Done with activation softmax backwards

main.cpp

@@ -59,6 +59,10 @@
 #include <math/exp.hpp>
 #include <math/sub.hpp>
 #include <neural_network/loss/loss_categorical_crossentropy.hpp>
+#include <math/log.hpp>
+#include <math/argmax.hpp>
+#include <math/equal.hpp>
+#include <math/mean.hpp>
 
 #include <math.h>
 
@@ -731,12 +735,35 @@ int main(void) {
     // Create activation softmax layer
     mymodel.add_activation_softmax();
 
-    mymodel.forward(X); 
+    // create loss function
+    panic::neural_network::loss_categorical_crossentropy loss_function;
 
-    panic::io::print_matrix(mymodel.outputs);
+    mymodel.forward(X);
+
+    loss_function.calculate(mymodel.outputs, y);
+
+    panic::tensor::uint_vector prediction;
+    prediction = panic::math::argmax_rowwise(mymodel.outputs);
+
+    panic::types::real_t accuracy;
+    panic::tensor::uint_vector comparisons;
+
+    comparisons = panic::math::equal(prediction, y);
+
+    accuracy = panic::math::mean(comparisons);
+
+    std::cout << "loss: " << loss_function.data_loss << std::endl;
+
+    std::cout << "acc: " << accuracy << std::endl;
 
 
 
+    
+
+    
+
+   
+
 
 	return 0;
 }