Activation Softmax Forward done

main.cpp

@@ -50,14 +50,14 @@
 
 #include <math/mul.hpp>
 #include <math/clip.hpp>
-#include <neural_network/activation/activation_ReLU.hpp>
+#include <neural_network/activation/activation_relu.hpp>
 #include <tensor/generators/linspace.hpp>
 #include <math/trigonometry/sin.hpp>
 #include <neural_network/datasets/sine_data.hpp>
 #include <neural_network/datasets/spiral_data.hpp>
 #include <neural_network/datasets/vertical_data.hpp>
 #include <math/exp.hpp>
-
+#include <math/sub.hpp>
 
 #include <math.h>
 
@@ -708,24 +708,33 @@ int main(void) {
     panic::tensor::real_matrix X;
     panic::tensor::uint_vector y;
 
-    panic::types::uint_t samples = 100;
+    panic::types::uint_t samples = 10;
     panic::types::uint_t classes = 3;
 
+
+    // create spiral data
     panic::neural_network::spiral_data(samples, classes, X, y);
 
+    // Initilise my model
     panic::neural_network::model mymodel;
 
     // Create Dense layer with 2 input features and 3 output values
     mymodel.add_layer_dense(2,3);
     
-    mymodel.add_activation_ReLU();
+    // Create an activation ReLU layer 
+    mymodel.add_activation_relu();
+
+    // Create a second dense layer with 3 inputs and 3 outputs
+    mymodel.add_layer_dense(3, 3);
+
+    // Create activation softmax layer
+    mymodel.add_activation_softmax();
 
     mymodel.forward(X); 
 
-    //panic::io::print_matrix(mymodel.outputs);
+    panic::io::print_matrix(mymodel.outputs);
+
 
-    std::cout << panic::math::exp(15.5f) << std::endl;
-    std::cout << std::exp(15.5) << std::endl;
 
 
 	return 0;