tree_learner.h 2.86 KB
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#ifndef LIGHTGBM_TREE_LEARNER_H_
#define LIGHTGBM_TREE_LEARNER_H_


#include <LightGBM/meta.h>
#include <LightGBM/config.h>
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#include <LightGBM/json11.hpp>
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#include <vector>

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using namespace json11;

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namespace LightGBM {

/*! \brief forward declaration */
class Tree;
class Dataset;
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class ObjectiveFunction;
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/*!
* \brief Interface for tree learner
*/
class TreeLearner {
public:
  /*! \brief virtual destructor */
  virtual ~TreeLearner() {}

  /*!
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  * \brief Initialize tree learner with training dataset
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  * \param train_data The used training data
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  * \param is_constant_hessian True if all hessians share the same value
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  */
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  virtual void Init(const Dataset* train_data, bool is_constant_hessian) = 0;
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  virtual void ResetTrainingData(const Dataset* train_data) = 0;

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  /*!
  * \brief Reset tree configs
  * \param tree_config config of tree
  */
  virtual void ResetConfig(const TreeConfig* tree_config) = 0;

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  /*!
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  * \brief training tree model on dataset 
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  * \param gradients The first order gradients
  * \param hessians The second order gradients
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  * \param is_constant_hessian True if all hessians share the same value
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  * \return A trained tree
  */
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  virtual Tree* Train(const score_t* gradients, const score_t* hessians, bool is_constant_hessian, 
                      Json& forced_split_json) = 0;
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  /*!
  * \brief use a existing tree to fit the new gradients and hessians.
  */
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  virtual Tree* FitByExistingTree(const Tree* old_tree, const score_t* gradients, const score_t* hessians) const = 0;
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  virtual Tree* FitByExistingTree(const Tree* old_tree, const std::vector<int>& leaf_pred,
                                  const score_t* gradients, const score_t* hessians) = 0;

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  /*!
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  * \brief Set bagging data
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  * \param used_indices Used data indices
  * \param num_data Number of used data
  */
  virtual void SetBaggingData(const data_size_t* used_indices,
    data_size_t num_data) = 0;

  /*!
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  * \brief Using last trained tree to predict score then adding to out_score;
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  * \param out_score output score
  */
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  virtual void AddPredictionToScore(const Tree* tree, double* out_score) const = 0;
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  virtual void RenewTreeOutput(Tree* tree, const ObjectiveFunction* obj, const double* prediction,
                               data_size_t total_num_data, const data_size_t* bag_indices, data_size_t bag_cnt) const = 0;

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  TreeLearner() = default;
  /*! \brief Disable copy */
  TreeLearner& operator=(const TreeLearner&) = delete;
  /*! \brief Disable copy */
  TreeLearner(const TreeLearner&) = delete;

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  /*!
  * \brief Create object of tree learner
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  * \param learner_type Type of tree learner
  * \param device_type Type of tree learner
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  * \param tree_config config of tree
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  */
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  static TreeLearner* CreateTreeLearner(const std::string& learner_type,
    const std::string& device_type,
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    const TreeConfig* tree_config);
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};

}  // namespace LightGBM

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#endif   // LightGBM_TREE_LEARNER_H_