/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 *
 *                                              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:         loss.hpp
 * Revision:          0.1.0
 * Date:              30-07-2026
 * Author:            Michelle Bausager
 *
 * Description:
 * Defines the base loss struct used in other loss functions in neural network
 *
 *++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
#pragma once
//---------------------------------------------------------------------------------------------------------------------------
// INCLUDE DESCRIPTION
//---------------------------------------------------------------------------------------------------------------------------
#include <config/types.hpp> // panic::uint_t, panic::int_t, and panic::real_t
#include <tensor/matrix.hpp> // panic::tensor::real_matrix (uint_matrix, int_matrix)
#include <tensor/vector.hpp>


namespace panic{
	namespace neural_network{



/**
 * @brief Base loss for the rest of the neural network library to use
 *
 *    	This base layer should be used in all loss functions.
 * 		This is done so it's easy to make new loss functions in the model.
 * 		The virtual means it should use derived object's version when called with a pointer.
 *      The derived object can use overloading on forward, or just use one of them, to support one-shot encoding.
 * 
 * The struct is used for PANIC neural_network library.
 */
struct loss{

	 /**
     * @brief Emphty vector to store sample losses
     *
     */
	panic::tensor::real_vector sample_losses;

    /**
     * @brief Mean loss over the entire batch.
     */
    panic::types::real_t data_loss;

    /**
     * @brief Matrix for backwards pass
     */
    panic::tensor::real_matrix dinputs;


    /**
     * @brief Default de-constructor
     *
     */
	virtual ~loss() = default;


    /**
     * @brief Virtual forward function for derivative loss functions
     *
     * @param y_pred Matrix of model predection.  
     * @param y_true Vector of true label of data.
     * 
     * @Note If the derivatived object does not use this,
     *          it returns false.
     */
	virtual bool forward(
        const panic::tensor::real_matrix& y_pred, 
        const panic::tensor::uint_vector& y_true);

    /**
     * @brief Virtual forward function for derivative loss functions
     *
     * @param y_pred Matrix of model predection.  
     * @param y_true Matrix of true label of data.
     * 
     * @Note If the derivatived object does not use this,
     *          it returns false.
     */
    virtual bool forward(
        const panic::tensor::real_matrix& y_pred, 
        const panic::tensor::real_matrix& y_true);

    /**
     * @brief Virtual calculate function that calculates the loss
     *
     * @param y_pred Matrix of model predection.  
     * @param y_true Vector of true label of data.
     * 
     */
	bool calculate(
        const panic::tensor::real_matrix& y_pred, 
        const panic::tensor::uint_vector& y_true);

    /**
     * @brief Virtual calculate function that calculates the loss
     *
     * @param y_pred Matrix of model predection.  
     * @param y_true Matrix of true label of data.
     * 
     */
    bool calculate(
        const panic::tensor::real_matrix& y_pred, 
        const panic::tensor::real_matrix& y_true);

};



	} // namespace neural_network
} // namespace panic