load first commit

main.c

@@ -1,12 +1,29 @@
 #include <stdio.h>
-#include <stdio.h>
-#include <malloc.h>
 
 #include "matrix.h"
 #include "image.h"
+#include "neuronal_network.h"
 
 int main() {
-    Image** images = import_images("../data/train-images.idx3-ubyte", "../data/train-labels.idx1-ubyte", NULL, 2);
+//    Image** images = import_images("../data/train-images.idx3-ubyte", "../data/train-labels.idx1-ubyte", NULL, 2);
-    img_visualize(images[1]);
+//    img_visualize(images[1]);
+
+//    Neural_Network* nn = new_network(4, 2, 3, 0.5);
+//
+//    int n = 20;
+//
+//    matrix_randomize(nn->bias_1, n);
+//    matrix_randomize(nn->bias_2, n);
+//    matrix_randomize(nn->bias_3, n);
+//
+//    matrix_randomize(nn->weights_1, n);
+//    matrix_randomize(nn->weights_2, n);
+//    matrix_randomize(nn->weights_3, n);
+//
+//    matrix_randomize(nn->weights_output, n);
+//
+//    save_network(nn);
+
+    Neural_Network* nn = load_network("../networks/test1.txt");
 
 }

matrix.c

@@ -339,20 +339,20 @@ int matrix_argmax(Matrix* matrix) {
 }
 
 void matrix_randomize(Matrix* matrix, int n) {
+
     //make a min and max
-    int min = -1.0 / sqrt(n);
+    double min = -1.0f / sqrt(n);
-    int max = 1.0 / sqrt(n);
+    double max = 1.0f / sqrt(n);
+
     //calculate difference
     double difference = max - min;
+
     //move decimal
-    int scale = 10000;
+    int scaled_difference = (int)(difference * scaling_value);
-    int scaled_difference = (int)(difference * scale);
-    //calculate final random int and move decimal back
-    double random_result = min + (1.0 * (rand() % scaled_difference) / scale );
     
     for (int i = 0; i < matrix->rows; i++) {
         for (int j = 0; j < matrix->columns; j++) {
-            matrix->numbers[i][j] = random_result;
+            matrix->numbers[i][j] = min + (1.0 * (rand() % scaled_difference) / scaling_value);
         }
     }
 }

matrix.h

@@ -5,6 +5,8 @@ typedef struct {
     double **numbers;
 } Matrix;
 
+static const int scaling_value = 10000;
+
 // operational functions
 Matrix* matrix_create(int rows, int columns);
 void matrix_fill(Matrix* matrix, double value);

networks/test1.txt

@@ -0,0 +1,45 @@
+4
+2
+3
+2
+1
+-0.2195067977
+-0.1657067977
+2
+4
+0.0297932023
+0.0289932023
+-0.2106067977
+-0.0132067977
+-0.1003067977
+-0.0923067977
+-0.1315067977
+0.1174932023
+2
+1
+-0.0374067977
+0.1903932023
+2
+2
+-0.1219067977
+-0.1745067977
+0.0758932023
+0.0761932023
+2
+1
+-0.0955067977
+0.0071932023
+2
+2
+-0.1881067977
+-0.1272067977
+-0.1149067977
+-0.1048067977
+3
+2
+0.1665932023
+-0.2083067977
+-0.1944067977
+0.1201932023
+0.1768932023
+-0.1408067977

neuronal_network.c

@@ -39,11 +39,7 @@ void free_network(Neural_Network* network){
 
 void save_network(Neural_Network* network) {
 
-    // create file name and file string
+    char* file_name = "../networks/newest_network.txt";
-    time_t seconds;
-    time(&seconds);
-    char* file_name = "../networks/";
-    sprintf(file_name, "%ld", seconds);
 
     // create file
     FILE* save_file = fopen(file_name, "w");
@@ -81,7 +77,31 @@ void save_network(Neural_Network* network) {
 }
 
 Neural_Network* load_network(char* file) {
-    return NULL;
+
+    // create file pointer and open file
+    FILE* save_file = fopen(file, "r");
+
+    // check if file could be opened
+    if(save_file == NULL) {
+        printf("ERROR: File could not be opened/found! (load_network)");
+        exit(1);
+    }
+
+    // read & store the information on the size of the network from the save file
+    char buffer[MAX_BYTES];
+    fgets(buffer, MAX_BYTES, save_file);
+    int input_size = (int) strtol(buffer, NULL, 10);
+    fgets(buffer, MAX_BYTES, save_file);
+    int hidden_size = (int) strtol(buffer, NULL, 10);
+    fgets(buffer, MAX_BYTES, save_file);
+    int output_size = (int) strtol(buffer, NULL, 10);
+
+    // create a new network to fill with the saved data
+    Neural_Network* saved_network = new_network(input_size, hidden_size, output_size, 0);
+
+
+
+    return saved_network;
 }
 
 //double predict_images(Neural_Network* network, Image** images, int amount) {
@@ -117,5 +137,5 @@ Neural_Network* load_network(char* file) {
 //    return result;
 //}
 
-void train_network(Neural_Network* network, Matrix* input, Matrix* output);
+//void train_network(Neural_Network* network, Matrix* input, Matrix* output);
-void batch_train_network(Neural_Network* network, Image** images, int size);
+//void batch_train_network(Neural_Network* network, Image** images, int size);

neuronal_network.h

@@ -25,6 +25,8 @@ typedef struct {
 
 } Neural_Network;
 
+static const int MAX_BYTES = 100;
+
 Neural_Network* new_network(int input_size, int hidden_size, int output_size, double learning_rate);
 //void print_network(Neural_Network* network);
 void free_network(Neural_Network* network);