stochastic_gradient_descent.h

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//   OpenNN: Open Neural Networks Library
//   www.opennn.net
//
//   S T O C H A S T I C   G R A D I E N T   D E S C E N T   C L A S S   H E A D E R
//
//   Artificial Intelligence Techniques SL
//   artelnics@artelnics.com
 
#pragma once
 
#include "optimizer.h"
 
namespace opennn
{
 
struct BackPropagation;

class StochasticGradientDescent final : public Optimizer
{
 
public:

    enum DataSlot { Velocity };

    StochasticGradientDescent(Loss* = nullptr);

    void set_default();

    void set_batch_size(const Index);

    Index get_samples_number() const;

    void set_initial_learning_rate(const float);
    void set_initial_decay(const float);
    void set_momentum(const float);
    void set_nesterov(bool);

    void update_parameters(BackPropagation&, OptimizerData&, float) const;

    TrainingResults train() override;

    void from_JSON(const JsonDocument&) override;

    void to_JSON(JsonWriter&) const override;
 
private:
 
    float initial_learning_rate;
 
    float initial_decay;
 
    float momentum = 0.0f;
 
    bool nesterov = false;
 
    Index batch_size = 0;
};
 
}
 
// OpenNN: Open Neural Networks Library.
// Copyright(C) 2005-2026 Artificial Intelligence Techniques, SL.
// Licensed under the GNU Lesser General Public License v2.1 or later.