a5a58102e5
This PR replaces the original RABIT implementation with a new one, which has already been partially merged into XGBoost. The new one features: - Federated learning for both CPU and GPU. - NCCL. - More data types. - A unified interface for all the underlying implementations. - Improved timeout handling for both tracker and workers. - Exhausted tests with metrics (fixed a couple of bugs along the way). - A reusable tracker for Python and JVM packages.
43 lines
1.2 KiB
C++
43 lines
1.2 KiB
C++
/**
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* Copyright 2020-2024, XGBoost Contributors
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*/
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#ifndef XGBOOST_TESTS_CPP_COMMON_TEST_QUANTILE_H_
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#define XGBOOST_TESTS_CPP_COMMON_TEST_QUANTILE_H_
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#include <algorithm>
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#include <vector>
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#include "../helpers.h"
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namespace xgboost::common {
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template <typename Fn> void RunWithSeedsAndBins(size_t rows, Fn fn) {
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std::vector<int32_t> seeds(2);
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SimpleLCG lcg;
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SimpleRealUniformDistribution<float> dist(3, 1000);
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std::generate(seeds.begin(), seeds.end(), [&](){ return dist(&lcg); });
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std::vector<bst_bin_t> bins(2);
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for (size_t i = 0; i < bins.size() - 1; ++i) {
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bins[i] = i * 35 + 2;
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}
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bins.back() = rows + 160; // provide a bin number greater than rows.
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std::vector<MetaInfo> infos(2);
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auto& h_weights = infos.front().weights_.HostVector();
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h_weights.resize(rows);
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SimpleRealUniformDistribution<float> weight_dist(0, 10);
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std::generate(h_weights.begin(), h_weights.end(), [&]() { return weight_dist(&lcg); });
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for (auto seed : seeds) {
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for (auto n_bin : bins) {
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for (auto const& info : infos) {
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fn(seed, n_bin, info);
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}
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}
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}
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}
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} // namespace xgboost::common
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#endif // XGBOOST_TESTS_CPP_COMMON_TEST_QUANTILE_H_
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