Merge pull request #11 from C-Text/feature/neural_network

Close #9

.github/workflows/main.yml

@@ -7,5 +7,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v2
-    - name: make
-      run: make      
+    - name: CMake the project
+      run: cmake .
+    - name: Make the projet
+      run: make

CMakeLists.txt

@@ -0,0 +1,32 @@
+cmake_minimum_required(VERSION 3.17)
+project(CText C)
+
+set(CMAKE_C_STANDARD 99)
+
+add_executable(
+        CText src/main.c
+        src/neuralnetwork/neuron.c src/neuralnetwork/neuron.h
+        src/neuralnetwork/function.c src/neuralnetwork/function.h
+        src/neuralnetwork/layer.c src/neuralnetwork/layer.h
+        src/util.c src/util.h
+)
+
+add_executable(
+        CText-tests src/test/main.c
+        src/neuralnetwork/neuron.c src/neuralnetwork/neuron.h
+        src/neuralnetwork/function.c src/neuralnetwork/function.h
+        src/neuralnetwork/layer.c src/neuralnetwork/layer.h
+        src/util.c src/util.h
+        src/test/test.c src/test/test.h
+        src/test/test_method.c src/test/test_method.h
+)
+
+target_link_libraries(CText m)
+target_link_libraries(CText-tests m)
+
+if ( CMAKE_COMPILER_IS_GNUCC )
+    set(CMAKE_CXX_FLAGS  "${CMAKE_CXX_FLAGS} -Wall -Wextra -Wshadow -Wdouble-promotion -Wformat=2 -Wformat-truncation -Wformat-overflow -Wundef -fno-common -Wconversion")
+endif()
+if ( MSVC )
+    set(CMAKE_CXX_FLAGS  "${CMAKE_CXX_FLAGS} /W4")
+endif()

README

@@ -1,22 +1,33 @@
-CText
+====== CText ======
 
-This is a school project.
+= Clone =
 
-Depandencies :
+git clone https://github.com/C-Text/CText.git
+
+= Dependencies =
 
 gcc
+cmake
+make
+
+= Build =
+cmake .
 make
 
-Prepare the project :
+= Launch =
+./CText
+./CText-tests
+
+= Contribute =
 
-git clone git@github.com:C-Text/CText.git
+git clone https://github.com/C-Text/CText.git
 git flow init
 
 
-Create a new feature :
+= Create a new feature =
 
 git flow feature start <my_feature>
 
 
-Finish a feature :
+= Finish a feature =
 Open a Pull Request -> base: develop, compare: feature/<my_feature>

src/main.c

@@ -0,0 +1,50 @@
+#include "neuralnetwork/layer.h"
+#include <stdio.h>
+
+void prints(layer *l1, layer *l2) {
+  lprint(l1, true);
+  printf("\n");
+  lprint(l2, true);
+  printf("\n");
+}
+
+void test(int ** arr) {
+  for (int i = 0; i < 5; ++i) {
+    printf("%d", arr[i][i]);
+  }
+}
+
+int main(void) {
+  const unsigned int EPOCHS = 100;
+  // XOR table
+  double inputs[4][2] = {
+      {0.0, 0.0},
+      {0.0, 1.0},
+      {1.0, 0},
+      {1.0, 1.0}
+  };
+  double outputs[4] = {0.0, 1.0, 1.0, 0.0};
+  // Creating layers
+  layer l = create_layer(2, 1);
+  layer l2 = create_layer(1, 1);
+
+  // Input
+  feed(&l, inputs[1]);
+  printf("================== INPUT ==================\n");
+  prints(&l,&l2);
+
+  // Activate the layer
+  activate(&l);
+  printf("================== ACTIV ==================\n");
+  prints(&l,&l2);
+
+  //Feed forward
+  feedforward(&l,&l2);
+  printf("================== FEEDF ==================\n");
+  prints(&l,&l2);
+
+  double out = sum(&l2, 0);
+  printf("OUTPUT: %lf", out);
+
+  return 0;
+}

src/neuralnetwork/function.c

@@ -0,0 +1,57 @@
+#include "function.h"
+#include "../util.h"
+#include <math.h>
+
+/**
+ * Softmax activation.
+ *
+ * @date    25/10/2020
+ * @version 0.0.1
+ * @author  Vinetos
+ * @package network
+ *
+ * This method activates the given input array using the softmax
+ * classification method.
+ *
+ * @warning This method modify the given array.
+ *
+ * @throw error  when size < 0.
+ * @param inputs the arrays of values to activate.
+ * @param size   the size of the array
+ *
+ */
+void softmax(double *inputs, size_t size) {
+  if (size == 0)
+    return;
+
+  double m = find_min(inputs, size);
+
+  double sum = 0.0;
+  for (size_t i = 0; i < size; ++i)
+    sum += exp(inputs[i] - m);
+
+  double constant = m + log(sum);
+  for (size_t i = 0; i < size; ++i)
+    inputs[i] = exp(inputs[i] - constant);
+}
+
+/**
+ * Mean squared error.
+ *
+ * @date    25/10/2020
+ * @version 0.0.1
+ * @author  Vinetos
+ * @package network
+ *
+ * This method calculate the mean squared error between the input and the
+ * expected output.
+ *
+ * @param input      The activated value of the neuron
+ * @param expected   The expected value
+ *
+ * @return the mean squared error value.
+ */
+double mse(double input, double expected) {
+  double diff = expected - input;
+  return diff * diff;
+}

src/neuralnetwork/function.h

@@ -0,0 +1,44 @@
+#ifndef CTEXT_SRC_NEURALNETWORK_FUNCTION_H_
+#define CTEXT_SRC_NEURALNETWORK_FUNCTION_H_
+
+#include <stdlib.h>
+
+/**
+ * Softmax activation.
+ *
+ * @date    25/10/2020
+ * @version 0.0.1
+ * @author  Vinetos
+ * @package network
+ *
+ * This method activates the given input array using the softmax
+ * classification method.
+ *
+ * @warning This method modify the given array.
+ *
+ * @throw error  when size < 0.
+ * @param inputs the arrays of values to activate.
+ * @param size   the size of the array
+ *
+ */
+void softmax(double *inputs, size_t size);
+
+/**
+ * Mean squared error.
+ *
+ * @date    25/10/2020
+ * @version 0.0.1
+ * @author  Vinetos
+ * @package network
+ *
+ * This method calculate the mean squared error between the input and the
+ * expected output.
+ *
+ * @param input      The activated value of the neuron
+ * @param expected   The expected value
+ *
+ * @return the mean squared error value.
+ */
+double mse(double input, double expected);
+
+#endif //CTEXT_SRC_NEURALNETWORK_FUNCTION_H_