Next up is dropout layers

include/neural_network/model/model.hpp

@@ -205,10 +205,12 @@ struct model{
      *
      * @note This function is convenient, but it allocates a new layer.
      */
-    bool add_layer_dense(
-        panic::types::uint_t input_size,
-        panic::types::uint_t neuron_count
-    );
+    bool add_layer_dense(panic::types::uint_t input_size, 
+                panic::types::uint_t neurons,
+                panic::types::real_t weight_regularizer_l1 = 0,
+                panic::types::real_t weight_regularizer_l2 = 0,
+                panic::types::real_t bias_regularizer_l1 = 0,
+                panic::types::real_t bias_regularizer_l2 = 0);
 
     /**
      * @brief Adds a activation ReLU layer to the model.
@@ -412,6 +414,18 @@ struct model{
      */
     bool optimize();
 
+    /**
+     * @brief  Calculates regulaization for parameters on trainable layers
+     *
+     * Computes:
+     * @code
+     * model.calculate_regularization_loss()
+     * @endcode
+     *
+     * @return true if optimization is done correctly.
+     *
+     */
+    bool calculate_regularization_loss(panic::types::real_t& regularization_loss);
 
 
     /**