Save

I've created the optimizer class

include/neural_network/activation_loss/activation_softmax_loss_categorical_crossentropy.hpp

@@ -0,0 +1,216 @@
+/**++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ *
+ *                                              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:         activation_softmax_loss_categorical_crossentropy.Hpp
+ * Revision:          0.1.0
+ * Date:              28-07-2026
+ * Author:            Michelle Bausager
+ *
+ * Description:
+ * Defines the combined activation function softmax and 
+ * categorical crossentropy loss used in neural network
+ *
+ *++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*/
+#pragma once
+
+//---------------------------------------------------------------------------------------------------------------------------
+// INCLUDE DESCRIPTION
+//---------------------------------------------------------------------------------------------------------------------------
+#include <config/types.hpp> // panic::uint_t, panic::int_t, and panic::real_t
+#include <tensor/vector.hpp>
+#include <tensor/matrix.hpp>
+
+#include <neural_network/activation/activation_softmax.hpp>
+#include <neural_network/loss/loss_categorical_crossentropy.hpp>
+
+
+namespace panic{
+	namespace neural_network{
+
+/**
+ * @brief struct for activation_softmax_loss_categorical_crossentropy object used in neural networks
+ * 
+ *
+ * The struct is used in PANIC nural_network library.
+ */
+struct activation_softmax_loss_categorical_crossentropy: loss{
+
+     activation_softmax activation;
+     loss_categorical_crossentropy loss;
+
+     /**
+     * @brief Emphty matrix to store input data for bacward pass
+     *
+     */
+    panic::tensor::real_matrix dinputs;
+
+     /**
+     * @brief Emphty matrix to store output data
+     *
+     */
+    panic::tensor::real_matrix outputs;
+
+
+
+    /**
+     * @brief Empthy constructor
+     *
+     */
+	activation_softmax_loss_categorical_crossentropy();
+
+    /**
+     * @brief Default de-constructor
+     *
+     */
+	~activation_softmax_loss_categorical_crossentropy() = default;
+
+    /**
+     * @brief forward function to calculate losses
+     *
+     * @param y_pred Matrix of model predection.  
+     * @param y_true Vector of true label of data.
+     * 
+     */
+     bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::uint_vector& y_true);
+
+    /**
+     * @brief forward function to calculate losses
+     *
+     * @param y_pred Matrix of model predection.  
+     * @param y_true Vector of true label of data.
+     * 
+     * @Note Overloaded if one-shot endcoded
+     *         is used.
+     */
+    bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true);
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+    /**
+     * @brief forward function to calculate losses
+     *
+     * @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 forward function to calculate losses
+     *
+     * @param y_pred Matrix of model predection.  
+     * @param y_true Vector of true label of data.
+     * 
+     * @Note Overloaded if one-shot endcoded
+     *         is used.
+     */
+    bool calculate(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true);
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+    /**
+     * @brief backward function to calculate from losses
+     *
+     * @param y_pred Matrix of model predection.  
+     * @param y_true Vector of true label of data.
+     * 
+     */
+    bool backward(const panic::tensor::real_matrix& dvalues, const panic::tensor::uint_vector& y_true);
+
+    /**
+     * @brief backward function to calculate from losses
+     *
+     * @param y_pred Matrix of model predection.  
+     * @param y_true Vector of true label of data.
+     * 
+     * @Note Overloaded if one-shot endcoded
+     *         is used.
+     */
+    bool backward(const panic::tensor::real_matrix& dvalues, const panic::tensor::real_matrix& y_true);
+
+
+
+
+};
+
+
+	} // namespace tensor
+} // namespace panic
+
+//---------------------------------------------------------------------------------------------------------------------------
+// VARIABLE DESCRIPTION
+//---------------------------------------------------------------------------------------------------------------------------
+
+//---------------------------------------------------------------------------------------------------------------------------
+// FUNCTION PROTOTYPE
+//---------------------------------------------------------------------------------------------------------------------------
+
+