matrix.c

@@ -2,8 +2,10 @@
 #include <stdlib.h>
 #include <stdio.h>
 #include <math.h>
+#include <time.h>
 #define MAX_BYTES 100
 
+static int RANDOMIZED = 0;
 // operational functions
 Matrix* matrix_create(int rows, int columns) {
 
@@ -17,7 +19,7 @@ Matrix* matrix_create(int rows, int columns) {
     // allocate memory for the numbers (2D-Array)
     matrix->numbers = malloc(sizeof(double*) * rows);
     for (int i = 0; i < rows; i++) {
-        matrix->numbers[i] = malloc(sizeof(double) * columns);
+        matrix->numbers[i] = calloc(sizeof(double), columns);
     }
 
     // return the pointer to the allocated memory
@@ -189,7 +191,8 @@ Matrix* apply(double (*function)(double), Matrix* matrix) {
     // apply the function to all values in the matrix
     for (int i = 0; i < matrix->rows; i++) {
         for (int j = 0; j < matrix->columns; j++) {
-            matrix->numbers[i][j] = (*function)(matrix->numbers[i][j]);
+            result_matrix->numbers[i][j] = (*function)(matrix->numbers[i][j]);
+            int k = 0;
         }
     }
 
@@ -350,6 +353,10 @@ int matrix_argmax(Matrix* matrix) {
 
 void matrix_randomize(Matrix* matrix, int n) {
 
+    if(!RANDOMIZED){
+        srand(time(NULL));
+        RANDOMIZED = 1;
+    }
     //make a min and max
     double min = -1.0f / sqrt(n);
     double max = 1.0f / sqrt(n);

neuronal_network.c

@@ -159,11 +159,10 @@ Matrix* predict(Neural_Network* network, Matrix* image_data) {
 //void batch_train_network(Neural_Network* network, Image** images, int size);
 
 double relu(double input) {
-    if (input < 0){
+    if (input <= 0){
         return 0.0;
     }
     return input;
-    //TODO: relu formel
 }
 
 Matrix* softmax(Matrix* matrix) {