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Author SHA1 Message Date
Simon Wiesend
3a9d8275a8
fix bug 2025-11-28 08:14:41 +01:00
Simon Wiesend
bbb0ea1cf5
Merge branch 'main' into neuralNetworkTests 2025-11-25 13:40:23 +01:00
Simon Wiesend
12825cc1d3
Revert "neuralNetwork fixed". The root cause has been fixed in matrix.h
This reverts commit 6ba9ba319592ac3aac15723ad549f1389b5c9718.
2025-11-25 13:38:56 +01:00
Simon Wiesend
633ee723f4
adapt matrix struct to existing tests 2025-11-25 13:33:20 +01:00
Fabrice
7ea80137b0 Header wird gelesen, läuft alles optimal 2025-11-24 10:35:46 +01:00
6ba9ba3195 neuralNetwork fixed 2025-11-24 08:24:37 +00:00
Fabrice
9c3d9f0a40 imageInput implementiert 2025-11-23 20:54:39 +01:00
f4427d2892 unittests bestanden 2025-11-23 16:38:17 +00:00
84b65525a6 Funktion implementiert / nicht getestet 2025-11-23 12:04:25 +00:00
Simon Wiesend
92ad1e1c31
clean up and improve allocation error handling 2025-11-21 09:09:55 +01:00
Simon Wiesend
6137e45bdb
Merge branch 'main' into matrix 2025-11-17 18:35:46 +01:00
Simon Wiesend
0d7f380d87
implement matmul 2025-11-14 09:17:31 +01:00
Simon Wiesend
645d471860
first implementation of new broadcasting addition requirement 2025-11-11 19:05:03 +01:00
721f5cc2d1 merge upstream 2025-11-11 12:55:12 +00:00
Simon Wiesend
79ad1285b5
This implements all functions in matrix.c except multiply(). All tests from matrixTests.c are passing for the implemented functions. 2025-11-09 13:43:06 +01:00
6 changed files with 269 additions and 18 deletions

3
.gitignore vendored
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@ -1,4 +1,5 @@
mnist mnist
runTests runTests
*.o *.o
*.exe *.exe
runMatrixTests

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@ -6,17 +6,107 @@
#define BUFFER_SIZE 100 #define BUFFER_SIZE 100
#define FILE_HEADER_STRING "__info2_image_file_format__" #define FILE_HEADER_STRING "__info2_image_file_format__"
// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei //Datei öffnen, Header, Anzahl, Höhe und Breite lesen, geöffnete Datei zurückgeben
static FILE* openAndReadShort (const char *path, unsigned short *count, unsigned short *width, unsigned short *height) {
FILE *file = fopen(path, "rb");
if (!file) {
return NULL;
}
size_t headerLength = strlen(FILE_HEADER_STRING);
char *header = malloc (headerLength + 1);
if(!header) {
return NULL;
}
// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen if (fread(header, sizeof(char), headerLength, file) != headerLength) {
free (header);
return NULL;
}
header[headerLength] = '\0';
if (strcmp (header, FILE_HEADER_STRING) != 0) {
free(header);
return NULL;
}
free (header);
fread(count, sizeof(unsigned short), 1, file);
fread(width, sizeof(unsigned short), 1, file);
fread(height, sizeof(unsigned short), 1, file);
return file;
}
//Speicher anlegen und Pixel eines Bildes einlesen
static GrayScaleImage* readPixles (FILE *file, unsigned short *width, unsigned short *height) {
GrayScaleImage *image = malloc (sizeof(GrayScaleImage));
image->width = *width;
image->height = *height;
image->buffer = malloc ((*width) * (*height) * sizeof(GrayScalePixelType));
if (!image->buffer) {
free(image);
return NULL;
}
for (unsigned int i = 0; i < (*width) * (*height); i++) {
unsigned char pixel;
if (fread(&pixel, sizeof(unsigned char), 1, file) != 1) {
free(image->buffer);
free(image);
return NULL;
}
image->buffer[i] = pixel;
}
return image;
}
//Ausführen von openAndReadShort, Anlegen des Speichers für Bilderserie, readPixles wird für jedes Bild ausgeführt
//Nach jedem Bild wird das zugehörige Label gelesen, bei sämtlichen Fehlern wird NULL zurückgegeben und Speicher durch clearSeries bereinigt
GrayScaleImageSeries *readImages(const char *path) GrayScaleImageSeries *readImages(const char *path)
{ {
GrayScaleImageSeries *series = NULL; unsigned short count = 0, width = 0, height = 0;
FILE *file = openAndReadShort(path, &count, &width, &height);
if (file == 0) {
return NULL;
}
GrayScaleImageSeries *series = malloc(sizeof(GrayScaleImageSeries));
if (!series) {
fclose(file);
return NULL;
}
series->count = count;
series->images = malloc(count * sizeof(GrayScaleImage));
series->labels = malloc(count* sizeof(unsigned char));
for (unsigned int i = 0; i < series->count; i++) {
GrayScaleImage *image = readPixles(file, &width, &height);
series->images[i] = *image;
free(image);
if (fread(&series->labels[i], sizeof(unsigned char), 1, file) != 1) {
clearSeries(series);
fclose(file);
return NULL;
}
}
fclose(file);
return series; return series;
} }
// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt //Bereinigt den Speicher
void clearSeries(GrayScaleImageSeries *series) void clearSeries(GrayScaleImageSeries *series)
{ {
for (unsigned int i = 0; i < series->count; i++) {
free(series->images[i].buffer);
}
free(series->images);
free(series->labels);
free(series);
} }

137
matrix.c
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@ -1,35 +1,154 @@
#include <stdlib.h> #include <stdlib.h>
#include <string.h> #include <string.h>
#include "matrix.h" #include "matrix.h"
#include <stdio.h>
// TODO Matrix-Funktionen implementieren
Matrix createMatrix(unsigned int rows, unsigned int cols) Matrix createMatrix(unsigned int rows, unsigned int cols)
{ {
Matrix mat = {.rows = rows, .cols = cols};
// If one dimension is 0, return both dimensions as 0 and don't init the array/buffer.
if (rows == 0 || cols == 0)
{
mat.rows = 0;
mat.cols = 0;
return mat;
}
// allocate contiguous and 0 initialized memory
mat.buffer = calloc(rows * cols, sizeof(MatrixType));
// check if calloc failed
if (mat.buffer == NULL)
{
clearMatrix(&mat);
perror("could not allocate memory");
}
return mat;
} }
// reduce the dimensions to (0, 0) and free the memory
void clearMatrix(Matrix *matrix) void clearMatrix(Matrix *matrix)
{ {
free(matrix->buffer);
matrix->buffer = NULL;
matrix->cols = 0;
matrix->rows = 0;
} }
void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx) void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
{ {
// do nothing if idx is not in array or matrix buffer is NULL
if (!(rowIdx < matrix.rows) || !(colIdx < matrix.cols) || matrix.buffer == NULL)
{
return;
}
matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
} }
MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx) MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
{ {
// return UNDEFINED_MATRIX_VALUE if idx is not in array or matrix buffer is NULL
} if (!(rowIdx < matrix.rows) || !(colIdx < matrix.cols) || matrix.buffer == NULL)
{
return UNDEFINED_MATRIX_VALUE;
}
return matrix.buffer[rowIdx * matrix.cols + colIdx];
};
Matrix add(const Matrix matrix1, const Matrix matrix2) Matrix add(const Matrix matrix1, const Matrix matrix2)
{ {
Matrix resMat = (matrix1.cols > matrix2.cols) ? createMatrix(matrix1.rows, matrix1.cols) : createMatrix(matrix2.rows, matrix2.cols);
if (resMat.buffer == NULL)
{
return createMatrix(0, 0);
}
// matrices not compatible
if (matrix1.rows != matrix2.rows)
{
clearMatrix(&resMat);
return resMat;
}
// check if broadcasting is possible
if (matrix1.cols != matrix2.cols)
{
// matrix1 is a vector
if (matrix1.cols == 1)
{
// broadcast vector
for (size_t m = 0; m < matrix2.rows; m++)
{
for (size_t n = 0; n < matrix2.cols; n++)
{
setMatrixAt(getMatrixAt(matrix2, m, n) + getMatrixAt(matrix1, m, 0), resMat, m, n);
}
}
return resMat;
}
// matrix2 is a vector
else if (matrix2.cols == 1)
{
// broadcast vector
for (size_t m = 0; m < matrix1.rows; m++)
{
for (size_t n = 0; n < matrix1.cols; n++)
{
setMatrixAt(getMatrixAt(matrix1, m, n) + getMatrixAt(matrix2, m, 0), resMat, m, n);
}
}
return resMat;
}
// addition not possible
else
{
clearMatrix(&resMat);
return resMat;
}
}
for (size_t m = 0; m < matrix1.rows; m++)
{
for (size_t n = 0; n < matrix1.cols; n++)
{
// this is unnecessarily complicated because at this point we already know that the matrices are compatible
setMatrixAt(getMatrixAt(matrix1, m, n) + getMatrixAt(matrix2, m, n), resMat, m, n);
}
}
return resMat;
} }
Matrix multiply(const Matrix matrix1, const Matrix matrix2) Matrix multiply(const Matrix matrix1, const Matrix matrix2)
{ {
if (matrix1.cols != matrix2.rows || matrix1.buffer == NULL || matrix2.buffer == NULL)
{
return createMatrix(0, 0);
}
int rows = matrix1.rows, cols = matrix2.cols;
Matrix resMat = createMatrix(rows, cols);
if (resMat.buffer == NULL)
{
return createMatrix(0, 0);
}
for (size_t rowIdx = 0; rowIdx < rows; rowIdx++)
{
for (size_t colIdx = 0; colIdx < cols; colIdx++)
{
int curCellVal = 0;
for (size_t k = 0; k < matrix1.cols; k++)
{
curCellVal += getMatrixAt(matrix1, rowIdx, k) * getMatrixAt(matrix2, k, colIdx);
}
setMatrixAt(curCellVal, resMat, rowIdx, colIdx);
}
}
return resMat;
} }

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@ -5,8 +5,13 @@
typedef float MatrixType; typedef float MatrixType;
// TODO Matrixtyp definieren // Matrixtyp
typedef struct Matrix
{
MatrixType *buffer;
size_t rows;
size_t cols;
} Matrix;
Matrix createMatrix(unsigned int rows, unsigned int cols); Matrix createMatrix(unsigned int rows, unsigned int cols);
void clearMatrix(Matrix *matrix); void clearMatrix(Matrix *matrix);
@ -15,5 +20,4 @@ MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int co
Matrix add(const Matrix matrix1, const Matrix matrix2); Matrix add(const Matrix matrix1, const Matrix matrix2);
Matrix multiply(const Matrix matrix1, const Matrix matrix2); Matrix multiply(const Matrix matrix1, const Matrix matrix2);
#endif #endif

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@ -5,10 +5,46 @@
#include "unity.h" #include "unity.h"
#include "neuralNetwork.h" #include "neuralNetwork.h"
static void writeLayer(FILE *file, const Matrix weights, const Matrix biases, unsigned int inputDim)
{
unsigned int outputDim = (unsigned int)weights.rows;
fwrite(&outputDim, sizeof(unsigned int), 1, file);
if (weights.buffer != NULL)
fwrite(weights.buffer, sizeof(MatrixType), outputDim * inputDim, file);
if (biases.buffer != NULL)
fwrite(biases.buffer, sizeof(MatrixType), outputDim, file);
}
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
{ {
// TODO FILE *file = fopen(path, "wb");
if (!file) return;
const char tag[] = "__info2_neural_network_file_format__";
fwrite(tag, sizeof(char), strlen(tag), file);
if (nn.numberOfLayers == 0)
{
unsigned int zero = 0;
fwrite(&zero, sizeof(unsigned int), 1, file);
fclose(file);
return;
}
unsigned int inputDim = (unsigned int)nn.layers[0].weights.cols;
fwrite(&inputDim, sizeof(unsigned int), 1, file);
for (int i = 0; i < nn.numberOfLayers; i++)
{
writeLayer(file, nn.layers[i].weights, nn.layers[i].biases, inputDim);
inputDim = (unsigned int)nn.layers[i].weights.rows;
}
unsigned int zero = 0;
fwrite(&zero, sizeof(unsigned int), 1, file);
fclose(file);
} }
void test_loadModelReturnsCorrectNumberOfLayers(void) void test_loadModelReturnsCorrectNumberOfLayers(void)

1
testFile.info2 Normal file
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@ -0,0 +1 @@
some_tag