Function MapBuildPlainFold

catboost/private/libs/distributed/master.cpp:180–218

}

void MapBuildPlainFold(TLearnContext* ctx) {
    Y_ASSERT(ctx->Params.SystemOptions->IsMaster());

    NJson::TJsonValue jsonParams;
    ctx->Params.Save(&jsonParams);
    const auto& metricOptions = ctx->Params.MetricOptions;
    if (metricOptions->EvalMetric.NotSet()) { // workaround for NotSet + Save + Load = DefaultValue
        if (ctx->Params.LossFunctionDescription->GetLossFunction() !=
            metricOptions->EvalMetric->GetLossFunction()) {
            // skip only if default metric differs from loss function

            const auto& evalMetric = metricOptions->EvalMetric;
            jsonParams[metricOptions.GetName()][evalMetric.GetName()][evalMetric->LossParams.GetName()]
                .InsertValue("hints", "skip_train~true");
        }
    }
    if (ctx->Params.DataProcessingOptions->AutoClassWeights.Get() != EAutoClassWeightsType::None) {
        // avoid issues with validation after deserialization on workers
        jsonParams["data_processing_options"].EraseValue("auto_class_weights");
    }

    const auto& plainFold = ctx->LearnProgress->Folds[0];
    Y_ASSERT(plainFold.PermutationBlockSize == plainFold.GetLearnSampleCount() ||
        plainFold.PermutationBlockSize == 1);
    const int workerCount = TMasterEnvironment::GetRef().RootEnvironment->GetSlaveCount();
    ApplyMapper<TPlainFoldBuilder>(
        workerCount,
        TMasterEnvironment::GetRef().SharedTrainData,
        TPlainFoldBuilderParams({
            ctx->CtrsHelper.GetTargetClassifiers(),
            ctx->LearnProgress->Rand.GenRand(),
            ctx->LearnProgress->ApproxDimension,
            WriteTJsonValue(jsonParams),
            plainFold.GetLearnSampleCount(),
            plainFold.GetSumWeight(),
            ctx->LearnProgress->HessianType
        })
    );
}

void MapRestoreApproxFromTreeStruct(TMaybe<int> bestIteration, TLearnContext* ctx) {
    Y_ASSERT(ctx->Params.SystemOptions->IsMaster());