From ae1da7bfd96cac37895654f262601e8f95bd14ba Mon Sep 17 00:00:00 2001
From: sosokker <sirin_29@hotmail.co.th>
Date: Sat, 26 Aug 2023 02:09:42 +0700
Subject: [PATCH] Update include path/ Change function  type in Loss

---
 src/Layers/DenseLayer.hpp |  2 +-
 src/Layers/Layers.hpp     |  2 +-
 src/Loss/Loss.cpp         | 10 +++++-----
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/Layers/DenseLayer.hpp b/src/Layers/DenseLayer.hpp
index b2d30e4..fafc1fd 100644
--- a/src/Layers/DenseLayer.hpp
+++ b/src/Layers/DenseLayer.hpp
@@ -1,4 +1,4 @@
-#include <Eigen/Dense>
+#include "../../include/Eigen/Dense"
 #include "Layers.hpp"
 
 class DenseLayer : public Layer {
diff --git a/src/Layers/Layers.hpp b/src/Layers/Layers.hpp
index a5f1239..6a4d40b 100644
--- a/src/Layers/Layers.hpp
+++ b/src/Layers/Layers.hpp
@@ -1,7 +1,7 @@
 #ifndef LAYERS_HPP
 #define LAYERS_HPP
 
-#include <Eigen/Dense>
+#include "../../include/Eigen/Dense"
 
 class Layer {
 public:
diff --git a/src/Loss/Loss.cpp b/src/Loss/Loss.cpp
index 6c261c4..bbf972f 100644
--- a/src/Loss/Loss.cpp
+++ b/src/Loss/Loss.cpp
@@ -1,16 +1,16 @@
-#include <Eigen/Dense>
+#include "../../include/Eigen/Dense"
 #include <cmath>
 
-double mse(const Eigen::VectorXd& y_true, const Eigen::VectorXd& y_pred) {
-    return (y_true - y_pred).squaredNorm() / y_true.size();
+Eigen::VectorXd mse(const Eigen::VectorXd& y_true, const Eigen::VectorXd& y_pred) {
+    return (y_true - y_pred).array().square() / y_true.size();
 }
 
 Eigen::VectorXd mse_prime(const Eigen::VectorXd& y_true, const Eigen::VectorXd& y_pred) {
     return 2.0 * (y_pred - y_true) / y_true.size();
 }
 
-double binary_cross_entropy(const Eigen::VectorXd& y_true, const Eigen::VectorXd& y_pred) {
-    return -((y_true.array() * y_pred.array().log()) + ((1 - y_true.array()) * (1 - y_pred.array()).log())).mean();
+Eigen::VectorXd binary_cross_entropy(const Eigen::VectorXd& y_true, const Eigen::VectorXd& y_pred) {
+    return -((y_true.array() * y_pred.array().log()) + ((1 - y_true.array()) * (1 - y_pred.array()).log())) / y_true.size();
 }
 
 Eigen::VectorXd binary_cross_entropy_prime(const Eigen::VectorXd& y_true, const Eigen::VectorXd& y_pred) {