wehub-resource-sync
143 lines
4.7 KiB
C++
143 lines
4.7 KiB
C++
/*!
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* Copyright (c) 2016-2026 Microsoft Corporation. All rights reserved.
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* Copyright (c) 2016-2026 The LightGBM developers. All rights reserved.
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* Licensed under the MIT License. See LICENSE file in the project root for license information.
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*/
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#ifndef LIGHTGBM_INCLUDE_LIGHTGBM_OBJECTIVE_FUNCTION_H_
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#define LIGHTGBM_INCLUDE_LIGHTGBM_OBJECTIVE_FUNCTION_H_
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#include <LightGBM/config.h>
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#include <LightGBM/dataset.h>
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#include <LightGBM/meta.h>
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#include <string>
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#include <functional>
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namespace LightGBM {
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/*!
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* \brief The interface of Objective Function.
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*/
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class ObjectiveFunction {
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public:
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/*! \brief virtual destructor */
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virtual ~ObjectiveFunction() {}
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/*!
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* \brief Initialize
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* \param metadata Label data
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* \param num_data Number of data
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*/
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virtual void Init(const Metadata& metadata, data_size_t num_data) = 0;
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/*!
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* \brief calculating first order derivative of loss function
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* \param score prediction score in this round
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* \gradients Output gradients
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* \hessians Output hessians
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*/
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virtual void GetGradients(const double* score,
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score_t* gradients, score_t* hessians) const = 0;
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/*!
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* \brief calculating first order derivative of loss function, used only for bagging by query in lambdarank
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* \param score prediction score in this round
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* \param num_sampled_queries number of in-bag queries
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* \param sampled_query_indices indices of in-bag queries
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* \gradients Output gradients
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* \hessians Output hessians
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*/
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virtual void GetGradientsWithSampledQueries(const double* score, const data_size_t /*num_sampled_queries*/, const data_size_t* /*sampled_query_indices*/,
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score_t* gradients, score_t* hessians) const { GetGradients(score, gradients, hessians); }
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virtual const char* GetName() const = 0;
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virtual bool IsConstantHessian() const { return false; }
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virtual bool IsRenewTreeOutput() const { return false; }
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virtual double RenewTreeOutput(double ori_output, std::function<double(const label_t*, int)>,
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const data_size_t*,
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const data_size_t*,
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data_size_t) const { return ori_output; }
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virtual void RenewTreeOutputCUDA(const double* /*score*/, const data_size_t* /*data_indices_in_leaf*/, const data_size_t* /*num_data_in_leaf*/,
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const data_size_t* /*data_start_in_leaf*/, const int /*num_leaves*/, double* /*leaf_value*/) const {}
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virtual double BoostFromScore(int /*class_id*/) const { return 0.0; }
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virtual bool ClassNeedTrain(int /*class_id*/) const { return true; }
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virtual bool SkipEmptyClass() const { return false; }
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virtual int NumModelPerIteration() const { return 1; }
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virtual int NumPredictOneRow() const { return 1; }
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/*! \brief The prediction should be accurate or not. True will disable early stopping for prediction. */
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virtual bool NeedAccuratePrediction() const { return true; }
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/*! \brief Return the number of positive samples. Return 0 if no binary classification tasks.*/
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virtual data_size_t NumPositiveData() const { return 0; }
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virtual void ConvertOutput(const double* input, double* output) const {
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output[0] = input[0];
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}
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virtual std::string ToString() const = 0;
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ObjectiveFunction() = default;
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/*! \brief Disable copy */
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ObjectiveFunction& operator=(const ObjectiveFunction&) = delete;
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/*! \brief Disable copy */
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ObjectiveFunction(const ObjectiveFunction&) = delete;
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/*!
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* \brief Create object of objective function
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* \param type Specific type of objective function
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* \param config Config for objective function
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*/
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LIGHTGBM_EXPORT static ObjectiveFunction* CreateObjectiveFunction(const std::string& type,
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const Config& config);
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/*!
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* \brief Load objective function from string object
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*/
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LIGHTGBM_EXPORT static ObjectiveFunction* CreateObjectiveFunction(const std::string& str);
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/*!
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* \brief Whether boosting is done on CUDA
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*/
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virtual bool IsCUDAObjective() const { return false; }
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#ifdef USE_CUDA
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/*!
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* \brief Convert output for CUDA version
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*/
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virtual const double* ConvertOutputCUDA(data_size_t /*num_data*/, const double* input, double* /*output*/) const {
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return input;
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}
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virtual bool NeedConvertOutputCUDA () const { return false; }
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virtual void SetNCCLInfo(
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ncclComm_t /*nccl_communicator*/,
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int /*nccl_gpu_rank*/,
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int /*local_gpu_rank*/,
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int /*gpu_device_id*/,
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data_size_t /*global_num_data*/) {}
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/*!
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* \brief Create object of objective function on CUDA
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* \param type Specific type of objective function
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* \param config Config for objective function
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*/
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LIGHTGBM_EXPORT static ObjectiveFunction* CreateObjectiveFunctionCUDA(const std::string& type,
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const Config& config);
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#endif // USE_CUDA
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};
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} // namespace LightGBM
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#endif // LIGHTGBM_INCLUDE_LIGHTGBM_OBJECTIVE_FUNCTION_H_
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