prepareNeuralNetwork initial implementation

Startcode/neuralNetwork.c

@@ -170,7 +170,7 @@ NeuralNetwork loadModel(const char *path)
 
 static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count)
 {
-    Matrix matrix = {NULL, 0, 0};
+    Matrix matrix = {0, 0, NULL};
 
     if(count > 0 && images != NULL)
     {

Startcode/neuralNetworkTests.c

@@ -4,11 +4,27 @@
 #include <math.h>
 #include "unity.h"
 #include "neuralNetwork.h"
-
+#define FILE_HEADER_STRING "__info2_neural_network_file_format__"
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *fd = fopen(path, "wb");
+
+    if (fd == NULL)
+        return;
+
+    fwrite(FILE_HEADER_STRING, sizeof(FILE_HEADER_STRING) - 1, 1, fd);
+    // fwrite(&nn, sizeof(nn), 1, fd);
+    fwrite(&(nn.layers[0].weights.cols), sizeof(nn.layers[0].weights.cols), 1, fd);
+    for (int i = 0; i < nn.numberOfLayers; ++i)
+    {
+        fwrite(&(nn.layers[i].weights.rows), sizeof(nn.layers[i].weights.rows), 1, fd);
+        fwrite(&(nn.layers[i].weights.buffer), sizeof(MatrixType) * nn.layers[i].weights.rows * nn.layers[i].weights.cols, 1, fd);
+        fwrite(&(nn.layers[i].biases.buffer), sizeof(MatrixType) * nn.layers[i].biases.rows, 1, fd);
+    }
+    const float zeroooooo = 0.0F;
+    fwrite(&zeroooooo, sizeof(MatrixType), 1, fd);
+    fclose(fd);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)