From e30b15e43b3206b76964d8b78489e561a8b672ce Mon Sep 17 00:00:00 2001
From: "szewczyk.franciszek02" <szewczyk.franciszek02@gmail.com>
Date: Wed, 8 Nov 2023 19:27:33 +0100
Subject: [PATCH] Iterating with references

---
 examples/xor_classification.cpp   | 4 ++--
 include/nn/Neuron.hpp             | 4 ++--
 include/nn/activation/Exp.hpp     | 2 +-
 include/nn/activation/ReLU.hpp    | 2 +-
 include/nn/activation/Sigmoid.hpp | 2 +-
 include/nn/activation/Softmax.hpp | 4 ++--
 include/nn/activation/Tanh.hpp    | 2 +-
 7 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/examples/xor_classification.cpp b/examples/xor_classification.cpp
index e8cd162..30ff5fa 100644
--- a/examples/xor_classification.cpp
+++ b/examples/xor_classification.cpp
@@ -16,7 +16,7 @@ int main() {
     auto mlp = SequentialBuilder<Type::float32>::begin()
                 .add(Linear32::create(2, 15))
                 .add(ReLU32::create())
-                .add(Dropout32::create(15, 5, 0.3))
+                .add(Dropout32::create(15, 5, 0.2))
                 .add(Tanh32::create())
                 .add(Linear32::create(5, 2))
                 .add(Softmax32::create())
@@ -27,7 +27,7 @@ int main() {
     Loss::Function32 lossFunction = Loss::CrossEntropy<Type::float32>;
 
     // ------ TRAINING THE NETWORK ------- //
-    for (size_t epoch = 0; epoch < 500; epoch++) {
+    for (size_t epoch = 0; epoch < 100; epoch++) {
         auto epochLoss = Val32::create(0);
 
         optimizer.reset();
diff --git a/include/nn/Neuron.hpp b/include/nn/Neuron.hpp
index a4cefa5..6d148de 100644
--- a/include/nn/Neuron.hpp
+++ b/include/nn/Neuron.hpp
@@ -46,8 +46,8 @@ template <typename T> std::vector<ValuePtr<T>> Neuron<T>::parameters() const {
     std::vector<ValuePtr<T>> params;
     params.reserve(_weights.size() + 1);
 
-    for (size_t i = 0; i < _weights.size(); ++i)
-        params.push_back(_weights[i]);
+    for (auto &w : _weights)
+        params.push_back(w);
 
     params.push_back(_bias);
 
diff --git a/include/nn/activation/Exp.hpp b/include/nn/activation/Exp.hpp
index 15521cf..b97bd1d 100644
--- a/include/nn/activation/Exp.hpp
+++ b/include/nn/activation/Exp.hpp
@@ -28,7 +28,7 @@ template <typename T> Vector<T> Exp<T>::operator()(const Vector<T> &x) const {
     std::vector<ValuePtr<T>> out;
     out.reserve(x.size());
 
-    for (auto entry : x)
+    for (auto &entry : x)
         out.emplace_back(entry->exp());
 
     return Vector<T>(out);
diff --git a/include/nn/activation/ReLU.hpp b/include/nn/activation/ReLU.hpp
index dfdce01..7c0f32b 100644
--- a/include/nn/activation/ReLU.hpp
+++ b/include/nn/activation/ReLU.hpp
@@ -28,7 +28,7 @@ template <typename T> Vector<T> ReLU<T>::operator()(const Vector<T> &x) const {
     std::vector<ValuePtr<T>> out;
     out.reserve(x.size());
 
-    for (auto entry : x)
+    for (auto &entry : x)
         out.emplace_back(entry->relu());
 
     return Vector<T>(out);
diff --git a/include/nn/activation/Sigmoid.hpp b/include/nn/activation/Sigmoid.hpp
index 6679421..cbc4ed7 100644
--- a/include/nn/activation/Sigmoid.hpp
+++ b/include/nn/activation/Sigmoid.hpp
@@ -30,7 +30,7 @@ template <typename T> Vector<T> Sigmoid<T>::operator()(const Vector<T> &x) const
     std::vector<ValuePtr<T>> out;
     out.reserve(x.size());
 
-    for (auto entry : x) {
+    for (auto &entry : x) {
         out.emplace_back(entry->sigmoid());
     }
 
diff --git a/include/nn/activation/Softmax.hpp b/include/nn/activation/Softmax.hpp
index eb581b7..004a99c 100644
--- a/include/nn/activation/Softmax.hpp
+++ b/include/nn/activation/Softmax.hpp
@@ -31,12 +31,12 @@ template <typename T> Vector<T> Softmax<T>::operator()(const Vector<T> &x) const
     out.reserve(x.size());
 
     auto maxValue = Value<T>::create(x[0]->getValue());
-    for (auto entry : x)
+    for (auto &entry : x)
         if (entry > maxValue)
             maxValue = entry;
 
     auto sumExponentiated = Value<T>::create(0);
-    for (auto entry : x) {
+    for (auto &entry : x) {
         auto exponentiated = (entry - maxValue)->exp();
         out.emplace_back(exponentiated);
         sumExponentiated = sumExponentiated + exponentiated;
diff --git a/include/nn/activation/Tanh.hpp b/include/nn/activation/Tanh.hpp
index ad77677..5066526 100644
--- a/include/nn/activation/Tanh.hpp
+++ b/include/nn/activation/Tanh.hpp
@@ -28,7 +28,7 @@ template <typename T> Vector<T> Tanh<T>::operator()(const Vector<T> &x) const {
     std::vector<ValuePtr<T>> out;
     out.reserve(x.size());
 
-    for (auto entry : x)
+    for (auto &entry : x)
         out.emplace_back(entry->tanh());
 
     return Vector<T>(out);