FirstOrderStochasticMinimizer.h

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2015 Wu Lin
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 *    list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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#ifndef FIRSTORDERSTOCHASTICMINIMIZER_H
#define FIRSTORDERSTOCHASTICMINIMIZER_H
#include <shogun/optimization/FirstOrderMinimizer.h>
#include <shogun/optimization/FirstOrderStochasticCostFunction.h>
#include <shogun/optimization/DescendUpdater.h>
#include <shogun/optimization/LearningRate.h>
namespace shogun
{

class FirstOrderStochasticMinimizer: public FirstOrderMinimizer
{
public:
    FirstOrderStochasticMinimizer()
        :FirstOrderMinimizer()
    {
        init();
    }

    FirstOrderStochasticMinimizer(FirstOrderStochasticCostFunction *fun)
        :FirstOrderMinimizer(fun)
    {
        init();
    }

    virtual const char* get_name() const { return "FirstOrderStochasticMinimizer"; }

    virtual ~FirstOrderStochasticMinimizer();

    virtual bool supports_batch_update() const {return false;}

    virtual void set_gradient_updater(DescendUpdater* gradient_updater);

    virtual float64_t minimize()=0;

    virtual void set_number_passes(int32_t num_passes);

    virtual void set_learning_rate(LearningRate *learning_rate);

    virtual int32_t get_iteration_counter() {return m_iter_counter;}

protected:
    virtual void do_proximal_operation(SGVector<float64_t>variable_reference);
    
    virtual void init_minimization();

    DescendUpdater* m_gradient_updater;

    int32_t m_num_passes;

    int32_t m_cur_passes;

    int32_t m_iter_counter;

    LearningRate* m_learning_rate;
    
private:
    void init();
};

}
#endif /* FIRSTORDERSTOCHASTICMINIMIZER_H */