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panic/include/neural_network/model/model.hpp
T
Bausager c7e87fe191 model.cpp/hpp
I made the model struct to store layers. I'm still missing the backward functions, but it's functional
2026-07-28 19:36:26 +02:00

178 lines
5.1 KiB
C++

/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
*
* PANIC
* Portable Algorithms and Numerics In C++
*
* Scientific computing from scratch, with feeling.
*
* Copyright (c) 2026 Michelle Bausager
*
* This file is part of PANIC.
*
* PANIC is free software licensed under the GNU General Public License v3.0 or later.
* You may redistribute and/or modify it under the terms of the GPL.
*
* PANIC is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
* See the LICENSE file for the full license text.
*
* SPDX-License-Identifier: GPL-3.0-or-later
*
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
*
* Project Name: PANIC
* Module Name: neural_network
* File Name: model.hpp
* Revision: 0.1.0
* Date: 25-06-2026
* Author: Michelle Bausager
*
* Description:
* Defines the base model struct used in in neural network
*
*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
#pragma once
//---------------------------------------------------------------------------------------------------------------------------
// INCLUDE DESCRIPTION
//---------------------------------------------------------------------------------------------------------------------------
#include <config/types.hpp> // panic::types::uint_t, int_t and real_t
#include <tensor/matrix.hpp> // panic::tensor::real_matrix
#include <neural_network/layer/layer.hpp> // Base layer struct
#include <neural_network/layer/layer_dense.hpp> // fully connected dense layer
//---------------------------------------------------------------------------------------------------------------------------
// TYPE DESCRIPTION
//---------------------------------------------------------------------------------------------------------------------------
namespace panic{
namespace neural_network{
/**
* @brief Basic neural network model.
*
* The model owns an array of layer pointers
*
* @note
* layer_count stores how many layers the model currently has.
*
* layers is a "pointer to pointers" -> layer** layers;
* That means it points to an array where each element is a layer*
*
* The struct is used for PANIC neural_network library.
*/
struct model{
/**
* @brief a pointer to a pointer of layers
*
* An example:
* layers[0] points to a layer_dense
* layers[1] points to an actication function
* layers[2] points to another layer_dense
*
* @note The model owns these layers and deletes them in clear().
*
*/
layer** layers;
// Number of layers currently stored in the model.
/**
* @brief Stores the number of layers
*
*/
panic::types::uint_t layer_count;
// model output (may be deleted and also used for debug)
panic::tensor::real_matrix outputs;
/**
* @brief Empthy constructor
*
*/
model();
/**
* @brief De-constructor
*
* @note Calls clear() to delete all layers and releases the layer pointer array
*
*/
~model();
// Add an already-created layer to the model.
// Helper function for e.g. model.add_dense(5,5)
/**
* @brief Helper function for adding layers
*
* Computes:
* @code
* layer_dense* new_layer = new layer_dense(3, 4);
* add(new_layer)
* @endcode
*
* @note it adds an already-inplemented layer to the model.
*
*/
bool add(layer* new_layer);
// Create and add a dense layer.
/**
* @brief Adds a dense layer to the model.
*
* Computes:
* @code
* model.add_layer_dense(3,4);
* @endcode
*
* @param inputs_size Input size of the data.
* @param neuron_count Number of neurons in the layer.
*
* @return true if layer is added
*
* @note This function is convenient, but it allocates a new layer.
*/
bool add_layer_dense(
panic::types::uint_t input_size,
panic::types::uint_t neuron_count
);
/**
* @brief Loops over all layers forward function
*
* Computes:
* @code
* model.forward(input_data_matrix)
* @endcode
*
* @param inputs Input data.
*
* @return true looped over every layer.
*
* @note It takes the privious layer outputs and uses it as
* the next layers input in the forward function.
*
*/
bool forward(const panic::tensor::real_matrix& inputs);
// Delete all layers and reset the model.
/**
* @brief Clears and deletes all layers and resets the model
*
* Computes:
* @code
* model.clear();
* @endcode
*
* @note Primary used in the de-construtor.
*
*/
void clear();
};
} // namespace neural_network
} // namespace panic