debugged

.vscode/launch.json

@@ -0,0 +1,33 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+    {
+        "name": "(gdb) Launch",
+        "type": "cppdbg",
+        "request": "launch",
+        "program": "${workspaceFolder}/mnist.exe",
+        "args": ["mnist_test.info2","mnist_model.info2"],
+        "stopAtEntry": false,
+        "cwd": "${fileDirname}",
+        "environment": [],
+        "externalConsole": false,
+        "MIMode": "gdb",
+        "miDebuggerPath": "C:\\msys64\\ucrt64\\bin\\gdb.exe",
+        "setupCommands": [
+            {
+                "description": "Enable pretty-printing for gdb",
+                "text": "-enable-pretty-printing",
+                "ignoreFailures": true
+            },
+            {
+                "description": "Set Disassembly Flavor to Intel",
+                "text": "-gdb-set disassembly-flavor intel",
+                "ignoreFailures": true
+            }
+        ]
+    }
+    ]
+}

imageInput.c

@@ -93,5 +93,5 @@ void clearSeries(GrayScaleImageSeries *series)
 
     free(series->images); // Speicher für die Bild-Array freigeben
     free(series->labels); // Speicher für die Labels freigeben
-    free(series);
+    free(series); // Speicher freigeben
 }

matrix.c

@@ -6,13 +6,13 @@
 
 Matrix createMatrix(unsigned int rows, unsigned int cols)
 {
-    Matrix m = {0, 0, NULL};
+    Matrix m = {NULL, 0, 0};
 
     if (rows > 0 && cols > 0)
     {
+        m.buffer = malloc(rows * cols * sizeof(MatrixType));
         m.rows = rows;
         m.cols = cols;
-        m.buffer = malloc(rows * cols * sizeof(int));
     }
 
     return m;
@@ -65,23 +65,11 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
         return result;
     }
 
-    result.rows = matrix1.rows;
-    result.cols = matrix1.cols;
-    result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
-
-    // wenn buffer nicht allokiert werden kann dann zurücksetzen und abbrechen
-    if (result.buffer == NULL)
-    {
-        result.rows = result.cols = 0;
-
-        return result;
-    }
 
     if (matrix1.cols == 1 && matrix1.rows == matrix2.rows) // Broadcasting
     {
-        result.rows = matrix2.rows;
+        result = createMatrix(matrix2.rows, matrix2.cols);
-        result.cols = matrix2.cols;
+
-        
         for (unsigned int i = 0; i < matrix1.rows; i++)
         {
             for (unsigned int j = 0; j < result.cols; j++)
@@ -95,8 +83,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
 
     else if (matrix2.cols == 1 && matrix1.rows == matrix2.rows) 
     {
-        result.rows = matrix1.rows;
+        result = createMatrix(matrix1.rows, matrix1.cols);
-        result.cols = matrix1.cols;
 
         for (unsigned int i = 0; i < matrix2.rows; i++)
         {
@@ -109,6 +96,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
 
     else
     {
+        result = createMatrix(matrix1.rows, matrix1.cols);
         // Elementweise Addition
         for (unsigned int i = 0; i < result.rows; i++)
         {

matrix.h

@@ -9,9 +9,9 @@ typedef float MatrixType;
 
 typedef struct 
 {
+    MatrixType *buffer;    // Zeiger auf die Matrixdaten 
     unsigned int rows;   // Anzahl der Zeilen
     unsigned int cols;   // Anzahl der Spalten
-    MatrixType *buffer;    // Zeiger auf die Matrixdaten 
 } Matrix;
 
 

neuralNetworkTests.c

@@ -8,7 +8,62 @@
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *file = fopen(path, "wb");
+    if (!file) {
+        perror("Fehler beim Erstellen der Testdatei");
+        exit(EXIT_FAILURE);
+    }
+
+    // File header
+    const char *fileTag = "__info2_neural_network_file_format__";
+    fwrite(fileTag, strlen(fileTag), 1, file);
+
+
+    if (nn.numberOfLayers == 0)
+    {
+        unsigned int zero = 0;
+        fwrite(&zero, sizeof(unsigned int), 1, file);
+        fclose(file);
+        return;
+    }
+
+    // first layer dimension
+    unsigned int in  = nn.layers[0].weights.cols;
+    unsigned int out = nn.layers[0].weights.rows;
+
+    fwrite(&in,  sizeof(unsigned int), 1, file);
+    fwrite(&out, sizeof(unsigned int), 1, file);
+
+    // do all layers
+    for (unsigned int i = 0; i < nn.numberOfLayers; i++)
+    {
+        const Layer *L = &nn.layers[i];
+
+        // Write weights matrix
+        fwrite(L->weights.buffer,
+               sizeof(MatrixType),
+               L->weights.rows * L->weights.cols,
+               file);
+
+        // Write biases matrix
+        fwrite(L->biases.buffer,
+               sizeof(MatrixType),
+               L->biases.rows * L->biases.cols,
+               file);
+
+        // After layer i, write dimension of next layer
+        if (i + 1 < nn.numberOfLayers)
+        {
+            unsigned int nextOut = nn.layers[i+1].weights.rows;
+            fwrite(&nextOut, sizeof(unsigned int), 1, file);
+        }
+    }
+
+    // --- 5. Write terminating zero ---
+    unsigned int zero = 0;
+    fwrite(&zero, sizeof(unsigned int), 1, file);
+
+    fclose(file);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)