree.Stat(0).loss_chg = 10;
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pruner->Update(&gpair, dmat->get(), trees);
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ASSERT_EQ(tree.NumExtraNodes(), 2);
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delete dmat;
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}
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} // namespace tree
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} // namespace xgboost
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