Function EvalMetrics

catboost/python-package/catboost/helpers.cpp:74–126

TVector<TVector<double>> EvalMetrics(
    const TFullModel& model,
    const NCB::TDataProvider& srcData,
    const TVector<TString>& metricsDescription,
    int begin,
    int end,
    int evalPeriod,
    int threadCount,
    const TString& resultDir,
    const TString& tmpDir
) {
    NPar::TLocalExecutor executor;
    executor.RunAdditionalThreads(threadCount - 1);

    TRestorableFastRng64 rand(0);

    auto metricLossDescriptions = CreateMetricLossDescriptions(metricsDescription);
    auto metrics = CreateMetrics(metricLossDescriptions, model.GetDimensionsCount());
    TMetricsPlotCalcer plotCalcer = CreateMetricCalcer(
        model,
        begin,
        end,
        evalPeriod,
        /*processedIterationsStep=*/50,
        tmpDir,
        metrics,
        &executor
    );

    auto processedDataProvider = NCB::CreateModelCompatibleProcessedDataProvider(
        srcData,
        metricLossDescriptions,
        model,
        NCB::GetMonopolisticFreeCpuRam(),
        &rand,
        &executor
    );

    if (plotCalcer.HasAdditiveMetric()) {
        plotCalcer.ProceedDataSetForAdditiveMetrics(processedDataProvider);
    }
    if (plotCalcer.HasNonAdditiveMetric()) {
        while (!plotCalcer.AreAllIterationsProcessed()) {
            plotCalcer.ProceedDataSetForNonAdditiveMetrics(processedDataProvider);
            plotCalcer.FinishProceedDataSetForNonAdditiveMetrics();
        }
    }

    TVector<TVector<double>> metricsScore = plotCalcer.GetMetricsScore();

    plotCalcer.SaveResult(resultDir, /*metricsFile=*/"", /*saveMetrics*/ false, /*saveStats=*/true).ClearTempFiles();
    return metricsScore;
}

TVector<TString> GetMetricNames(const TFullModel& model, const TVector<TString>& metricsDescription) {
    auto metrics = CreateMetricsFromDescription(metricsDescription, model.GetDimensionsCount());