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Maybe backward on activation+loss works

include/neural_network/activation_loss/activation_softmax_loss_categorical_crossentropy.hpp

@@ -59,19 +59,6 @@ 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
@@ -92,7 +79,7 @@ struct activation_softmax_loss_categorical_crossentropy: loss{
      * @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) override;
+     bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::uint_vector& y_true) override;
 
     /**
      * @brief forward function to calculate losses
@@ -103,74 +90,7 @@ struct activation_softmax_loss_categorical_crossentropy: loss{
      * @Note Overloaded if one-shot endcoded
      *         is used.
      */
-    bool calculate(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true) override;
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-    /**
-     * @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);
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+    bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true) override;
 
 
 

include/neural_network/loss/loss.hpp

@@ -112,6 +112,33 @@ struct loss{
         const panic::tensor::real_matrix& y_pred, 
         const panic::tensor::real_matrix& y_true);
 
+
+    /**
+     * @brief Virtual backward 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 backward(
+        const panic::tensor::real_matrix& y_pred, 
+        const panic::tensor::uint_vector& y_true);
+
+    /**
+     * @brief Virtual backward 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 backward(
+        const panic::tensor::real_matrix& y_pred, 
+        const panic::tensor::real_matrix& y_true);
+
     /**
      * @brief Virtual calculate function that calculates the loss
      *

include/neural_network/loss/loss_categorical_crossentropy.hpp

@@ -67,7 +67,7 @@ struct loss_categorical_crossentropy: loss{
      */
 	bool forward(
         const panic::tensor::real_matrix& y_pred, 
-        const panic::tensor::uint_vector& y_true);
+        const panic::tensor::uint_vector& y_true)override;
 
     /**
      * @brief forward function to calculate losses
@@ -80,7 +80,7 @@ struct loss_categorical_crossentropy: loss{
      */
     bool forward(
         const panic::tensor::real_matrix& y_pred, 
-        const panic::tensor::real_matrix& y_true);
+        const panic::tensor::real_matrix& y_true)override;
 
 
     /**