Started Loss, done softmax, up to p.125

I've implemented alot of support functions that needs to be refactored, optimised and tested; mean.h, exponential.h, matdiv.h matsum.h matsubtract.h. Maybe we need to have a look at if matdiv/matmul should be in the same. Same with matadd/matsubtract and if some of it should be in matvec.h.

include/modules/neural_networks/loss/Loss _CategoricalCrossentrophy.h

@@ -0,0 +1,34 @@
+#pragma once
+
+#include "./core/omp_config.h"
+
+#include "./utils/vector.h"
+#include "./utils/matrix.h"
+
+
+namespace neural_networks{
+
+	template <typename Td, typename Ti>
+	struct Loss{
+
+			utils::Matrix<Td> sample_losses;
+			Td data_losses;
+
+			virtual utils::Vector<Td> forward(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y) = 0;
+
+			Td calculate(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y){
+				// Calculate sample losses
+				sample_losses = forward(output, y);
+
+				// Calculate mean loss
+				data_losses = numerics::mean(sample_losses);
+				return data_losses;
+
+			}
+
+
+	};
+
+
+
+} // end namespace neural_networks

include/modules/neural_networks/loss/loss.h

@@ -0,0 +1,34 @@
+#pragma once
+
+#include "./core/omp_config.h"
+
+#include "./utils/vector.h"
+#include "./utils/matrix.h"
+
+
+namespace neural_networks{
+
+	template <typename Td, typename Ti>
+	struct Loss{
+
+			utils::Matrix<Td> sample_losses;
+			Td data_losses;
+
+			virtual utils::Vector<Td> forward(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y) = 0;
+
+			Td calculate(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y){
+				// Calculate sample losses
+				sample_losses = forward(output, y);
+
+				// Calculate mean loss
+				data_losses = numerics::mean(sample_losses);
+				return data_losses;
+
+			}
+
+
+	};
+
+
+
+} // end namespace neural_networks