Softmax + Categorical Crossentropy

I fixed the activation+loss function, you can't select it directly, it automaticly uses it if it can. I also fixed one-hot generator. Still haven't tested the activation + loss nor any other backward function. I'll do that when I get to the optimizers which is next.

include/neural_network/loss/loss.hpp

@@ -44,6 +44,11 @@ namespace panic{
 	namespace neural_network{
 
 
+enum struct loss_type {
+    unknown,
+    categorical_crossentropy
+};
+
 
 /**
  * @brief Base loss for the rest of the neural network library to use
@@ -58,7 +63,7 @@ namespace panic{
 struct loss{
 
 	 /**
-     * @brief Emphty vector to store sample losses
+     * @brief Emphty vector to store sample losses for each sample in the batch.
      *
      */
 	panic::tensor::real_vector sample_losses;
@@ -66,19 +71,15 @@ struct loss{
     /**
      * @brief Mean loss over the entire batch.
      */
-    panic::types::real_t data_loss;
+    panic::types::real_t data_loss = 0;
 
     /**
-     * @brief Matrix for backwards pass
+     * @brief Gradient with respect to the loss input.
+     *
+     * This will be used later during the backward pass.
      */
     panic::tensor::real_matrix dinputs;
 
-    /**
-     * @brief Matrix for output of loss function
-     */
-    panic::tensor::real_matrix outputs;
-
-
     /**
      * @brief Default de-constructor
      *
@@ -86,6 +87,16 @@ struct loss{
 	virtual ~loss() = default;
 
 
+    /**
+     * @brief Virtual loss_type function for derivative losses
+     *
+     * @Note This returns the type of loss it is
+     *    unknown be default
+     */
+    virtual loss_type get_type() const {
+        return loss_type::unknown;
+    }
+
     /**
      * @brief Virtual forward function for derivative loss functions
      *
@@ -146,7 +157,7 @@ struct loss{
      * @param y_true Vector of true label of data.
      * 
      */
-	virtual bool calculate(
+	bool calculate(
         const panic::tensor::real_matrix& y_pred, 
         const panic::tensor::uint_vector& y_true);
 
@@ -157,7 +168,7 @@ struct loss{
      * @param y_true Matrix of true label of data.
      * 
      */
-    virtual bool calculate(
+    bool calculate(
         const panic::tensor::real_matrix& y_pred, 
         const panic::tensor::real_matrix& y_true);
 

include/neural_network/loss/loss_categorical_crossentropy.hpp

@@ -53,10 +53,17 @@ namespace panic{
  * 
  * The struct is used for PANIC neural_network library.
  */
-struct loss_categorical_crossentropy: loss{
-
-
+struct loss_categorical_crossentropy: public loss{
 
+    /**
+     * @brief get_type function for loss
+     *
+     * @returns the loss type
+     * 
+     */
+    loss_type get_type() const override {
+        return loss_type::categorical_crossentropy;
+    }
 
     /**
      * @brief forward function to calculate losses
@@ -65,9 +72,7 @@ struct loss_categorical_crossentropy: loss{
      * @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)override;
+	bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::uint_vector& y_true) override;
 
     /**
      * @brief forward function to calculate losses
@@ -78,9 +83,7 @@ struct loss_categorical_crossentropy: loss{
      * @Note Overloaded if one-shot endcoded
      *         is used.
      */
-    bool forward(
-        const panic::tensor::real_matrix& y_pred, 
-        const panic::tensor::real_matrix& y_true)override;
+    bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true) override;
 
 
     /**
@@ -90,9 +93,7 @@ struct loss_categorical_crossentropy: loss{
      * @param y_true Vector of true label of data.
      * 
      */
-    bool backward(
-        const panic::tensor::real_matrix& dvalues, 
-        const panic::tensor::uint_vector& y_true) override;
+    bool backward(const panic::tensor::real_matrix& dvalues, const panic::tensor::uint_vector& y_true) override;
 
     /**
      * @brief backward function to calculate from losses
@@ -103,9 +104,7 @@ struct loss_categorical_crossentropy: loss{
      * @Note Overloaded if one-shot endcoded
      *         is used.
      */
-    bool backward(
-        const panic::tensor::real_matrix& dvalues, 
-        const panic::tensor::real_matrix& y_true) override;
+    bool backward(const panic::tensor::real_matrix& dvalues, const panic::tensor::real_matrix& y_true) override;
 
 
 };