sgd.h

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// SPDX-License-Identifier: AGPL-3.0-only
// Copyright (C) 2026 Artificial Intelligence Techniques, S.L. and Roberto López González
 
#pragma once
 
#include "opennn/training/optimizer.h"
 
namespace opennn
{
 
struct BackPropagation;
 
class SGD final : public Optimizer
{
 
public:
 
    enum DataSlot { Velocity, GraphLearningRate };
 
    explicit SGD(Loss* = nullptr);
 
    void set_initial_learning_rate(const float new_learning_rate) { initial_learning_rate = new_learning_rate; }
    float get_initial_learning_rate() const { return initial_learning_rate; }
    void set_initial_decay(const float new_decay) { initial_decay = new_decay; }
    void set_momentum(const float new_momentum) { momentum = new_momentum; }
    void set_nesterov(bool new_nesterov_momentum) { nesterov = new_nesterov_momentum; }
 
    void update_parameters(BackPropagation&, OptimizerData&,
                           UpdateMode = UpdateMode::Standard) override;
 
    void from_JSON(const JsonDocument&) override;
 
    void to_JSON(JsonWriter&) const override;
 
private:
 
    string get_display_name() const override { return "stochastic gradient descent (SGD)"; }
    bool supports_cuda_graph() const noexcept override { return true; }
    void setup_optimizer_data(OptimizerData&, Index, Device) override;
    void on_epoch_begin(Index, OptimizerData&) override;
 
    float initial_learning_rate = 0.001f;
 
    float initial_decay = 0.001f;
 
    float momentum = 0.0f;
 
    float current_learning_rate = 0.0f;
 
    bool nesterov = false;
};
 
}