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.
27 lines
942 B
Plaintext
27 lines
942 B
Plaintext
/*!
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* Copyright (c) by Contributors 2020
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*/
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#include <gtest/gtest.h>
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#include "test_survival_metric.h"
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#include "xgboost/metric.h"
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/** Tests for Survival metrics that should run both on CPU and GPU **/
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namespace xgboost::common {
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// Test configuration of AFT metric
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TEST(AFTNegLogLikMetric, DeclareUnifiedTest(Configuration)) {
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auto ctx = MakeCUDACtx(GPUIDX);
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std::unique_ptr<Metric> metric(Metric::Create("aft-nloglik", &ctx));
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metric->Configure({{"aft_loss_distribution", "normal"}, {"aft_loss_distribution_scale", "10"}});
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// Configuration round-trip test
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Json j_obj{ Object() };
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metric->SaveConfig(&j_obj);
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auto aft_param_json = j_obj["aft_loss_param"];
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EXPECT_EQ(get<String>(aft_param_json["aft_loss_distribution"]), "normal");
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EXPECT_EQ(get<String>(aft_param_json["aft_loss_distribution_scale"]), "10");
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CheckDeterministicMetricElementWise(StringView{"aft-nloglik"}, GPUIDX);
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}
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} // namespace xgboost::common
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