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:
2026-07-28 19:36:26 +02:00
parent 441540a996
commit c7e87fe191
10 changed files with 552 additions and 107 deletions
+55 -38
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@@ -24,7 +24,7 @@
* Module Name: neural_network
* File Name: layer_dense.hpp
* Revision: 0.1.0
* Date: 23-06-2026
* Date: 28-08-2026
* Author: Michelle Bausager
*
* Description:
@@ -41,59 +41,76 @@
#include <tensor/vector.hpp>
#include <tensor/matrix.hpp>
//---------------------------------------------------------------------------------------------------------------------------
// DEFINE DESCRIPTION
//---------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------
// TYPE DESCRIPTION
//---------------------------------------------------------------------------------------------------------------------------
//--------------------------------------------------------------------------------------------------------------------------
// Function Name : panic::neural_network::layer_dense
//
// Description:
// Dense/fully-connected neural network layer.
//
// Inputs:
// Samples x input size const panic::tensor::real_matrix&
//
// Weight shape:
// input_size x neuron_count
//
// Bias shape:
// 1 x neuron_count
//
// Output shape:
// samples x neuron_count panic::tensor::real_matrix
//
// Notes:
// forward(input) calculates:
//
// outputs = inputs * weights + biases
//--------------------------------------------------------------------------------------------------------------------------
namespace panic{
namespace neural_network{
/**
* @brief struct for dense layer object used in neural networks
*
* Computes:
* @code
* panic::neural_network::layer_dense myDenseLayer(3, 5);
* myDenseLayer.forward(inputMatrix);
* @endcode
*
* The struct is used in PANIC nural_network library.
*/
struct layer_dense : public layer{
/**
* @brief Emphty weight matrix to store layer weights
*
* Weight shape:
* input_size x neuron_count
*/
panic::tensor::real_matrix weights;
panic::tensor::real_vector biases;
panic::tensor::real_matrix outputs;
// Empthy contructor
/**
* @brief Emphty bias vector to store layer bias
*
* Bias shape:
* 1 x neuron_count
*/
panic::tensor::real_vector biases;
/**
* @brief Empthy constructor
*
*/
layer_dense();
// Contructor with layer size
/**
* @brief Constructor with input size and amount of neurons
*
* @param input_size Input size of data to the network.
* @param neurons Amount of neurons in the layer
*
*/
layer_dense(panic::types::uint_t input_size, panic::types::uint_t neurons);
// Decontructor (All internal variables has decontructors, so we can just use default)
/**
* @brief Default de-constructor
*
*/
~layer_dense() = default;
// Forward function for forward pass
/**
* @brief Forward function for layer
*
* @param inputs Data input for forward pass.
*
* @Note Calculates -> outputs = inputs * weights + biases
*/
bool forward(const panic::tensor::real_matrix& inputs);
// Backward pass
/**
* @brief Backward function for layer
*
* @param inputs Data input for bacward pass.
*
* @Note Calculates derivative of forward function.
*/
bool backward(const panic::tensor::real_matrix& dinpus);
};