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392 lines
15 KiB
C++
392 lines
15 KiB
C++
#include "CatBoostLibraryHandler.h"
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#include <Columns/ColumnTuple.h>
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#include <Common/FieldVisitorConvertToNumber.h>
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int BAD_ARGUMENTS;
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extern const int CANNOT_APPLY_CATBOOST_MODEL;
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extern const int CANNOT_LOAD_CATBOOST_MODEL;
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extern const int LOGICAL_ERROR;
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}
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CatBoostLibraryHandler::APIHolder::APIHolder(SharedLibrary & lib)
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{
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ModelCalcerCreate = lib.get<CatBoostLibraryAPI::ModelCalcerCreateFunc>(CatBoostLibraryAPI::ModelCalcerCreateName);
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ModelCalcerDelete = lib.get<CatBoostLibraryAPI::ModelCalcerDeleteFunc>(CatBoostLibraryAPI::ModelCalcerDeleteName);
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GetErrorString = lib.get<CatBoostLibraryAPI::GetErrorStringFunc>(CatBoostLibraryAPI::GetErrorStringName);
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LoadFullModelFromFile = lib.get<CatBoostLibraryAPI::LoadFullModelFromFileFunc>(CatBoostLibraryAPI::LoadFullModelFromFileName);
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CalcModelPredictionFlat = lib.get<CatBoostLibraryAPI::CalcModelPredictionFlatFunc>(CatBoostLibraryAPI::CalcModelPredictionFlatName);
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CalcModelPrediction = lib.get<CatBoostLibraryAPI::CalcModelPredictionFunc>(CatBoostLibraryAPI::CalcModelPredictionName);
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CalcModelPredictionWithHashedCatFeatures = lib.get<CatBoostLibraryAPI::CalcModelPredictionWithHashedCatFeaturesFunc>(CatBoostLibraryAPI::CalcModelPredictionWithHashedCatFeaturesName);
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GetStringCatFeatureHash = lib.get<CatBoostLibraryAPI::GetStringCatFeatureHashFunc>(CatBoostLibraryAPI::GetStringCatFeatureHashName);
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GetIntegerCatFeatureHash = lib.get<CatBoostLibraryAPI::GetIntegerCatFeatureHashFunc>(CatBoostLibraryAPI::GetIntegerCatFeatureHashName);
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GetFloatFeaturesCount = lib.get<CatBoostLibraryAPI::GetFloatFeaturesCountFunc>(CatBoostLibraryAPI::GetFloatFeaturesCountName);
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GetCatFeaturesCount = lib.get<CatBoostLibraryAPI::GetCatFeaturesCountFunc>(CatBoostLibraryAPI::GetCatFeaturesCountName);
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GetTreeCount = lib.tryGet<CatBoostLibraryAPI::GetTreeCountFunc>(CatBoostLibraryAPI::GetTreeCountName);
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GetDimensionsCount = lib.tryGet<CatBoostLibraryAPI::GetDimensionsCountFunc>(CatBoostLibraryAPI::GetDimensionsCountName);
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}
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CatBoostLibraryHandler::CatBoostLibraryHandler(
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const std::string & library_path,
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const std::string & model_path)
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: loading_start_time(std::chrono::system_clock::now())
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, library(std::make_shared<SharedLibrary>(library_path))
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, api(*library)
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{
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model_calcer_handle = api.ModelCalcerCreate();
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if (!api.LoadFullModelFromFile(model_calcer_handle, model_path.c_str()))
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{
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throw Exception(ErrorCodes::CANNOT_LOAD_CATBOOST_MODEL,
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"Cannot load CatBoost model: {}", api.GetErrorString());
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}
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float_features_count = api.GetFloatFeaturesCount(model_calcer_handle);
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cat_features_count = api.GetCatFeaturesCount(model_calcer_handle);
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tree_count = 1;
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if (api.GetDimensionsCount)
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tree_count = api.GetDimensionsCount(model_calcer_handle);
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loading_duration = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - loading_start_time);
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}
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CatBoostLibraryHandler::~CatBoostLibraryHandler()
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{
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api.ModelCalcerDelete(model_calcer_handle);
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}
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std::chrono::system_clock::time_point CatBoostLibraryHandler::getLoadingStartTime() const
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{
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return loading_start_time;
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}
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std::chrono::milliseconds CatBoostLibraryHandler::getLoadingDuration() const
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{
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return loading_duration;
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}
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namespace
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{
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/// Buffer should be allocated with features_count * column->size() elements.
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/// Place column elements in positions buffer[0], buffer[features_count], ... , buffer[size * features_count]
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template <typename T>
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void placeColumnAsNumber(const IColumn * column, T * buffer, size_t features_count)
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{
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size_t size = column->size();
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FieldVisitorConvertToNumber<T> visitor;
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for (size_t i = 0; i < size; ++i)
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{
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/// TODO: Replace with column visitor.
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Field field;
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column->get(i, field);
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*buffer = applyVisitor(visitor, field);
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buffer += features_count;
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}
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}
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/// Buffer should be allocated with features_count * column->size() elements.
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/// Place string pointers in positions buffer[0], buffer[features_count], ... , buffer[size * features_count]
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void placeStringColumn(const ColumnString & column, const char ** buffer, size_t features_count)
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{
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size_t size = column.size();
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for (size_t i = 0; i < size; ++i)
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{
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*buffer = const_cast<char *>(column.getDataAt(i).data);
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buffer += features_count;
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}
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}
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/// Buffer should be allocated with features_count * column->size() elements.
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/// Place string pointers in positions buffer[0], buffer[features_count], ... , buffer[size * features_count]
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/// Returns PODArray which holds data (because ColumnFixedString doesn't store terminating zero).
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PODArray<char> placeFixedStringColumn(const ColumnFixedString & column, const char ** buffer, size_t features_count)
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{
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size_t size = column.size();
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size_t str_size = column.getN();
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PODArray<char> data(size * (str_size + 1));
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char * data_ptr = data.data();
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for (size_t i = 0; i < size; ++i)
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{
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auto ref = column.getDataAt(i);
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memcpy(data_ptr, ref.data, ref.size);
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data_ptr[ref.size] = 0;
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*buffer = data_ptr;
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data_ptr += ref.size + 1;
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buffer += features_count;
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}
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return data;
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}
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/// Place columns into buffer, returns column which holds placed data. Buffer should contains column->size() values.
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template <typename T>
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ColumnPtr placeNumericColumns(const ColumnRawPtrs & columns, size_t offset, size_t size, const T** buffer)
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{
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if (size == 0)
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return nullptr;
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size_t column_size = columns[offset]->size();
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auto data_column = ColumnVector<T>::create(size * column_size);
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T * data = data_column->getData().data();
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for (size_t i = 0; i < size; ++i)
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{
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const auto * column = columns[offset + i];
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if (column->isNumeric())
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placeColumnAsNumber(column, data + i, size);
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}
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for (size_t i = 0; i < column_size; ++i)
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{
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*buffer = data;
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++buffer;
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data += size;
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}
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return data_column;
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}
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/// Place columns into buffer, returns data which was used for fixed string columns.
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/// Buffer should contains column->size() values, each value contains size strings.
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std::vector<PODArray<char>> placeStringColumns(const ColumnRawPtrs & columns, size_t offset, size_t size, const char ** buffer)
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{
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if (size == 0)
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return {};
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std::vector<PODArray<char>> data;
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for (size_t i = 0; i < size; ++i)
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{
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const auto * column = columns[offset + i];
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if (const auto * column_string = typeid_cast<const ColumnString *>(column))
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placeStringColumn(*column_string, buffer + i, size);
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else if (const auto * column_fixed_string = typeid_cast<const ColumnFixedString *>(column))
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data.push_back(placeFixedStringColumn(*column_fixed_string, buffer + i, size));
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else
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throw Exception(ErrorCodes::LOGICAL_ERROR, "Cannot place string column.");
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}
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return data;
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}
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/// buffer[column_size * cat_features_count] -> char * => cat_features[column_size][cat_features_count] -> char *
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void fillCatFeaturesBuffer(
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const char *** cat_features, const char ** buffer,
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size_t column_size, size_t cat_features_count)
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{
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for (size_t i = 0; i < column_size; ++i)
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{
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*cat_features = buffer;
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++cat_features;
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buffer += cat_features_count;
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}
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}
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/// Calc hash for string cat feature at ps positions.
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template <typename Column>
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void calcStringHashes(const Column * column, size_t ps, const int ** buffer, const CatBoostLibraryHandler::APIHolder & api)
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{
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size_t column_size = column->size();
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for (size_t j = 0; j < column_size; ++j)
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{
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auto ref = column->getDataAt(j);
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const_cast<int *>(*buffer)[ps] = api.GetStringCatFeatureHash(ref.data, ref.size);
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++buffer;
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}
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}
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/// Calc hash for int cat feature at ps position. Buffer at positions ps should contains unhashed values.
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void calcIntHashes(size_t column_size, size_t ps, const int ** buffer, const CatBoostLibraryHandler::APIHolder & api)
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{
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for (size_t j = 0; j < column_size; ++j)
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{
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const_cast<int *>(*buffer)[ps] = api.GetIntegerCatFeatureHash((*buffer)[ps]);
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++buffer;
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}
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}
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/// buffer contains column->size() rows and size columns.
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/// For int cat features calc hash inplace.
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/// For string cat features calc hash from column rows.
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void calcHashes(const ColumnRawPtrs & columns, size_t offset, size_t size, const int ** buffer, const CatBoostLibraryHandler::APIHolder & api)
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{
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if (size == 0)
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return;
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size_t column_size = columns[offset]->size();
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std::vector<PODArray<char>> data;
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for (size_t i = 0; i < size; ++i)
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{
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const auto * column = columns[offset + i];
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if (const auto * column_string = typeid_cast<const ColumnString *>(column))
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calcStringHashes(column_string, i, buffer, api);
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else if (const auto * column_fixed_string = typeid_cast<const ColumnFixedString *>(column))
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calcStringHashes(column_fixed_string, i, buffer, api);
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else
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calcIntHashes(column_size, i, buffer, api);
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}
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}
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}
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/// Convert values to row-oriented format and call evaluation function from CatBoost wrapper api.
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/// * CalcModelPredictionFlat if no cat features
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/// * CalcModelPrediction if all cat features are strings
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/// * CalcModelPredictionWithHashedCatFeatures if has int cat features.
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ColumnFloat64::MutablePtr CatBoostLibraryHandler::evalImpl(
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const ColumnRawPtrs & columns,
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bool cat_features_are_strings) const
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{
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size_t column_size = columns.front()->size();
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auto result = ColumnFloat64::create(column_size * tree_count);
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auto * result_buf = result->getData().data();
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if (!column_size)
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return result;
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/// Prepare float features.
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PODArray<const float *> float_features(column_size);
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auto * float_features_buf = float_features.data();
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/// Store all float data into single column. float_features is a list of pointers to it.
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auto float_features_col = placeNumericColumns<float>(columns, 0, float_features_count, float_features_buf);
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if (cat_features_count == 0)
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{
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if (!api.CalcModelPredictionFlat(model_calcer_handle, column_size,
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float_features_buf, float_features_count,
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result_buf, column_size * tree_count))
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{
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throw Exception(ErrorCodes::CANNOT_APPLY_CATBOOST_MODEL,
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"Error occurred while applying CatBoost model: {}", api.GetErrorString());
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}
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return result;
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}
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/// Prepare cat features.
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if (cat_features_are_strings)
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{
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/// cat_features_holder stores pointers to ColumnString data or fixed_strings_data.
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PODArray<const char *> cat_features_holder(cat_features_count * column_size);
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PODArray<const char **> cat_features(column_size);
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auto * cat_features_buf = cat_features.data();
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fillCatFeaturesBuffer(cat_features_buf, cat_features_holder.data(), column_size, cat_features_count);
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/// Fixed strings are stored without termination zero, so have to copy data into fixed_strings_data.
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auto fixed_strings_data = placeStringColumns(columns, float_features_count,
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cat_features_count, cat_features_holder.data());
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if (!api.CalcModelPrediction(model_calcer_handle, column_size,
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float_features_buf, float_features_count,
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cat_features_buf, cat_features_count,
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result_buf, column_size * tree_count))
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{
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throw Exception(ErrorCodes::CANNOT_APPLY_CATBOOST_MODEL,
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"Error occurred while applying CatBoost model: {}", api.GetErrorString());
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}
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}
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else
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{
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PODArray<const int *> cat_features(column_size);
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auto * cat_features_buf = cat_features.data();
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auto cat_features_col = placeNumericColumns<int>(columns, float_features_count,
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cat_features_count, cat_features_buf);
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calcHashes(columns, float_features_count, cat_features_count, cat_features_buf, api);
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if (!api.CalcModelPredictionWithHashedCatFeatures(
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model_calcer_handle, column_size,
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float_features_buf, float_features_count,
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cat_features_buf, cat_features_count,
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result_buf, column_size * tree_count))
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{
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throw Exception(ErrorCodes::CANNOT_APPLY_CATBOOST_MODEL,
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"Error occurred while applying CatBoost model: {}", api.GetErrorString());
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}
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}
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return result;
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}
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size_t CatBoostLibraryHandler::getTreeCount() const
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{
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std::lock_guard lock(mutex);
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return tree_count;
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}
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ColumnPtr CatBoostLibraryHandler::evaluate(const ColumnRawPtrs & columns) const
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{
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std::lock_guard lock(mutex);
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if (columns.empty())
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throw Exception(ErrorCodes::BAD_ARGUMENTS, "Got empty columns list for CatBoost model.");
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if (columns.size() != float_features_count + cat_features_count)
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throw Exception(ErrorCodes::BAD_ARGUMENTS,
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"Number of columns is different with number of features: columns size {} float features size {} + cat features size {}",
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columns.size(),
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float_features_count,
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cat_features_count);
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for (size_t i = 0; i < float_features_count; ++i)
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{
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if (!columns[i]->isNumeric())
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{
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throw Exception(ErrorCodes::BAD_ARGUMENTS, "Column {} should be numeric to make float feature.", i);
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}
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}
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bool cat_features_are_strings = true;
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for (size_t i = float_features_count; i < float_features_count + cat_features_count; ++i)
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{
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const auto * column = columns[i];
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if (column->isNumeric())
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{
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cat_features_are_strings = false;
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}
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else if (!(typeid_cast<const ColumnString *>(column)
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|| typeid_cast<const ColumnFixedString *>(column)))
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{
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throw Exception(ErrorCodes::BAD_ARGUMENTS, "Column {} should be numeric or string.", i);
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}
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}
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auto result = evalImpl(columns, cat_features_are_strings);
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if (tree_count == 1)
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return result;
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size_t column_size = columns.front()->size();
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auto * result_buf = result->getData().data();
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/// Multiple trees case. Copy data to several columns.
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MutableColumns mutable_columns(tree_count);
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std::vector<Float64 *> column_ptrs(tree_count);
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for (size_t i = 0; i < tree_count; ++i)
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{
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auto col = ColumnFloat64::create(column_size);
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column_ptrs[i] = col->getData().data();
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mutable_columns[i] = std::move(col);
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}
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Float64 * data = result_buf;
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for (size_t row = 0; row < column_size; ++row)
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{
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for (size_t i = 0; i < tree_count; ++i)
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{
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*column_ptrs[i] = *data;
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++column_ptrs[i];
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++data;
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}
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}
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return ColumnTuple::create(std::move(mutable_columns));
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}
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}
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