fixed modifiers indent (#1997)

src/application/predictor.hpp

@@ -23,7 +23,7 @@ namespace LightGBM {
 * \brief Used to predict data with input model
 */
 class Predictor {
-public:
+ public:
   /*!
   * \brief Constructor
   * \param boosting Input boosting model
@@ -207,7 +207,7 @@ public:
     predict_data_reader.ReadAllAndProcessParallel(process_fun);
   }
 
-private:
+ private:
   void CopyToPredictBuffer(double* pred_buf, const std::vector<std::pair<int, double>>& features) {
     int loop_size = static_cast<int>(features.size());
     for (int i = 0; i < loop_size; ++i) {

src/boosting/dart.hpp

@@ -15,7 +15,7 @@ namespace LightGBM {
 * \brief DART algorithm implementation. including Training, prediction, bagging.
 */
 class DART: public GBDT {
-public:
+ public:
   /*!
   * \brief Constructor
   */
@@ -84,7 +84,7 @@ public:
     return false;
   }
 
-private:
+ private:
   /*!
   * \brief drop trees based on drop_rate
   */

src/boosting/gbdt.h

@@ -24,7 +24,7 @@ namespace LightGBM {
 * \brief GBDT algorithm implementation. including Training, prediction, bagging.
 */
 class GBDT : public GBDTBase {
-public:
+ public:
   /*!
   * \brief Constructor
   */
@@ -354,7 +354,7 @@ public:
   */
   virtual const char* SubModelName() const override { return "tree"; }
 
-protected:
+ protected:
   /*!
   * \brief Print eval result and check early stopping
   */

src/boosting/goss.hpp

@@ -24,7 +24,7 @@ std::chrono::duration<double, std::milli> re_init_tree_time;
 #endif
 
 class GOSS: public GBDT {
-public:
+ public:
   /*!
   * \brief Constructor
   */
@@ -208,7 +208,7 @@ public:
     }
   }
 
-private:
+ private:
   std::vector<data_size_t> tmp_indice_right_;
 };
 

src/boosting/rf.hpp

@@ -16,7 +16,7 @@ namespace LightGBM {
 * \brief Rondom Forest implementation
 */
 class RF : public GBDT {
-public:
+ public:
   RF() : GBDT() {
     average_output_ = true;
   }
@@ -199,7 +199,7 @@ public:
     return true;
   };
 
-private:
+ private:
   std::vector<score_t> tmp_grad_;
   std::vector<score_t> tmp_hess_;
   std::vector<double> init_scores_;

src/boosting/score_updater.hpp

@@ -15,7 +15,7 @@ namespace LightGBM {
 * \brief Used to store and update score for data
 */
 class ScoreUpdater {
-public:
+ public:
   /*!
   * \brief Constructor, will pass a const pointer of dataset
   * \param data This class will bind with this data set
@@ -109,7 +109,7 @@ public:
   /*! \brief Disable copy */
   ScoreUpdater(const ScoreUpdater&) = delete;
 
-private:
+ private:
   /*! \brief Number of total data */
   data_size_t num_data_;
   /*! \brief Pointer of data set */

src/c_api.cpp

@@ -44,7 +44,7 @@ catch(...) { return LGBM_APIHandleException("unknown exception"); } \
 return 0;
 
 class Booster {
-public:
+ public:
   explicit Booster(const char* filename) {
     boosting_.reset(Boosting::CreateBoosting("gbdt", filename));
   }
@@ -323,7 +323,7 @@ public:
 
   const Boosting* GetBoosting() const { return boosting_.get(); }
 
-private:
+ private:
   const Dataset* train_data_;
   std::unique_ptr<Boosting> boosting_;
   /*! \brief All configs */
@@ -356,7 +356,7 @@ RowFunctionFromCSR(const void* indptr, int indptr_type, const int32_t* indices,
 
 // Row iterator of on column for CSC matrix
 class CSC_RowIterator {
-public:
+ public:
   CSC_RowIterator(const void* col_ptr, int col_ptr_type, const int32_t* indices,
                   const void* data, int data_type, int64_t ncol_ptr, int64_t nelem, int col_idx);
   ~CSC_RowIterator() {}
@@ -364,7 +364,8 @@ public:
   double Get(int idx);
   // return next non-zero pair, if index < 0, means no more data
   std::pair<int, double> NextNonZero();
-private:
+
+ private:
   int nonzero_idx_ = 0;
   int cur_idx_ = -1;
   double cur_val_ = 0.0f;

src/io/dense_bin.hpp

@@ -14,7 +14,7 @@ class DenseBin;
 
 template <typename VAL_T>
 class DenseBinIterator: public BinIterator {
-public:
+ public:
   explicit DenseBinIterator(const DenseBin<VAL_T>* bin_data, uint32_t min_bin, uint32_t max_bin, uint32_t default_bin)
     : bin_data_(bin_data), min_bin_(static_cast<VAL_T>(min_bin)),
     max_bin_(static_cast<VAL_T>(max_bin)),
@@ -28,7 +28,8 @@ public:
   inline uint32_t RawGet(data_size_t idx) override;
   inline uint32_t Get(data_size_t idx) override;
   inline void Reset(data_size_t) override { }
-private:
+
+ private:
   const DenseBin<VAL_T>* bin_data_;
   VAL_T min_bin_;
   VAL_T max_bin_;
@@ -41,7 +42,7 @@ private:
 */
 template <typename VAL_T>
 class DenseBin: public Bin {
-public:
+ public:
   friend DenseBinIterator<VAL_T>;
   DenseBin(data_size_t num_data)
     : num_data_(num_data), data_(num_data_, static_cast<VAL_T>(0)) {
@@ -310,7 +311,7 @@ public:
     return sizeof(VAL_T) * num_data_;
   }
 
-protected:
+ protected:
   data_size_t num_data_;
   std::vector<VAL_T> data_;
 };

src/io/dense_nbits_bin.hpp

@@ -12,7 +12,7 @@ namespace LightGBM {
 class Dense4bitsBin;
 
 class Dense4bitsBinIterator : public BinIterator {
-public:
+ public:
   explicit Dense4bitsBinIterator(const Dense4bitsBin* bin_data, uint32_t min_bin, uint32_t max_bin, uint32_t default_bin)
     : bin_data_(bin_data), min_bin_(static_cast<uint8_t>(min_bin)),
     max_bin_(static_cast<uint8_t>(max_bin)),
@@ -26,7 +26,8 @@ public:
   inline uint32_t RawGet(data_size_t idx) override;
   inline uint32_t Get(data_size_t idx) override;
   inline void Reset(data_size_t) override {}
-private:
+
+ private:
   const Dense4bitsBin* bin_data_;
   uint8_t min_bin_;
   uint8_t max_bin_;
@@ -35,7 +36,7 @@ private:
 };
 
 class Dense4bitsBin : public Bin {
-public:
+ public:
   friend Dense4bitsBinIterator;
   Dense4bitsBin(data_size_t num_data)
     : num_data_(num_data) {
@@ -362,7 +363,7 @@ public:
     return sizeof(uint8_t) * data_.size();
   }
 
-protected:
+ protected:
   data_size_t num_data_;
   std::vector<uint8_t> data_;
   std::vector<uint8_t> buf_;

src/io/file_io.cpp

@@ -42,7 +42,7 @@ struct LocalFile : VirtualFileReader, VirtualFileWriter {
     return fwrite(buffer, bytes, 1, file_) == 1 ? bytes : 0;
   }
 
-private:
+ private:
   FILE* file_ = NULL;
   const std::string filename_;
   const std::string mode_;
@@ -86,7 +86,7 @@ struct HDFSFile : VirtualFileReader, VirtualFileWriter {
     return FileOperation<const void*>(data, bytes, &hdfsWrite);
   }
 
-private:
+ private:
   template <typename BufferType>
   using fileOp = tSize(*)(hdfsFS, hdfsFile, BufferType, tSize);
 

src/io/json11.cpp

@@ -147,7 +147,7 @@ void Json::dump(string &out) const {
 
 template <Json::Type tag, typename T>
 class Value : public JsonValue {
-protected:
+ protected:
     // Constructors
     explicit Value(const T &value) : m_value(value) {}
     explicit Value(T &&value)      : m_value(move(value)) {}
@@ -174,7 +174,7 @@ class JsonDouble final : public Value<Json::NUMBER, double> {
     int int_value() const override { return static_cast<int>(m_value); }
     bool equals(const JsonValue * other) const override { return m_value == other->number_value(); }
     bool less(const JsonValue * other)   const override { return m_value <  other->number_value(); }
-public:
+ public:
     explicit JsonDouble(double value) : Value(value) {}
 };
 
@@ -183,19 +183,19 @@ class JsonInt final : public Value<Json::NUMBER, int> {
     int int_value() const override { return m_value; }
     bool equals(const JsonValue * other) const override { return m_value == other->number_value(); }
     bool less(const JsonValue * other)   const override { return m_value <  other->number_value(); }
-public:
+ public:
     explicit JsonInt(int value) : Value(value) {}
 };
 
 class JsonBoolean final : public Value<Json::BOOL, bool> {
     bool bool_value() const override { return m_value; }
-public:
+ public:
     explicit JsonBoolean(bool value) : Value(value) {}
 };
 
 class JsonString final : public Value<Json::STRING, string> {
     const string &string_value() const override { return m_value; }
-public:
+ public:
     explicit JsonString(const string &value) : Value(value) {}
     explicit JsonString(string &&value)      : Value(move(value)) {}
 };
@@ -203,7 +203,7 @@ public:
 class JsonArray final : public Value<Json::ARRAY, Json::array> {
     const Json::array &array_items() const override { return m_value; }
     const Json & operator[](size_t i) const override;
-public:
+ public:
     explicit JsonArray(const Json::array &value) : Value(value) {}
     explicit JsonArray(Json::array &&value)      : Value(move(value)) {}
 };
@@ -211,13 +211,13 @@ public:
 class JsonObject final : public Value<Json::OBJECT, Json::object> {
     const Json::object &object_items() const override { return m_value; }
     const Json & operator[](const string &key) const override;
-public:
+ public:
     explicit JsonObject(const Json::object &value) : Value(value) {}
     explicit JsonObject(Json::object &&value)      : Value(move(value)) {}
 };
 
 class JsonNull final : public Value<Json::NUL, NullStruct> {
-public:
+ public:
     JsonNull() : Value({}) {}
 };
 

src/io/ordered_sparse_bin.hpp

@@ -24,7 +24,7 @@ namespace LightGBM {
 */
 template <typename VAL_T>
 class OrderedSparseBin: public OrderedBin {
-public:
+ public:
   /*! \brief Pair to store one bin entry */
   struct SparsePair {
     data_size_t ridx;  // data(row) index
@@ -192,7 +192,7 @@ public:
   /*! \brief Disable copy */
   OrderedSparseBin<VAL_T>(const OrderedSparseBin<VAL_T>&) = delete;
 
-private:
+ private:
   const SparseBin<VAL_T>* bin_data_;
   /*! \brief Store non-zero pair , group by leaf */
   std::vector<SparsePair> ordered_pair_;

src/io/parser.hpp

@@ -13,7 +13,7 @@
 namespace LightGBM {
 
 class CSVParser: public Parser {
-public:
+ public:
   explicit CSVParser(int label_idx, int total_columns)
     :label_idx_(label_idx), total_columns_(total_columns) {
   }
@@ -45,13 +45,13 @@ public:
     return total_columns_;
   }
 
-private:
+ private:
   int label_idx_ = 0;
   int total_columns_ = -1;
 };
 
 class TSVParser: public Parser {
-public:
+ public:
   explicit TSVParser(int label_idx, int total_columns)
     :label_idx_(label_idx), total_columns_(total_columns) {
   }
@@ -81,13 +81,13 @@ public:
     return total_columns_;
   }
 
-private:
+ private:
   int label_idx_ = 0;
   int total_columns_ = -1;
 };
 
 class LibSVMParser: public Parser {
-public:
+ public:
   explicit LibSVMParser(int label_idx)
     :label_idx_(label_idx) {
     if (label_idx > 0) {
@@ -121,7 +121,7 @@ public:
     return -1;
   }
 
-private:
+ private:
   int label_idx_ = 0;
 };
 

src/io/sparse_bin.hpp

@@ -20,7 +20,7 @@ const size_t kNumFastIndex = 64;
 
 template <typename VAL_T>
 class SparseBinIterator: public BinIterator {
-public:
+ public:
   SparseBinIterator(const SparseBin<VAL_T>* bin_data,
     uint32_t min_bin, uint32_t max_bin, uint32_t default_bin)
     : bin_data_(bin_data), min_bin_(static_cast<VAL_T>(min_bin)),
@@ -52,7 +52,7 @@ public:
 
   inline void Reset(data_size_t idx) override;
 
-private:
+ private:
   const SparseBin<VAL_T>* bin_data_;
   data_size_t cur_pos_;
   data_size_t i_delta_;
@@ -67,7 +67,7 @@ class OrderedSparseBin;
 
 template <typename VAL_T>
 class SparseBin: public Bin {
-public:
+ public:
   friend class SparseBinIterator<VAL_T>;
   friend class OrderedSparseBin<VAL_T>;
 
@@ -407,7 +407,7 @@ public:
     GetFastIndex();
   }
 
-protected:
+ protected:
   data_size_t num_data_;
   std::vector<uint8_t> deltas_;
   std::vector<VAL_T> vals_;

src/metric/binary_metric.hpp

@@ -18,7 +18,7 @@ namespace LightGBM {
 */
 template<typename PointWiseLossCalculator>
 class BinaryMetric: public Metric {
-public:
+ public:
   explicit BinaryMetric(const Config&) {
   }
 
@@ -92,7 +92,7 @@ public:
     return std::vector<double>(1, loss);
   }
 
-private:
+ private:
   /*! \brief Number of data */
   data_size_t num_data_;
   /*! \brief Pointer of label */
@@ -109,7 +109,7 @@ private:
 * \brief Log loss metric for binary classification task.
 */
 class BinaryLoglossMetric: public BinaryMetric<BinaryLoglossMetric> {
-public:
+ public:
   explicit BinaryLoglossMetric(const Config& config) :BinaryMetric<BinaryLoglossMetric>(config) {}
 
   inline static double LossOnPoint(label_t label, double prob) {
@@ -133,7 +133,7 @@ public:
 * \brief Error rate metric for binary classification task.
 */
 class BinaryErrorMetric: public BinaryMetric<BinaryErrorMetric> {
-public:
+ public:
   explicit BinaryErrorMetric(const Config& config) :BinaryMetric<BinaryErrorMetric>(config) {}
 
   inline static double LossOnPoint(label_t label, double prob) {
@@ -153,7 +153,7 @@ public:
 * \brief Auc Metric for binary classification task.
 */
 class AUCMetric: public Metric {
-public:
+ public:
   explicit AUCMetric(const Config&) {
   }
 
@@ -246,7 +246,7 @@ public:
     return std::vector<double>(1, auc);
   }
 
-private:
+ private:
   /*! \brief Number of data */
   data_size_t num_data_;
   /*! \brief Pointer of label */

src/metric/map_metric.hpp

@@ -13,7 +13,7 @@
 namespace LightGBM {
 
 class MapMetric:public Metric {
-public:
+ public:
   explicit MapMetric(const Config& config) {
     // get eval position
     eval_at_ = config.eval_at;
@@ -142,7 +142,7 @@ public:
     return result;
   }
 
-private:
+ private:
   /*! \brief Number of data */
   data_size_t num_data_;
   /*! \brief Pointer of label */

src/metric/multiclass_metric.hpp

@@ -14,7 +14,7 @@ namespace LightGBM {
 */
 template<typename PointWiseLossCalculator>
 class MulticlassMetric: public Metric {
-public:
+ public:
   explicit MulticlassMetric(const Config& config) {
     num_class_ = config.num_class;
   }
@@ -112,7 +112,7 @@ public:
     return std::vector<double>(1, loss);
   }
 
-private:
+ private:
   /*! \brief Number of data */
   data_size_t num_data_;
   /*! \brief Pointer of label */
@@ -128,7 +128,7 @@ private:
 
 /*! \brief L2 loss for multiclass task */
 class MultiErrorMetric: public MulticlassMetric<MultiErrorMetric> {
-public:
+ public:
   explicit MultiErrorMetric(const Config& config) :MulticlassMetric<MultiErrorMetric>(config) {}
 
   inline static double LossOnPoint(label_t label, std::vector<double>& score) {
@@ -148,7 +148,7 @@ public:
 
 /*! \brief Logloss for multiclass task */
 class MultiSoftmaxLoglossMetric: public MulticlassMetric<MultiSoftmaxLoglossMetric> {
-public:
+ public:
   explicit MultiSoftmaxLoglossMetric(const Config& config) :MulticlassMetric<MultiSoftmaxLoglossMetric>(config) {}
 
   inline static double LossOnPoint(label_t label, std::vector<double>& score) {

src/metric/rank_metric.hpp

@@ -13,7 +13,7 @@
 namespace LightGBM {
 
 class NDCGMetric:public Metric {
-public:
+ public:
   explicit NDCGMetric(const Config& config) {
     // get eval position
     eval_at_ = config.eval_at;
@@ -143,7 +143,7 @@ public:
     return result;
   }
 
-private:
+ private:
   /*! \brief Number of data */
   data_size_t num_data_;
   /*! \brief Pointer of label */

src/metric/regression_metric.hpp

@@ -14,7 +14,7 @@ namespace LightGBM {
 */
 template<typename PointWiseLossCalculator>
 class RegressionMetric: public Metric {
-public:
+ public:
   explicit RegressionMetric(const Config& config) :config_(config) {
   }
 
@@ -95,7 +95,7 @@ public:
   inline static void CheckLabel(label_t) {
   }
 
-private:
+ private:
   /*! \brief Number of data */
   data_size_t num_data_;
   /*! \brief Pointer of label */
@@ -111,7 +111,7 @@ private:
 
 /*! \brief RMSE loss for regression task */
 class RMSEMetric: public RegressionMetric<RMSEMetric> {
-public:
+ public:
   explicit RMSEMetric(const Config& config) :RegressionMetric<RMSEMetric>(config) {}
 
   inline static double LossOnPoint(label_t label, double score, const Config&) {
@@ -130,7 +130,7 @@ public:
 
 /*! \brief L2 loss for regression task */
 class L2Metric: public RegressionMetric<L2Metric> {
-public:
+ public:
   explicit L2Metric(const Config& config) :RegressionMetric<L2Metric>(config) {}
 
   inline static double LossOnPoint(label_t label, double score, const Config&) {
@@ -144,7 +144,7 @@ public:
 
 /*! \brief L2 loss for regression task */
 class QuantileMetric : public RegressionMetric<QuantileMetric> {
-public:
+ public:
   explicit QuantileMetric(const Config& config) :RegressionMetric<QuantileMetric>(config) {
   }
 
@@ -165,7 +165,7 @@ public:
 
 /*! \brief L1 loss for regression task */
 class L1Metric: public RegressionMetric<L1Metric> {
-public:
+ public:
   explicit L1Metric(const Config& config) :RegressionMetric<L1Metric>(config) {}
 
   inline static double LossOnPoint(label_t label, double score, const Config&) {
@@ -178,7 +178,7 @@ public:
 
 /*! \brief Huber loss for regression task */
 class HuberLossMetric: public RegressionMetric<HuberLossMetric> {
-public:
+ public:
   explicit HuberLossMetric(const Config& config) :RegressionMetric<HuberLossMetric>(config) {
   }
 
@@ -199,7 +199,7 @@ public:
 /*! \brief Fair loss for regression task */
 // http://research.microsoft.com/en-us/um/people/zhang/INRIA/Publis/Tutorial-Estim/node24.html
 class FairLossMetric: public RegressionMetric<FairLossMetric> {
-public:
+ public:
   explicit FairLossMetric(const Config& config) :RegressionMetric<FairLossMetric>(config) {
   }
 
@@ -216,7 +216,7 @@ public:
 
 /*! \brief Poisson regression loss for regression task */
 class PoissonMetric: public RegressionMetric<PoissonMetric> {
-public:
+ public:
   explicit PoissonMetric(const Config& config) :RegressionMetric<PoissonMetric>(config) {
   }
 
@@ -235,7 +235,7 @@ public:
 
 /*! \brief Mape regression loss for regression task */
 class MAPEMetric : public RegressionMetric<MAPEMetric> {
-public:
+ public:
   explicit MAPEMetric(const Config& config) :RegressionMetric<MAPEMetric>(config) {
   }
 
@@ -248,7 +248,7 @@ public:
 };
 
 class GammaMetric : public RegressionMetric<GammaMetric> {
-public:
+ public:
   explicit GammaMetric(const Config& config) :RegressionMetric<GammaMetric>(config) {
   }
 
@@ -271,7 +271,7 @@ public:
 
 
 class GammaDevianceMetric : public RegressionMetric<GammaDevianceMetric> {
-public:
+ public:
   explicit GammaDevianceMetric(const Config& config) :RegressionMetric<GammaDevianceMetric>(config) {
   }
 
@@ -292,7 +292,7 @@ public:
 };
 
 class TweedieMetric : public RegressionMetric<TweedieMetric> {
-public:
+ public:
   explicit TweedieMetric(const Config& config) :RegressionMetric<TweedieMetric>(config) {
   }
 

src/metric/xentropy_metric.hpp

@@ -65,7 +65,7 @@ namespace LightGBM {
 // CrossEntropyMetric : "xentropy" : (optional) weights are used linearly
 //
 class CrossEntropyMetric : public Metric {
-public:
+ public:
   explicit CrossEntropyMetric(const Config&) {}
   virtual ~CrossEntropyMetric() {}
 
@@ -142,7 +142,7 @@ public:
     return -1.0f;  // negative means smaller loss is better, positive means larger loss is better
   }
 
-private:
+ private:
   /*! \brief Number of data points */
   data_size_t num_data_;
   /*! \brief Pointer to label */
@@ -160,7 +160,7 @@ private:
 // ATTENTION: Supposed to be used when the objective also is "xentlambda"
 //
 class CrossEntropyLambdaMetric : public Metric {
-public:
+ public:
   explicit CrossEntropyLambdaMetric(const Config&) {}
   virtual ~CrossEntropyLambdaMetric() {}
 
@@ -228,7 +228,7 @@ public:
     return -1.0f;
   }
 
-private:
+ private:
   /*! \brief Number of data points */
   data_size_t num_data_;
   /*! \brief Pointer to label */
@@ -243,7 +243,7 @@ private:
 // KullbackLeiblerDivergence : "kldiv" : (optional) weights are used linearly
 //
 class KullbackLeiblerDivergence : public Metric {
-public:
+ public:
   explicit KullbackLeiblerDivergence(const Config&) {}
   virtual ~KullbackLeiblerDivergence() {}
 
@@ -336,7 +336,7 @@ public:
     return -1.0f;
   }
 
-private:
+ private:
   /*! \brief Number of data points */
   data_size_t num_data_;
   /*! \brief Pointer to label */