Making loss_categorical_crossentropy
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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: loss_categorical_crossentropy.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_categorical_crossentropy 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 <neural_network/loss/loss.hpp>
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#include <config/omp.hpp>
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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 loss_categorical_crossentropy used in the rest of the neural network library
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*
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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_categorical_crossentropy: loss{
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/**
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* @brief forward function to calculate losses
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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 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 forward function to calculate losses
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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 Overloaded if one-shot endcoded
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* is used.
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*/
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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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} // namespace neural_network
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} // namespace panic
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