From 318d8945eca700a67681768f485ba20adc86de74 Mon Sep 17 00:00:00 2001
From: sosokker <sirin_29@hotmail.co.th>
Date: Sat, 26 Aug 2023 02:08:46 +0700
Subject: [PATCH] Update include path in utilscpp/ add train func/ Add header
 to include

---
 include/Layers/DenseLayer.hpp | 17 +++++++++++++++++
 include/utils/utils.hpp       | 20 ++++++++++++++++++++
 src/utils/utils.cpp           |  4 ++--
 src/utils/utils.hpp           | 20 ++++++++++++++++++++
 4 files changed, 59 insertions(+), 2 deletions(-)
 create mode 100644 include/Layers/DenseLayer.hpp
 create mode 100644 include/utils/utils.hpp
 create mode 100644 src/utils/utils.hpp

diff --git a/include/Layers/DenseLayer.hpp b/include/Layers/DenseLayer.hpp
new file mode 100644
index 0000000..b2d30e4
--- /dev/null
+++ b/include/Layers/DenseLayer.hpp
@@ -0,0 +1,17 @@
+#include <Eigen/Dense>
+#include "Layers.hpp"
+
+class DenseLayer : public Layer {
+public:
+    DenseLayer(int input_size, int output_size);
+
+    void forward(const Eigen::VectorXd& input) override;
+    void backward(const Eigen::VectorXd& output_gradient, double learning_rate) override;
+
+    const Eigen::VectorXd& getOutput() const;
+    const Eigen::VectorXd& getInputGradient() const;
+
+private:
+    Eigen::MatrixXd weights;
+    Eigen::VectorXd bias;
+};
diff --git a/include/utils/utils.hpp b/include/utils/utils.hpp
new file mode 100644
index 0000000..678e996
--- /dev/null
+++ b/include/utils/utils.hpp
@@ -0,0 +1,20 @@
+#ifndef NEURAL_NETWORK_UTILS_HPP
+#define NEURAL_NETWORK_UTILS_HPP
+
+#include <vector>
+#include <functional>
+#include <Eigen/Dense>
+#include <Layers/Layers.hpp>
+
+Eigen::VectorXd predict(const std::vector<Layer*>& network, const Eigen::VectorXd& input);
+
+void train(std::vector<Layer*>& network,
+           const std::function<Eigen::VectorXd(const Eigen::VectorXd&, const Eigen::VectorXd&)>& loss,
+           const std::function<Eigen::VectorXd(const Eigen::VectorXd&, const Eigen::VectorXd&)>& loss_prime,
+           const std::vector<Eigen::VectorXd>& x_train,
+           const std::vector<Eigen::VectorXd>& y_train,
+           int epochs = 1000,
+           double learning_rate = 0.01,
+           bool verbose = true);
+
+#endif // NEURAL_NETWORK_UTILS_HPP
diff --git a/src/utils/utils.cpp b/src/utils/utils.cpp
index c853a7a..28f1c33 100644
--- a/src/utils/utils.cpp
+++ b/src/utils/utils.cpp
@@ -1,8 +1,8 @@
 #include <iostream>
 #include <vector>
 #include <functional>
-#include <Eigen/Dense>
-#include <Layers/Layers.hpp>
+#include "../../include/Eigen/Dense"
+#include "../Layers/Layers.hpp"
 
 Eigen::VectorXd predict(const std::vector<Layer*>& network, const Eigen::VectorXd& input) {
     Eigen::VectorXd output = input;
diff --git a/src/utils/utils.hpp b/src/utils/utils.hpp
new file mode 100644
index 0000000..01b8261
--- /dev/null
+++ b/src/utils/utils.hpp
@@ -0,0 +1,20 @@
+#ifndef NEURAL_NETWORK_UTILS_HPP
+#define NEURAL_NETWORK_UTILS_HPP
+
+#include <vector>
+#include <functional>
+#include "../../include/Eigen/Dense"
+#include "../Layers/Layers.hpp"
+
+Eigen::VectorXd predict(const std::vector<Layer*>& network, const Eigen::VectorXd& input);
+
+void train(std::vector<Layer*>& network,
+           const std::function<Eigen::VectorXd(const Eigen::VectorXd&, const Eigen::VectorXd&)>& loss,
+           const std::function<Eigen::VectorXd(const Eigen::VectorXd&, const Eigen::VectorXd&)>& loss_prime,
+           const std::vector<Eigen::VectorXd>& x_train,
+           const std::vector<Eigen::VectorXd>& y_train,
+           int epochs = 1000,
+           double learning_rate = 0.01,
+           bool verbose = true);
+
+#endif // NEURAL_NETWORK_UTILS_HPP