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/**
* Copyright 2022-2024, XGBoost Contributors
*/
#include <gtest/gtest.h>
#include <xgboost/linalg.h>
#include "../../src/common/linalg_op.h"
#include "../../src/tree/fit_stump.h"
#include "../collective/test_worker.h" // for TestDistributedGlobal
#include "../helpers.h"
namespace xgboost::tree {
namespace {
void TestFitStump(Context const *ctx, DataSplitMode split = DataSplitMode::kRow) {
std::size_t constexpr kRows = 16, kTargets = 2;
linalg::Matrix<GradientPair> gpair;
gpair.SetDevice(ctx->Device());
gpair.Reshape(kRows, kTargets);
auto h_gpair = gpair.HostView();
for (std::size_t i = 0; i < kRows; ++i) {
for (std::size_t t = 0; t < kTargets; ++t) {
h_gpair(i, t) = GradientPair{static_cast<float>(i), 1};
}
}
linalg::Vector<float> out;
MetaInfo info;
info.data_split_mode = split;
FitStump(ctx, info, gpair, kTargets, &out);
auto h_out = out.HostView();
for (auto it = linalg::cbegin(h_out); it != linalg::cend(h_out); ++it) {
// sum_hess == kRows
auto n = static_cast<float>(kRows);
auto sum_grad = n * (n - 1) / 2;
ASSERT_EQ(static_cast<float>(-sum_grad / n), *it);
}
}
} // anonymous namespace
TEST(InitEstimation, FitStump) {
Context ctx;
TestFitStump(&ctx);
}
#if defined(XGBOOST_USE_CUDA)
TEST(InitEstimation, GPUFitStump) {
Context ctx;
ctx.UpdateAllowUnknown(Args{{"device", "cuda"}});
TestFitStump(&ctx);
}
#endif // defined(XGBOOST_USE_CUDA)
TEST(InitEstimation, FitStumpColumnSplit) {
Context ctx;
auto constexpr kWorldSize{3};
collective::TestDistributedGlobal(kWorldSize, [&] { TestFitStump(&ctx, DataSplitMode::kCol); });
}
} // namespace xgboost::tree
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