model.cpp/hpp
I made the model struct to store layers. I'm still missing the backward functions, but it's functional
This commit is contained in:
@@ -28,7 +28,7 @@
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* Author: Michelle Bausager
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*
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* Description:
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* Defines the base layers struct used in pther layers in neural network
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* Defines the base layers struct used in other layers in neural network
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*
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*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
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#pragma once
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@@ -38,38 +38,57 @@
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#include <config/types.hpp> // panic::uint_t, panic::int_t, and panic::real_t
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#include <tensor/matrix.hpp> // panic::tensor::real_matrix (uint_matrix, int_matrix)
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//---------------------------------------------------------------------------------------------------------------------------
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// DEFINE DESCRIPTION
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//---------------------------------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------------------------------
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// TYPE DESCRIPTION
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//---------------------------------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------------------------------
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// Type Name : panic::neural_network::layer
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//
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// Description:
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// A base layer to use in neural networks
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//
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// Member Variables:
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// None.
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//
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// Notes:
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// This base layer should be used in all layers/activations that have a forward and backward function
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// This is done so it's easy to make a list of layers in the model to loop over.
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// The virtual means it should use derived object's version when called with a pointer.
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// The =0 means the derviced object NEEDS to have these functions to work.
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//
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//---------------------------------------------------------------------------------------------------------------------------
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namespace panic{
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namespace neural_network{
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/**
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* @brief Base layer for the rest of the neural network library to use
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*
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* This base layer should be used in all layers/activations that have a forward and backward function
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* This is done so it's easy to make a list of layers in the model to loop over.
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* The virtual means it should use derived object's version when called with a pointer.
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* The =0 means the derivative object NEEDS to have these functions to work.
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*
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* The struct is used for PANIC neural_network library.
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*/
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struct layer{
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/**
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* @brief Emphty output matrix to store layer output
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*
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* Output shape:
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* samples x neuron_count
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*/
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panic::tensor::real_matrix outputs;
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/**
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* @brief Default de-constructor
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*
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*/
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virtual ~layer() = default;
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/**
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* @brief Virtual forward function for derivative layers
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*
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* @param inputs Data matrix input for forward function.
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*
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* @Note It's equal to 0 because it make the derivative
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* object NEEDS to have these function to work.
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*/
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virtual bool forward(const panic::tensor::real_matrix& inputs) = 0;
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/**
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* @brief Virtual backward function for derivative layers
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*
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* @param dinputs Data matrix input for backward function.
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*
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* @Note It's equal to 0 because it make the derivative
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* object NEEDS to have these function to work.
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*/
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virtual bool backward(const panic::tensor::real_matrix& dinputs) = 0;
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};
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@@ -79,12 +98,5 @@ struct layer{
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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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@@ -24,7 +24,7 @@
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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: 23-06-2026
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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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@@ -41,59 +41,76 @@
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#include <tensor/vector.hpp>
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#include <tensor/matrix.hpp>
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//---------------------------------------------------------------------------------------------------------------------------
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// DEFINE DESCRIPTION
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//---------------------------------------------------------------------------------------------------------------------------
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//---------------------------------------------------------------------------------------------------------------------------
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// TYPE DESCRIPTION
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//---------------------------------------------------------------------------------------------------------------------------
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//--------------------------------------------------------------------------------------------------------------------------
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// Function Name : panic::neural_network::layer_dense
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//
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// Description:
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// Dense/fully-connected neural network layer.
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//
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// Inputs:
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// Samples x input size const panic::tensor::real_matrix&
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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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// Bias shape:
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// 1 x neuron_count
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//
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// Output shape:
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// samples x neuron_count panic::tensor::real_matrix
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//
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// Notes:
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// forward(input) calculates:
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//
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// outputs = inputs * weights + biases
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//--------------------------------------------------------------------------------------------------------------------------
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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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panic::tensor::real_vector biases;
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panic::tensor::real_matrix outputs;
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// Empthy contructor
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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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// Contructor with layer size
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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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// Decontructor (All internal variables has decontructors, so we can just use default)
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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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// Forward function for forward pass
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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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// Backward pass
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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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@@ -0,0 +1,178 @@
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/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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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: model.hpp
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* Revision: 0.1.0
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* Date: 25-06-2026
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* Author: Michelle Bausager
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*
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* Description:
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* Defines the base model struct used in 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::types::uint_t, int_t and real_t
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#include <tensor/matrix.hpp> // panic::tensor::real_matrix
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#include <neural_network/layer/layer.hpp> // Base layer struct
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#include <neural_network/layer/layer_dense.hpp> // fully connected dense layer
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//---------------------------------------------------------------------------------------------------------------------------
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// TYPE DESCRIPTION
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//---------------------------------------------------------------------------------------------------------------------------
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namespace panic{
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namespace neural_network{
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/**
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* @brief Basic neural network model.
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*
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* The model owns an array of layer pointers
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*
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* @note
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* layer_count stores how many layers the model currently has.
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*
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* layers is a "pointer to pointers" -> layer** layers;
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* That means it points to an array where each element is a layer*
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*
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* The struct is used for PANIC neural_network library.
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*/
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struct model{
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/**
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* @brief a pointer to a pointer of layers
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*
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* An example:
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* layers[0] points to a layer_dense
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* layers[1] points to an actication function
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* layers[2] points to another layer_dense
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*
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* @note The model owns these layers and deletes them in clear().
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*
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*/
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layer** layers;
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// Number of layers currently stored in the model.
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/**
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* @brief Stores the number of layers
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*
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*/
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panic::types::uint_t layer_count;
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// model output (may be deleted and also used for debug)
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panic::tensor::real_matrix outputs;
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/**
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* @brief Empthy constructor
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*
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*/
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model();
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/**
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* @brief De-constructor
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*
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* @note Calls clear() to delete all layers and releases the layer pointer array
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*
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*/
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~model();
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// Add an already-created layer to the model.
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// Helper function for e.g. model.add_dense(5,5)
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/**
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* @brief Helper function for adding layers
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*
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* Computes:
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* @code
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* layer_dense* new_layer = new layer_dense(3, 4);
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* add(new_layer)
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* @endcode
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*
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* @note it adds an already-inplemented layer to the model.
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*
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*/
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bool add(layer* new_layer);
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// Create and add a dense layer.
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/**
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* @brief Adds a dense layer to the model.
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*
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* Computes:
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* @code
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* model.add_layer_dense(3,4);
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* @endcode
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*
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* @param inputs_size Input size of the data.
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* @param neuron_count Number of neurons in the layer.
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*
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* @return true if layer is added
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*
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* @note This function is convenient, but it allocates a new layer.
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*/
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bool add_layer_dense(
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panic::types::uint_t input_size,
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panic::types::uint_t neuron_count
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);
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/**
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* @brief Loops over all layers forward function
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*
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* Computes:
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* @code
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* model.forward(input_data_matrix)
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* @endcode
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*
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* @param inputs Input data.
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*
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* @return true looped over every layer.
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*
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* @note It takes the privious layer outputs and uses it as
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* the next layers input in the forward function.
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*
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*/
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bool forward(const panic::tensor::real_matrix& inputs);
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// Delete all layers and reset the model.
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/**
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* @brief Clears and deletes all layers and resets the model
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*
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* Computes:
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* @code
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* model.clear();
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* @endcode
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*
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* @note Primary used in the de-construtor.
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*
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*/
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void clear();
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};
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} // namespace neural_network
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} // namespace panic
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