Bausager
c7e87fe191
I made the model struct to store layers. I'm still missing the backward functions, but it's functional
129 lines
3.9 KiB
C++
129 lines
3.9 KiB
C++
/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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*
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* PANIC
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* Portable Algorithms and Numerics In C++
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*
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* Scientific computing from scratch, with feeling.
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*
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* Copyright (c) 2026 Michelle Bausager
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*
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* This file is part of PANIC.
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*
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* PANIC is free software licensed under the GNU General Public License v3.0 or later.
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* You may redistribute and/or modify it under the terms of the GPL.
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*
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* PANIC is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
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* without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
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* See the LICENSE file for the full license text.
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*
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* SPDX-License-Identifier: GPL-3.0-or-later
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*
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*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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*
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* Project Name: PANIC
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* Module Name: neural_network
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* File Name: layer_dense.hpp
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* Revision: 0.1.0
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* Date: 28-08-2026
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* Author: Michelle Bausager
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*
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* Description:
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* Defines the dense layers used in neural network
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*
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*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
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#pragma once
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//---------------------------------------------------------------------------------------------------------------------------
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// INCLUDE DESCRIPTION
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//---------------------------------------------------------------------------------------------------------------------------
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#include <config/types.hpp> // panic::uint_t, panic::int_t, and panic::real_t
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#include <neural_network/layer/layer.hpp> // for base layer struct
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#include <tensor/vector.hpp>
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#include <tensor/matrix.hpp>
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namespace panic{
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namespace neural_network{
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/**
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* @brief struct for dense layer object used in neural networks
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*
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* Computes:
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* @code
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* panic::neural_network::layer_dense myDenseLayer(3, 5);
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* myDenseLayer.forward(inputMatrix);
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* @endcode
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*
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* The struct is used in PANIC nural_network library.
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*/
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struct layer_dense : public layer{
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/**
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* @brief Emphty weight matrix to store layer weights
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*
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* Weight shape:
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* input_size x neuron_count
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*/
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panic::tensor::real_matrix weights;
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/**
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* @brief Emphty bias vector to store layer bias
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*
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* Bias shape:
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* 1 x neuron_count
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*/
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panic::tensor::real_vector biases;
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/**
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* @brief Empthy constructor
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*
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*/
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layer_dense();
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/**
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* @brief Constructor with input size and amount of neurons
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*
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* @param input_size Input size of data to the network.
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* @param neurons Amount of neurons in the layer
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*
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*/
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layer_dense(panic::types::uint_t input_size, panic::types::uint_t neurons);
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/**
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* @brief Default de-constructor
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*
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*/
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~layer_dense() = default;
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/**
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* @brief Forward function for layer
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*
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* @param inputs Data input for forward pass.
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*
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* @Note Calculates -> outputs = inputs * weights + biases
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*/
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bool forward(const panic::tensor::real_matrix& inputs);
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/**
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* @brief Backward function for layer
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*
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* @param inputs Data input for bacward pass.
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*
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* @Note Calculates derivative of forward function.
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*/
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bool backward(const panic::tensor::real_matrix& dinpus);
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};
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} // namespace tensor
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} // namespace panic
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//---------------------------------------------------------------------------------------------------------------------------
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// VARIABLE DESCRIPTION
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//---------------------------------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------------------------------
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// FUNCTION PROTOTYPE
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//---------------------------------------------------------------------------------------------------------------------------
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