115 lines
4.0 KiB
C++
115 lines
4.0 KiB
C++
/********************************************************
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* ██████╗ ██████╗████████╗██╗
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* ██╔════╝ ██╔════╝╚══██╔══╝██║
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* ██║ ███╗██║ ██║ ██║
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* ██║ ██║██║ ██║ ██║
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* ╚██████╔╝╚██████╗ ██║ ███████╗
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* ╚═════╝ ╚═════╝ ╚═╝ ╚══════╝
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* Geophysical Computational Tools & Library (GCTL)
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*
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* Copyright (c) 2022 Yi Zhang (yizhang-geo@zju.edu.cn)
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*
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* GCTL is distributed under a dual licensing scheme. You can redistribute
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* it and/or modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation, either version 2
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* of the License, or (at your option) any later version. You should have
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* received a copy of the GNU Lesser General Public License along with this
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* program. If not, see <http://www.gnu.org/licenses/>.
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*
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* If the terms and conditions of the LGPL v.2. would prevent you from using
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* the GCTL, please consider the option to obtain a commercial license for a
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* fee. These licenses are offered by the GCTL's original author. As a rule,
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* licenses are provided "as-is", unlimited in time for a one time fee. Please
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* send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget
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* to include some description of your company and the realm of its activities.
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* Also add information on how to contact you by electronic and paper mail.
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******************************************************/
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#ifndef _GCTL_DWA_H
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#define _GCTL_DWA_H
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#include "gctl/core.h"
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#include "gctl/utility.h"
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namespace gctl
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{
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/**
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* @brief Lost balanced multitask evaluation.
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*
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* @note Reference: 2019. End-to-end multitask learning with attention.
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*
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*/
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class dwa
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{
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private:
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bool l_ready_;
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size_t fx_c_, fx_n_;
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double K_, T_, multi_fx_;
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array<double> wgts_;
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array<double> L_p1_, L_p2_;
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array<double> grad_;
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std::vector<array<double>> rcd_wgts_;
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public:
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dwa();
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virtual ~dwa();
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/**
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* @brief Initiate the number of loss functions and size of the model gradients.
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*
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* @note This function must be called at first.
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*
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* @param num Number of the loss functions
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* @param grad_num Size of the model gradients
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*/
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void InitDWA(size_t num, size_t grad_num);
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/**
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* @brief Add the value of a single loss function and the current model gradients.
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*
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* @param fx objective value
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* @param g model gradients
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*/
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void AddSingleLoss(double fx, const array<double> &g);
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/**
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* @brief Get the merged objective value and the model gradients.
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*
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* @note All single loss functions must be added before calling this function. The merged objective value and the model gradients will be reset after the calling.
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*
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* @param g model gradients
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*
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* @return objective value
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*/
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double DWALoss(array<double> &g);
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/**
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* @brief Update weights for single loss functions using the DWA algorithm.
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*
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*/
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void UpdateWeights();
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/**
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* @brief Set the cooling temperature. The bigger value is, the closer the weights will be to one. The default is 1.0.
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*
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* @param t Input temperature
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*/
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void set_control_temperature(double t);
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/**
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* @brief Set the normal sum of the weights. Ths default equals to function size.
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*
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* @param k Input sum
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*/
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void set_normal_sum(double k);
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/**
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* @brief Save the recorded weights.
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*
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* @param file Output file name
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*/
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void save_records(std::string file);
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};
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};
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#endif // _GCTL_DWA_H
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