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/**
* Copyright 2023, XGBoost contributors
*/
#include <gtest/gtest.h>
#include <xgboost/context.h> // for DeviceOrd
#include <xgboost/data.h> // for DataSplitMode
#include <algorithm> // for min
#include <cstdint> // for int32_t
#include <functional> // for function
#include <string> // for string
#include <thread> // for thread
#include "../collective/test_worker.h" // for TestDistributedGlobal
#include "test_auc.h"
#include "test_elementwise_metric.h"
#include "test_multiclass_metric.h"
#include "test_rank_metric.h"
#include "test_survival_metric.h"
#if defined(XGBOOST_USE_FEDERATED)
#include "../plugin/federated/test_worker.h" // for TestFederatedGlobal
#endif // defined(XGBOOST_USE_FEDERATED)
namespace xgboost::metric {
namespace {
using Verifier = std::function<void(DataSplitMode, DeviceOrd)>;
struct Param {
bool is_dist; // is distributed
bool is_fed; // is federated learning
DataSplitMode split; // how to split data
Verifier v; // test function
std::string name; // metric name
DeviceOrd device; // device to run
};
class TestDistributedMetric : public ::testing::TestWithParam<Param> {
protected:
template <typename Fn>
void Run(bool is_dist, bool is_fed, DataSplitMode split_mode, Fn fn, DeviceOrd device) {
if (!is_dist) {
fn(split_mode, device);
return;
}
std::int32_t n_workers{0};
if (device.IsCUDA()) {
n_workers = curt::AllVisibleGPUs();
} else {
n_workers = std::min(static_cast<std::int32_t>(std::thread::hardware_concurrency()), 3);
}
auto fn1 = [&]() {
auto r = collective::GetRank();
if (device.IsCPU()) {
fn(split_mode, DeviceOrd::CPU());
} else {
fn(split_mode, DeviceOrd::CUDA(r));
}
};
if (is_fed) {
#if defined(XGBOOST_USE_FEDERATED)
collective::TestFederatedGlobal(n_workers, fn1);
#endif // defined(XGBOOST_USE_FEDERATED)
} else {
collective::TestDistributedGlobal(n_workers, fn1);
}
}
};
} // anonymous namespace
TEST_P(TestDistributedMetric, BinaryAUCRowSplit) {
auto p = GetParam();
this->Run(p.is_dist, p.is_fed, p.split, p.v, p.device);
}
constexpr bool UseNCCL() {
#if defined(XGBOOST_USE_NCCL)
return true;
#else
return false;
#endif // defined(XGBOOST_USE_NCCL)
}
constexpr bool UseCUDA() {
#if defined(XGBOOST_USE_CUDA)
return true;
#else
return false;
#endif // defined(XGBOOST_USE_CUDA)
}
constexpr bool UseFederated() {
#if defined(XGBOOST_USE_FEDERATED)
return true;
#else
return false;
#endif
}
auto MakeParamsForTest() {
std::vector<Param> cases;
auto push = [&](std::string name, auto fn) {
for (bool is_federated : {false, true}) {
for (DataSplitMode m : {DataSplitMode::kCol, DataSplitMode::kRow}) {
for (auto d : {DeviceOrd::CPU(), DeviceOrd::CUDA(0)}) {
if (!is_federated && !UseNCCL() && d.IsCUDA()) {
// Federated doesn't use nccl.
continue;
}
if (!UseCUDA() && d.IsCUDA()) {
// skip CUDA tests
continue;
}
if (!UseFederated() && is_federated) {
// skip GRPC tests
continue;
}
auto p = Param{true, is_federated, m, fn, name, d};
cases.push_back(p);
if (!is_federated) {
// Add a local test.
p.is_dist = false;
cases.push_back(p);
}
}
}
}
};
#define REFLECT_NAME(name) push(#name, Verify##name)
// AUC
REFLECT_NAME(BinaryAUC);
REFLECT_NAME(MultiClassAUC);
REFLECT_NAME(RankingAUC);
REFLECT_NAME(PRAUC);
REFLECT_NAME(MultiClassPRAUC);
REFLECT_NAME(RankingPRAUC);
// Elementwise
REFLECT_NAME(RMSE);
REFLECT_NAME(RMSLE);
REFLECT_NAME(MAE);
REFLECT_NAME(MAPE);
REFLECT_NAME(MPHE);
REFLECT_NAME(LogLoss);
REFLECT_NAME(Error);
REFLECT_NAME(PoissonNegLogLik);
REFLECT_NAME(MultiRMSE);
REFLECT_NAME(Quantile);
// Multi-Class
REFLECT_NAME(MultiClassError);
REFLECT_NAME(MultiClassLogLoss);
// Ranking
REFLECT_NAME(Precision);
REFLECT_NAME(NDCG);
REFLECT_NAME(MAP);
REFLECT_NAME(NDCGExpGain);
// AFT
using namespace xgboost::common; // NOLINT
REFLECT_NAME(AFTNegLogLik);
REFLECT_NAME(IntervalRegressionAccuracy);
#undef REFLECT_NAME
return cases;
}
INSTANTIATE_TEST_SUITE_P(
DistributedMetric, TestDistributedMetric, ::testing::ValuesIn(MakeParamsForTest()),
[](const ::testing::TestParamInfo<TestDistributedMetric::ParamType>& info) {
std::string result;
if (info.param.is_dist) {
result += "Dist_";
}
if (info.param.is_fed) {
result += "Federated_";
}
if (info.param.split == DataSplitMode::kRow) {
result += "RowSplit";
} else {
result += "ColSplit";
}
result += "_";
result += info.param.device.IsCPU() ? "CPU" : "CUDA";
result += "_";
result += info.param.name;
return result;
});
} // namespace xgboost::metric
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