Function CalcGeneric

catboost/libs/model/cpu/formula_evaluator.cpp:10–81

        template <typename TFloatFeatureAccessor, typename TCatFeatureAccessor,
                  typename TTextFeatureAccessor, typename TEmbeddingFeatureAccessor>
        inline void CalcGeneric(
            const TModelTrees& trees,
            const TModelTrees::TForApplyData& applyData,
            const TIntrusivePtr<ICtrProvider>& ctrProvider,
            const TIntrusivePtr<TTextProcessingCollection>& textProcessingCollection,
            const TIntrusivePtr<TEmbeddingProcessingCollection>& embeddingProcessingCollection,
            TFloatFeatureAccessor floatFeatureAccessor,
            TCatFeatureAccessor catFeaturesAccessor,
            TTextFeatureAccessor textFeatureAccessor,
            TEmbeddingFeatureAccessor embeddingFeatureAccessor,
            size_t docCount,
            size_t treeStart,
            size_t treeEnd,
            EPredictionType predictionType,
            TArrayRef<double> results,
            const NCB::NModelEvaluation::TFeatureLayout* featureInfo = nullptr
        ) {
            const size_t blockSize = Min(FORMULA_EVALUATION_BLOCK_SIZE, docCount);
            auto calcTrees = GetCalcTreesFunction(trees, blockSize);
            if (trees.GetTreeCount() == 0) {
                auto biasRef = trees.GetScaleAndBias().GetBiasRef();
                if (biasRef.size() == 1) {
                    Fill(results.begin(), results.end(), biasRef[0]);
                } else {
                    for (size_t idx = 0; idx < results.size();) {
                        for (size_t dim = 0; dim < biasRef.size(); ++dim, ++idx) {
                            results[idx] = biasRef[dim];
                        }
                    }
                }
                return;
            }
            Fill(results.begin(), results.end(), 0.0);
            TVector<TCalcerIndexType> indexesVec(blockSize);
            TEvalResultProcessor resultProcessor(
                docCount,
                results,
                predictionType,
                trees.GetScaleAndBias(),
                trees.GetDimensionsCount(),
                blockSize
            );
            ui32 blockId = 0;
            ProcessDocsInBlocks(
                trees,
                ctrProvider,
                textProcessingCollection,
                embeddingProcessingCollection,
                floatFeatureAccessor,
                catFeaturesAccessor,
                textFeatureAccessor,
                embeddingFeatureAccessor,
                docCount,
                blockSize,
                [&] (size_t docCountInBlock, const TCPUEvaluatorQuantizedData* quantizedData) {
                    auto blockResultsView = resultProcessor.GetViewForRawEvaluation(blockId);
                    calcTrees(
                        trees,