Next up is dropout layers

main.cpp

@@ -706,9 +706,16 @@ int main(void) {
     panic::tensor::real_matrix X;
     panic::tensor::uint_vector y;
 
-    panic::types::uint_t samples = 100;
+    panic::types::uint_t samples = 1000;
     panic::types::uint_t classes = 3;
 
+    panic::types::uint_t layer_size = 256;
+
+
+    panic::types::real_t weight_regularizer_l1 = 0;
+    panic::types::real_t weight_regularizer_l2 = 5e-4;
+    panic::types::real_t bias_regularizer_l1 = 0;
+    panic::types::real_t bias_regularizer_l2 = 5e-4;
 
     // create spiral data 
     panic::neural_network::spiral_data(samples, classes, X, y);
@@ -718,7 +725,11 @@ int main(void) {
     panic::neural_network::model mymodel;
 
     // Create Dense layer with 2 input features and 3 output values
-    if (!mymodel.add_layer_dense(2,64)){
+    if (!mymodel.add_layer_dense(2,layer_size,
+                                    weight_regularizer_l1,
+                                    weight_regularizer_l2,
+                                    bias_regularizer_l1,
+                                    bias_regularizer_l2)){
         return false;
     }
     
@@ -726,9 +737,14 @@ int main(void) {
     if (!mymodel.add_activation_relu()){
         return false;
     }
+
     
     // Create a second dense layer with 3 inputs and 3 outputs
-    if (!mymodel.add_layer_dense(64, 3)){
+    if (!mymodel.add_layer_dense(layer_size, 3,
+                                    weight_regularizer_l1,
+                                    weight_regularizer_l2,
+                                    bias_regularizer_l1,
+                                    bias_regularizer_l2)){
         return false;
     }
     
@@ -769,7 +785,7 @@ int main(void) {
     }
     */
 
-    panic::types::real_t learning_rate = 0.02;
+    panic::types::real_t learning_rate = 0.001;
     panic::types::real_t decay = 1e-5;
     panic::types::real_t epsilon = 1e-7;
     panic::types::real_t beta_1 = 0.9;
@@ -794,5 +810,11 @@ int main(void) {
     }
 
 
+    
+
+
+    
+
+
 	return 0;
 }