Änderung an neuralesNetwork.c vorgenommen, weil es die Funktion aus

matrix.c falsch benutzt hat

Startcode/neuralNetwork.c

@@ -67,14 +67,14 @@ static unsigned int readDimension(FILE *file)
 
     if(fread(&dimension, sizeof(int), 1, file) != 1)
         dimension = 0;
-    
+
     return dimension;
 }
 
 static Matrix readMatrix(FILE *file, unsigned int rows, unsigned int cols)
 {
     Matrix matrix = createMatrix(rows, cols);
-    
+
     if(matrix.buffer != NULL)
     {
         if(fread(matrix.buffer, sizeof(MatrixType), rows*cols, file) != rows*cols)
@@ -128,7 +128,7 @@ NeuralNetwork loadModel(const char *path)
     {
         if(checkFileHeader(file))
         {
-            unsigned int inputDimension = readDimension(file); 
+            unsigned int inputDimension = readDimension(file);
             unsigned int outputDimension = readDimension(file);
 
             while(inputDimension > 0 && outputDimension > 0)
@@ -142,7 +142,7 @@ NeuralNetwork loadModel(const char *path)
                     clearModel(&model);
                     break;
                 }
-                
+
                 layerBuffer = (Layer *)realloc(model.layers, (model.numberOfLayers + 1) * sizeof(Layer));
 
                 if(layerBuffer != NULL)
@@ -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)
     {
@@ -201,7 +201,7 @@ static Matrix forward(const NeuralNetwork model, Matrix inputBatch)
         {
             Matrix biasResult;
             Matrix weightResult;
-            
+
             weightResult = multiply(model.layers[i].weights, result);
             clearMatrix(&result);
             biasResult = add(model.layers[i].biases, weightResult);
@@ -248,9 +248,9 @@ unsigned char *predict(const NeuralNetwork model, const GrayScaleImage images[],
     Matrix outputBatch = forward(model, inputBatch);
 
     unsigned char *result = argmax(outputBatch);
-    
+
     clearMatrix(&outputBatch);
-    
+
     return result;
 }
 
@@ -265,4 +265,4 @@ void clearModel(NeuralNetwork *model)
         model->layers = NULL;
         model->numberOfLayers = 0;
     }
-}
+}