wehub-resource-sync
94 lines
2.4 KiB
C++
94 lines
2.4 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_APPLICATION_H_
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#define LIGHTGBM_INCLUDE_LIGHTGBM_APPLICATION_H_
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#include <LightGBM/config.h>
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#include <LightGBM/meta.h>
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#include <memory>
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#include <vector>
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namespace LightGBM {
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class DatasetLoader;
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class Dataset;
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class Boosting;
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class ObjectiveFunction;
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class Metric;
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/*!
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* \brief The main entrance of LightGBM. this application has two tasks:
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* Train and Predict.
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* Train task will train a new model
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* Predict task will predict the scores of test data using existing model,
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* and save the score to disk.
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*/
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class Application {
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public:
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Application(int argc, char** argv);
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/*! \brief Destructor */
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~Application();
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/*! \brief To call this function to run application*/
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inline void Run();
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private:
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/*! \brief Load parameters from command line and config file*/
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void LoadParameters(int argc, char** argv);
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/*! \brief Load data, including training data and validation data*/
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void LoadData();
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/*! \brief Initialization before training*/
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void InitTrain();
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/*! \brief Main Training logic */
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void Train();
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/*! \brief Initializations before prediction */
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void InitPredict();
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/*! \brief Main predicting logic */
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void Predict();
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/*! \brief Main Convert model logic */
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void ConvertModel();
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/*! \brief All configs */
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Config config_;
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/*! \brief Training data */
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std::unique_ptr<Dataset> train_data_;
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/*! \brief Validation data */
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std::vector<std::unique_ptr<Dataset>> valid_datas_;
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/*! \brief Metric for training data */
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std::vector<std::unique_ptr<Metric>> train_metric_;
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/*! \brief Metrics for validation data */
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std::vector<std::vector<std::unique_ptr<Metric>>> valid_metrics_;
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/*! \brief Boosting object */
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std::unique_ptr<Boosting> boosting_;
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/*! \brief Training objective function */
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std::unique_ptr<ObjectiveFunction> objective_fun_;
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};
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inline void Application::Run() {
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if (config_.task == TaskType::kPredict || config_.task == TaskType::KRefitTree) {
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InitPredict();
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Predict();
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} else if (config_.task == TaskType::kConvertModel) {
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ConvertModel();
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} else {
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InitTrain();
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Train();
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}
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}
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} // namespace LightGBM
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#endif // LIGHTGBM_INCLUDE_LIGHTGBM_APPLICATION_H_
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