50 lines
1.3 KiB
C++
50 lines
1.3 KiB
C++
/**
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* Copyright 2022 by XGBoost Contributors
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*/
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#include <gtest/gtest.h>
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#include <xgboost/linalg.h>
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#include "../../src/common/linalg_op.h"
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#include "../../src/tree/fit_stump.h"
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namespace xgboost {
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namespace tree {
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namespace {
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void TestFitStump(Context const *ctx) {
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std::size_t constexpr kRows = 16, kTargets = 2;
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HostDeviceVector<GradientPair> gpair;
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auto &h_gpair = gpair.HostVector();
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h_gpair.resize(kRows * kTargets);
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for (std::size_t i = 0; i < kRows; ++i) {
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for (std::size_t t = 0; t < kTargets; ++t) {
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h_gpair.at(i * kTargets + t) = GradientPair{static_cast<float>(i), 1};
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}
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}
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linalg::Vector<float> out;
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MetaInfo info;
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FitStump(ctx, info, gpair, kTargets, &out);
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auto h_out = out.HostView();
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for (auto it = linalg::cbegin(h_out); it != linalg::cend(h_out); ++it) {
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// sum_hess == kRows
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auto n = static_cast<float>(kRows);
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auto sum_grad = n * (n - 1) / 2;
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ASSERT_EQ(static_cast<float>(-sum_grad / n), *it);
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}
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}
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} // anonymous namespace
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TEST(InitEstimation, FitStump) {
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Context ctx;
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TestFitStump(&ctx);
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}
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#if defined(XGBOOST_USE_CUDA)
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TEST(InitEstimation, GPUFitStump) {
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Context ctx;
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ctx.UpdateAllowUnknown(Args{{"gpu_id", "0"}});
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TestFitStump(&ctx);
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}
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#endif // defined(XGBOOST_USE_CUDA)
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} // namespace tree
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} // namespace xgboost
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