135 lines
4.1 KiB
C++
135 lines
4.1 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: loss.hpp
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* Revision: 0.1.0
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* Date: 30-07-2026
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* Author: Michelle Bausager
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*
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* Description:
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* Defines the base loss struct used in other loss functions 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 <tensor/matrix.hpp> // panic::tensor::real_matrix (uint_matrix, int_matrix)
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#include <tensor/vector.hpp>
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namespace panic{
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namespace neural_network{
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/**
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* @brief Base loss 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 loss functions.
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* This is done so it's easy to make new loss functions in the model.
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* The virtual means it should use derived object's version when called with a pointer.
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* The derived object can use overloading on forward, or just use one of them, to support one-shot encoding.
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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 loss{
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/**
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* @brief Emphty vector to store sample losses
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*
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*/
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panic::tensor::real_vector sample_losses;
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/**
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* @brief Mean loss over the entire batch.
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*/
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panic::types::real_t data_loss;
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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 ~loss() = default;
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/**
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* @brief Virtual forward function for derivative loss functions
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*
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* @param y_pred Matrix of model predection.
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* @param y_true Vector of true label of data.
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*
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* @Note If the derivatived object does not use this,
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* it returns false.
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*/
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virtual bool forward(
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const panic::tensor::real_matrix& y_pred,
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const panic::tensor::uint_vector& y_true);
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/**
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* @brief Virtual forward function for derivative loss functions
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*
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* @param y_pred Matrix of model predection.
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* @param y_true Matrix of true label of data.
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*
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* @Note If the derivatived object does not use this,
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* it returns false.
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*/
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virtual bool forward(
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const panic::tensor::real_matrix& y_pred,
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const panic::tensor::real_matrix& y_true);
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/**
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* @brief Virtual calculate function that calculates the loss
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*
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* @param y_pred Matrix of model predection.
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* @param y_true Vector of true label of data.
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*
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*/
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bool calculate(
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const panic::tensor::real_matrix& y_pred,
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const panic::tensor::uint_vector& y_true);
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/**
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* @brief Virtual calculate function that calculates the loss
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*
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* @param y_pred Matrix of model predection.
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* @param y_true Matrix of true label of data.
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*
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*/
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bool calculate(
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const panic::tensor::real_matrix& y_pred,
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const panic::tensor::real_matrix& y_true);
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};
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} // namespace neural_network
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} // namespace panic
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