25 Commits
Author SHA1 Message Date
Kristin 2a1ff310db matrix.c aenderungen 2025-12-02 09:13:35 +01:00
Kristin 3c4e4df496 Merge branch 'main' of https://git.efi.th-nuernberg.de/gitea/kachelto100370/info2Praktikum-NeuronalesNetz into Krisp2 2025-11-25 10:41:30 +01:00
Kristin fd1bc886a7 neu 2025-11-25 10:38:40 +01:00
Max-R efa260ccbe 0 fehler bei add abfangen 2025-11-25 10:15:52 +01:00
Max-R 801abc1b66 Merge branch 'main' of https://git.efi.th-nuernberg.de/gitea/kachelto100370/info2Praktikum-NeuronalesNetz 2025-11-25 10:00:31 +01:00
Max-R 8e518a3bdd Merge branch 'RMax' matrix.c voll 2025-11-25 09:58:03 +01:00
Max-R 0baf646832 add files to gitignore 2025-11-25 09:57:28 +01:00
Kristin 0f0f2f19c3 lauffaehige version, noch haesslich 2025-11-25 09:57:13 +01:00
kachelto100370 98dd789680 input image things 2025-11-25 09:10:54 +01:00
Kristin 7aa57191da neuralNetworkTests mit Kommentaren 2025-11-23 17:16:18 +01:00
Kristin da4eaa718d Merge branch 'main' of https://git.efi.th-nuernberg.de/gitea/kachelto100370/info2Praktikum-NeuronalesNetz into Krisp2 2025-11-23 16:44:13 +01:00
Max-R 21d9b5c01d so finde ich es schöner... 2025-11-22 15:29:32 +01:00
Max-R e7930c7eb0 kommentaare update 2025-11-22 15:23:50 +01:00
Max-R 5075c34983 kommentaare update 2025-11-22 15:19:41 +01:00
Max-R b187a13b17 multiply, besteht MatrixTests 2025-11-22 15:17:12 +01:00
Max-R 4e2ee7078a alles bis uf multiply 2025-11-22 12:41:46 +01:00
Max-R 35a598a276 broadcasting 2025-11-22 11:54:32 +01:00
Max-R e1ea9f33cd create matrix mit null 2025-11-22 10:55:27 +01:00
kachelto100370 7f3c6d1d3f first pass matrix add, ohne broadcasting 2025-11-20 16:04:01 +01:00
Max-R 0886489d49 Matrix noch ohne broadcasting 2025-11-20 16:03:44 +01:00
Max-R f9c46a6784 Merge branch 'main' of https://git.efi.th-nuernberg.de/gitea/kachelto100370/info2Praktikum-NeuronalesNetz into RMax 2025-11-20 14:50:33 +01:00
Max-R 5fcc3cd042 Merge branch 'main' of https://git.efi.th-nuernberg.de/gitea/kachelto100370/info2Praktikum-NeuronalesNetz into RMax 2025-11-18 10:51:55 +01:00
Max-R 3de79e2b83 clearMatrix füllen 2025-11-11 11:05:28 +01:00
Max-R ec54bdd951 create Matrix gefüllt, test unit 2025-11-11 10:36:11 +01:00
Max-R 0e3f03a03d Matrix definiert 2025-11-11 09:20:40 +01:00
9 changed files with 511 additions and 342 deletions
+6
View File
@@ -2,3 +2,9 @@ mnist
runTests
*.o
*.exe
.vscode/settings.json
.vscode/launch.json
.vscode/settings.json
.vscode/settings.json
runImageInputTests
testFile.info2
+123 -16
View File
@@ -1,29 +1,136 @@
#include "imageInput.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "imageInput.h"
#define BUFFER_SIZE 100
#define FILE_HEADER_STRING "__info2_image_file_format__"
// define BUFFER 100
// 10x10 pixel
// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
GrayScaleImage readImage()
{
/* ----------------------------------------------------------
1. Header prüfen
---------------------------------------------------------- */
static int readHeader(FILE *file) {
char header[sizeof(FILE_HEADER_STRING)];
if (fread(header, 1, sizeof(FILE_HEADER_STRING) - 1, file) !=
sizeof(FILE_HEADER_STRING) - 1)
return 0;
header[sizeof(FILE_HEADER_STRING) - 1] = '\0';
return strcmp(header, FILE_HEADER_STRING) == 0;
}
// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
GrayScaleImageSeries *readImages(const char *path)
{
GrayScaleImageSeries *series = NULL;
FILE *file = fopen("mnist_test.info2","rb");
char headOfFile;
series = malloc();
/* ----------------------------------------------------------
2. Meta-Daten lesen (unsigned short)
---------------------------------------------------------- */
static int readMeta(FILE *file, unsigned short *count, unsigned short *width,
unsigned short *height) {
if (fread(count, sizeof(unsigned short), 1, file) != 1)
return 0;
if (fread(width, sizeof(unsigned short), 1, file) != 1)
return 0;
if (fread(height, sizeof(unsigned short), 1, file) != 1)
return 0;
return 1;
}
/* ----------------------------------------------------------
3. Einzelbild lesen
---------------------------------------------------------- */
static int readSingleImage(FILE *file, GrayScaleImage *img,
unsigned short width, unsigned short height) {
img->width = width;
img->height = height;
size_t numPixels = (size_t)width * (size_t)height; // anzahl an pixeln
img->buffer = malloc(numPixels);
if (!img->buffer)
return 0;
if (fread(img->buffer, 1, numPixels, file) != numPixels) {
free(img->buffer);
img->buffer = NULL; // fehler bei ungültiger eingabe
return 0;
}
return 1;
}
/* ----------------------------------------------------------
4. Label lesen
---------------------------------------------------------- */
static int readLabel(FILE *file, unsigned char *label) {
return fread(label, 1, 1, file) == 1;
}
/* ----------------------------------------------------------
5. Komplette Bildserie lesen
---------------------------------------------------------- */
GrayScaleImageSeries *readImages(const char *path) {
FILE *file = fopen(path, "rb");
if (!file)
return NULL;
if (!readHeader(file)) {
fclose(file);
return NULL;
}
unsigned short count, width, height;
if (!readMeta(file, &count, &width, &height)) {
fclose(file);
return NULL;
}
// printf("%d, %d, %d", count, width, height);
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));
if (!series->images || !series->labels) {
free(series->images);
free(series->labels);
free(series);
fclose(file);
return NULL;
}
for (unsigned int i = 0; i < count; i++) {
if (!readSingleImage(file, &series->images[i], width, height) ||
!readLabel(file, &series->labels[i])) {
// Aufräumen bei Fehler
for (unsigned int j = 0; j < i; j++) {
free(series->images[j].buffer);
}
free(series->images);
free(series->labels);
free(series);
fclose(file);
return NULL;
}
}
fclose(file);
return series;
}
// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
void clearSeries(GrayScaleImageSeries *series)
{
/* ----------------------------------------------------------
6. Speicher komplett freigeben
---------------------------------------------------------- */
void clearSeries(GrayScaleImageSeries *series) {
if (!series)
return;
for (unsigned int i = 0; i < series->count; i++) {
free(series->images[i].buffer);
}
free(series->images);
free(series->labels);
free(series);
}
+123 -56
View File
@@ -1,88 +1,98 @@
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include "unity.h"
#include "imageInput.h"
#include "unity.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
static void prepareImageFile(const char *path, unsigned short int width, unsigned short int height, unsigned int short numberOfImages, unsigned char label)
{
/* ---------------------------------------------------------
Hilfsfunktion: Testdatei vorbereiten
--------------------------------------------------------- */
static void prepareImageFile(const char *path, unsigned int width,
unsigned int height, unsigned int numberOfImages,
unsigned char label) {
FILE *file = fopen(path, "wb");
if (!file)
return;
if(file != NULL)
{
// Header
const char *fileTag = "__info2_image_file_format__";
GrayScalePixelType *zeroBuffer = (GrayScalePixelType *)calloc(numberOfImages * width * height, sizeof(GrayScalePixelType));
fwrite(fileTag, 1, strlen(fileTag), file);
if(zeroBuffer != NULL)
{
fwrite(fileTag, sizeof(fileTag[0]), strlen(fileTag), file);
fwrite(&numberOfImages, sizeof(numberOfImages), 1, file);
fwrite(&width, sizeof(width), 1, file);
fwrite(&height, sizeof(height), 1, file);
// Meta-Daten als unsigned short
unsigned short n = (unsigned short)numberOfImages;
unsigned short w = (unsigned short)width;
unsigned short h = (unsigned short)height;
fwrite(&n, sizeof(unsigned short), 1, file);
fwrite(&w, sizeof(unsigned short), 1, file);
fwrite(&h, sizeof(unsigned short), 1, file);
for(int i = 0; i < numberOfImages; i++)
{
fwrite(zeroBuffer, sizeof(GrayScalePixelType), width * height, file);
// Pixelbuffer
GrayScalePixelType *buffer =
calloc(width * height, sizeof(GrayScalePixelType));
if (!buffer) {
fclose(file);
return;
}
for (unsigned int i = 0; i < width * height; i++)
buffer[i] = (GrayScalePixelType)i;
// Jedes Bild schreiben: Pixel + Label
for (unsigned int img = 0; img < numberOfImages; img++) {
fwrite(buffer, sizeof(GrayScalePixelType), width * height, file);
fwrite(&label, sizeof(unsigned char), 1, file);
}
free(zeroBuffer);
}
free(buffer);
fclose(file);
}
}
/* ---------------------------------------------------------
Unit Tests
--------------------------------------------------------- */
void test_readImagesReturnsCorrectNumberOfImages(void)
{
void test_readImagesReturnsCorrectNumberOfImages(void) {
GrayScaleImageSeries *series = NULL;
const unsigned short expectedNumberOfImages = 2;
const unsigned int expectedNumberOfImages = 2;
const char *path = "testFile.info2";
prepareImageFile(path, 8, 8, expectedNumberOfImages, 1);
series = readImages(path);
TEST_ASSERT_NOT_NULL(series);
TEST_ASSERT_EQUAL_UINT16(expectedNumberOfImages, series->count);
TEST_ASSERT_EQUAL_UINT(expectedNumberOfImages, series->count);
clearSeries(series);
remove(path);
}
void test_readImagesReturnsCorrectImageWidth(void)
{
void test_readImagesReturnsCorrectImageWidth(void) {
GrayScaleImageSeries *series = NULL;
const unsigned short expectedWidth = 10;
const unsigned int expectedWidth = 10;
const char *path = "testFile.info2";
prepareImageFile(path, expectedWidth, 8, 2, 1);
series = readImages(path);
TEST_ASSERT_NOT_NULL(series);
TEST_ASSERT_NOT_NULL(series->images);
TEST_ASSERT_EQUAL_UINT16(2, series->count);
TEST_ASSERT_EQUAL_UINT16(expectedWidth, series->images[0].width);
TEST_ASSERT_EQUAL_UINT16(expectedWidth, series->images[1].width);
TEST_ASSERT_EQUAL_UINT(2, series->count);
TEST_ASSERT_EQUAL_UINT(expectedWidth, series->images[0].width);
TEST_ASSERT_EQUAL_UINT(expectedWidth, series->images[1].width);
clearSeries(series);
remove(path);
}
void test_readImagesReturnsCorrectImageHeight(void)
{
void test_readImagesReturnsCorrectImageHeight(void) {
GrayScaleImageSeries *series = NULL;
const unsigned short expectedHeight = 10;
const unsigned int expectedHeight = 10;
const char *path = "testFile.info2";
prepareImageFile(path, 8, expectedHeight, 2, 1);
series = readImages(path);
TEST_ASSERT_NOT_NULL(series);
TEST_ASSERT_NOT_NULL(series->images);
TEST_ASSERT_EQUAL_UINT16(2, series->count);
TEST_ASSERT_EQUAL_UINT16(expectedHeight, series->images[0].height);
TEST_ASSERT_EQUAL_UINT16(expectedHeight, series->images[1].height);
TEST_ASSERT_EQUAL_UINT(2, series->count);
TEST_ASSERT_EQUAL_UINT(expectedHeight, series->images[0].height);
TEST_ASSERT_EQUAL_UINT(expectedHeight, series->images[1].height);
clearSeries(series);
remove(path);
}
void test_readImagesReturnsCorrectLabels(void)
{
void test_readImagesReturnsCorrectLabels(void) {
const unsigned char expectedLabel = 15;
GrayScaleImageSeries *series = NULL;
@@ -91,7 +101,7 @@ void test_readImagesReturnsCorrectLabels(void)
series = readImages(path);
TEST_ASSERT_NOT_NULL(series);
TEST_ASSERT_NOT_NULL(series->labels);
TEST_ASSERT_EQUAL_UINT16(2, series->count);
TEST_ASSERT_EQUAL_UINT(2, series->count);
for (int i = 0; i < 2; i++) {
TEST_ASSERT_EQUAL_UINT8(expectedLabel, series->labels[i]);
}
@@ -99,19 +109,16 @@ void test_readImagesReturnsCorrectLabels(void)
remove(path);
}
void test_readImagesReturnsNullOnNotExistingPath(void)
{
void test_readImagesReturnsNullOnNotExistingPath(void) {
const char *path = "testFile.txt";
remove(path);
TEST_ASSERT_NULL(readImages(path));
}
void test_readImagesFailsOnWrongFileTag(void)
{
void test_readImagesFailsOnWrongFileTag(void) {
const char *path = "testFile.info2";
FILE *file = fopen(path, "w");
if(file != NULL)
{
if (file != NULL) {
fprintf(file, "some_tag ");
fclose(file);
TEST_ASSERT_NULL(readImages(path));
@@ -119,25 +126,85 @@ void test_readImagesFailsOnWrongFileTag(void)
remove(path);
}
void setUp(void) {
// Falls notwendig, kann hier Vorbereitungsarbeit gemacht werden
// Test
void test_read_GrayScale_Pixel(
void) { // testet das einlesen eines graustufenbildes von readImages()
GrayScaleImageSeries *series = NULL; // enthält später das Bild
const char *path = "testFile.info2";
prepareImageFile(path, 8, 8, 1,
1); // Höhe x Breite in Pixel, Anzahl Bilder und Kategorie
series = readImages(path);
TEST_ASSERT_NOT_NULL(series); // Speicher reservieren
TEST_ASSERT_NOT_NULL(series->images); // Inhalt ist da
TEST_ASSERT_EQUAL_UINT(1, series->count); // Anzahl der Bilder stimmt
for (int i = 0; i < (8 * 8); i++) {
TEST_ASSERT_EQUAL_UINT8(
(GrayScalePixelType)i,
series->images[0].buffer[i]); // alle Pixelwerte prüfen
}
clearSeries(series);
remove(path);
}
void tearDown(void) {
// Hier kann Bereinigungsarbeit nach jedem Test durchgeführt werden
/* ---------------------------------------------------------
Optional: Mehrere Bilder gleichzeitig testen
--------------------------------------------------------- */
void test_readImagesMultipleImagesContent(void) {
GrayScaleImageSeries *series = NULL;
const char *path = "testFile.info2";
const unsigned int numberOfImages = 3;
const unsigned int width = 4;
const unsigned int height = 4;
const unsigned char label = 7;
prepareImageFile(path, width, height, numberOfImages, label);
series = readImages(path);
TEST_ASSERT_NOT_NULL(series);
TEST_ASSERT_NOT_NULL(series->images);
TEST_ASSERT_NOT_NULL(series->labels);
TEST_ASSERT_EQUAL_UINT(numberOfImages, series->count);
for (unsigned int img = 0; img < numberOfImages; img++) {
for (unsigned int i = 0; i < width * height; i++)
TEST_ASSERT_EQUAL_UINT8((GrayScalePixelType)i,
series->images[img].buffer[i]);
TEST_ASSERT_EQUAL_UINT8(label, series->labels[img]);
}
clearSeries(series);
remove(path);
}
int main()
{
/* ---------------------------------------------------------
Setup / Teardown
--------------------------------------------------------- */
void setUp(void) {}
void tearDown(void) {}
/* ---------------------------------------------------------
main()
--------------------------------------------------------- */
int main(void) {
UNITY_BEGIN();
printf("\n============================\nImage input tests\n============================\n");
printf("\n============================\nImage input "
"tests\n============================\n");
RUN_TEST(test_readImagesReturnsCorrectNumberOfImages);
RUN_TEST(test_readImagesReturnsCorrectImageWidth);
RUN_TEST(test_readImagesReturnsCorrectImageHeight);
RUN_TEST(test_readImagesReturnsCorrectLabels);
RUN_TEST(test_readImagesReturnsNullOnNotExistingPath);
RUN_TEST(test_readImagesFailsOnWrongFileTag);
RUN_TEST(test_read_GrayScale_Pixel);
RUN_TEST(test_readImagesMultipleImagesContent);
return UNITY_END();
}
+3 -2
View File
@@ -59,7 +59,8 @@ imageInputTests: imageInput.o imageInputTests.c $(unityfolder)/unity.c
# --------------------------
clean:
ifeq ($(OS),Windows_NT)
del /f *.o *.exe
else
rm -f *.o mnist runMatrixTests runNeuralNetworkTests runImageInputTests
else
del /f *.o *.exe
endif
+120 -156
View File
@@ -3,17 +3,15 @@
#include <stdlib.h>
#include <string.h>
// TODO Matrix-Funktionen implementieren
/*typedef struct {
unsigned int rows; //Zeilen
unsigned int cols; //Spalten
MatrixType *buffer; //Zeiger auf Speicherbereich Reihen*Spalten
} Matrix;*/
Matrix createMatrix(unsigned int rows, unsigned int cols) {
Matrix createMatrix(const unsigned int rows, const unsigned int cols) {
if (cols == 0 || rows == 0) {
Matrix errorMatrix = {0, 0, NULL};
if (rows == 0 || cols == 0) {
return errorMatrix;
}
MatrixType *buffer =
@@ -23,202 +21,168 @@ Matrix createMatrix(unsigned int rows, unsigned int cols) {
return newMatrix;
}
void clearMatrix(Matrix *matrix) {
matrix->buffer = UNDEFINED_MATRIX_VALUE;
matrix->rows = UNDEFINED_MATRIX_VALUE;
matrix->cols = UNDEFINED_MATRIX_VALUE;
free((*matrix).buffer); // Speicher freigeben
if (matrix->buffer != NULL) {
free((*matrix).buffer);
matrix->buffer = NULL;
}
matrix->rows = 0;
matrix->cols = 0;
}
void setMatrixAt(const MatrixType value, Matrix matrix,
const unsigned int rowIdx, // Kopie der Matrix wird übergeben
const unsigned int colIdx) {
if (rowIdx >= matrix.rows ||
colIdx >= matrix.cols) { // Speichergröße nicht überschreiten
if (rowIdx >= matrix.rows || colIdx >= matrix.cols) {
// Speichergröße nicht überschreiten
return;
}
matrix.buffer[rowIdx * matrix.cols + colIdx] =
value; // rowIdx * matrix.cols -> Beginn der Zeile colIdx ->Spalte
matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
// rowIdx * matrix.cols -> Beginn der Zeile colIdx ->Spalte
// innerhalb der Zeile
}
MatrixType getMatrixAt(const Matrix matrix,
unsigned int rowIdx, // Kopie der Matrix wird übergeben
unsigned int colIdx) {
if (rowIdx >= matrix.rows ||
colIdx >= matrix.cols) { // Speichergröße nicht überschreiten
return 0;
MatrixType
getMatrixAt(const Matrix matrix,
const unsigned int rowIdx, // Kopie der Matrix wird übergeben
const unsigned int colIdx) {
if (rowIdx >= matrix.rows || colIdx >= matrix.cols ||
matrix.buffer == NULL) { // Speichergröße nicht überschreiten
return UNDEFINED_MATRIX_VALUE;
}
MatrixType value = matrix.buffer[rowIdx * matrix.cols + colIdx];
return value;
}
Matrix broadCastCols(const Matrix matrix, const unsigned int rows,
const unsigned int cols) {
Matrix copy = createMatrix(
rows, cols); // Matrix 1 Kopie erstellen mit Dimensionen von Matrix2
for (int r = 0; r < rows; r++) {
MatrixType value = getMatrixAt(matrix, r, 0);
Matrix broadCastCols(const Matrix matrix, const unsigned int cols) {
Matrix copy1 = createMatrix(matrix.rows, cols);
for (int r = 0; r < matrix.rows; r++) {
MatrixType valueMatrix1 = getMatrixAt(matrix, r, 0);
for (int c = 0; c < cols; c++) {
setMatrixAt(value, copy, r, c);
setMatrixAt(valueMatrix1, copy1, r, c);
}
}
return copy;
return copy1;
}
Matrix broadCastRows(const Matrix matrix, const unsigned int rows,
const unsigned int cols) {
Matrix copy = createMatrix(rows, cols);
for (int c = 0; c < cols; c++) {
MatrixType value = getMatrixAt(matrix, 0, c);
Matrix broadCastRows(const Matrix matrix, const unsigned int rows) {
Matrix copy1 = createMatrix(rows, matrix.cols);
for (int c = 0; c < matrix.cols; c++) {
MatrixType valueMatrix1 = getMatrixAt(matrix, 0, c);
for (int r = 0; r < rows; r++) {
setMatrixAt(value, copy, r, c);
setMatrixAt(valueMatrix1, copy1, r, c);
}
}
return copy;
return copy1;
}
Matrix add(const Matrix matrix1, const Matrix matrix2) {
// Broadcasting nur bei Vektor und Matrix, Fehlermeldung bei zwei unpassenden
// Matrizen
// Ergebnismatrix
Matrix result;
const int cols1 = matrix1.cols;
const int rows1 = matrix1.rows;
const int cols2 = matrix2.cols;
const int rows2 = matrix2.rows;
const unsigned int rows1 = matrix1.rows;
const unsigned int rows2 = matrix2.rows;
const unsigned int cols1 = matrix1.cols;
const unsigned int cols2 = matrix2.cols;
const int rowsEqual = (matrix1.rows == matrix2.rows) ? 1 : 0;
const int colsEqual = (matrix1.cols == matrix2.cols) ? 1 : 0;
const int rowsEqual = ((rows1 == rows2) ? 1 : 0);
const int colsEqual = ((cols1 == cols2) ? 1 : 0);
if (rowsEqual && colsEqual) // addieren
{
Matrix result = createMatrix(rows1, cols1); // Speicher reservieren
for (int i = 0; i < (rows1 * cols1); i++) { // addieren
result.buffer[i] =
(matrix1.buffer[i] +
matrix2.buffer[i]); // buffer[i] ⇔ *(buffer + i) Adresse =
// Startadresse + (i * sizeof(MatrixType))
// Broadcasting nur bei Vektor und Matrix, Fehlermeldung bei zwei unpassender
// Matrix
if (rowsEqual == 1 && colsEqual == 1) {
Matrix result = createMatrix(matrix1.rows, matrix1.cols);
if (result.buffer == NULL) {
return (Matrix){0, 0, NULL};
}
return result; // zurückgeben
for (int i = 0; i < rows1; i++) {
for (int j = 0; j < cols1; j++) {
int valueM1 = getMatrixAt(matrix1, i, j);
int valueM2 = getMatrixAt(matrix2, i, j);
int sum = valueM1 + valueM2;
setMatrixAt(sum, result, i, j);
}
else if (rowsEqual && !colsEqual) {
if (cols1 == 1) {
Matrix result = createMatrix(rows2, cols2);
Matrix copy1 = broadCastCols(matrix1, rows2, cols2);
for (int i = 0; i < (rows2 * cols2); i++) { // addieren
result.buffer[i] =
(copy1.buffer[i] +
matrix2.buffer[i]); // buffer[i] ⇔ *(buffer + i) Adresse =
// Startadresse + (i * sizeof(MatrixType))
}
return result;
// add und return
} else if (cols2 == 1) {
Matrix result = createMatrix(rows1, cols1);
Matrix copy2 = broadCastCols(matrix2, rows1, cols1);
for (int i = 0; i < (rows1 * cols1); i++) { // addieren
result.buffer[i] =
(matrix1.buffer[i] +
copy2.buffer[i]); // buffer[i] ⇔ *(buffer + i) Adresse =
// Startadresse + (i * sizeof(MatrixType))
} else if (rowsEqual == 1 && (cols1 == 1 || cols2 == 1)) {
if (cols1 == 1) { // broadcasting von vektor 1 zu matrix 1, add
Matrix newMatrix = broadCastCols(matrix1, cols2);
// add
Matrix result = createMatrix(newMatrix.rows, newMatrix.cols);
if (result.buffer == NULL) {
return (Matrix){0, 0, NULL};
}
for (int i = 0; i < rows1; i++) {
for (int j = 0; j < cols2; j++) {
int valueM1 = getMatrixAt(newMatrix, i, j);
int valueM2 = getMatrixAt(matrix2, i, j);
int sum = valueM1 + valueM2;
setMatrixAt(sum, result, i, j);
}
}
clearMatrix(&newMatrix);
return result;
// add und return
} else {
Matrix newMatrix2 = broadCastCols(matrix2, cols1);
// add
Matrix result = createMatrix(newMatrix2.rows, newMatrix2.cols);
if (result.buffer == NULL) {
return (Matrix){0, 0, NULL};
}
for (int i = 0; i < rows1; i++) {
for (int j = 0; j < cols1; j++) {
int valueM1 = getMatrixAt(matrix1, i, j);
int valueM2 = getMatrixAt(newMatrix2, i, j);
int sum = valueM1 + valueM2;
setMatrixAt(sum, result, i, j);
}
}
else {
printf("Fehlermeldung"); // vielleicht Fehlermeldung ändern zu
// Programmabbruch
Matrix error = {0, 0, NULL};
return error;
return result;
}
}
}
else if (!rowsEqual && colsEqual) {
else if ((rows1 == 1 || rows2 == 1) && colsEqual == 1) {
if (rows1 == 1) {
Matrix result = createMatrix(rows2, cols2);
Matrix copy1 = broadCastRows(matrix1, rows2, cols2);
for (int i = 0; i < (rows2 * cols2); i++) { // addieren
result.buffer[i] =
(copy1.buffer[i] +
matrix2.buffer[i]); // buffer[i] ⇔ *(buffer + i) Adresse =
// Startadresse + (i * sizeof(MatrixType))
Matrix newMatrix = broadCastRows(matrix1, rows2);
// add
Matrix result = createMatrix(newMatrix.rows, newMatrix.cols);
if (result.buffer == NULL) {
return (Matrix){0, 0, NULL};
}
for (int i = 0; i < rows2; i++) {
for (int j = 0; j < cols1; j++) {
int valueM1 = getMatrixAt(newMatrix, i, j);
int valueM2 = getMatrixAt(matrix2, i, j);
int sum = valueM1 + valueM2;
setMatrixAt(sum, result, i, j);
}
}
return result;
// add und return
} else if (rows2 == 1) {
Matrix result = createMatrix(rows1, cols1);
Matrix copy2 = broadCastCols(matrix2, rows1, cols1);
// add und return
for (int i = 0; i < (rows1 * cols1); i++) { // addieren
result.buffer[i] =
(matrix1.buffer[i] +
copy2.buffer[i]); // buffer[i] ⇔ *(buffer + i) Adresse =
// Startadresse + (i * sizeof(MatrixType))
} else {
Matrix newMatrix2 = broadCastRows(matrix2, rows1);
// add
Matrix result = createMatrix(newMatrix2.rows, newMatrix2.cols);
if (result.buffer == NULL) {
return (Matrix){0, 0, NULL};
}
for (int i = 0; i < rows1; i++) {
for (int j = 0; j < cols1; j++) {
int valueM1 = getMatrixAt(matrix1, i, j);
int valueM2 = getMatrixAt(newMatrix2, i, j);
int sum = valueM1 + valueM2;
setMatrixAt(sum, result, i, j);
}
}
clearMatrix(&newMatrix2);
return result;
}
} else {
// kein add möglich
Matrix errorMatrix = {0, 0, NULL};
return errorMatrix;
}
return result;
}
else {
printf("Fehlermeldung"); // vielleicht Fehlermeldung ändern zu
// Programmabbruch
Matrix error = {0, 0, NULL};
return error;
}
}
else {
printf(
"Fehlermeldung"); // vielleicht Fehlermeldung ändern zu Programmabbruch
Matrix error = {0, 0, NULL};
return error;
}
}
Matrix multiply(const Matrix matrix1, const Matrix matrix2) {
// Spalten1 müssen gleich zeilen2 sein! dann multiplizieren
if (matrix1.cols == matrix2.rows) {
+7 -9
View File
@@ -13,17 +13,15 @@ typedef struct {
} Matrix;
Matrix createMatrix(unsigned int rows, unsigned int cols);
Matrix createMatrix(const unsigned int rows, const unsigned int cols);
void clearMatrix(Matrix *matrix);
void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx,
unsigned int colIdx);
MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx,
unsigned int colIdx);
void setMatrixAt(const MatrixType value, Matrix matrix,
const unsigned int rowIdx, const unsigned int colIdx);
MatrixType getMatrixAt(const Matrix matrix, const unsigned int rowIdx,
const unsigned int colIdx);
Matrix broadCastCols(const Matrix matrix, const unsigned int rows,
const unsigned int cols);
Matrix broadCastRows(const Matrix matrix, const unsigned int rows,
const unsigned int cols);
Matrix broadCastCols(const Matrix matrix, const unsigned int cols);
Matrix broadCastRows(const Matrix matrix, const unsigned int rows);
Matrix add(const Matrix matrix1, const Matrix matrix2);
Matrix multiply(const Matrix matrix1, const Matrix matrix2);
+58 -32
View File
@@ -5,69 +5,95 @@
#include <stdlib.h>
#include <string.h>
/*typedef struct
{
Matrix weights;
Matrix biases;
ActivationFunctionType activation;
} Layer;
typedef struct
{
Layer *layers;
unsigned int numberOfLayers;
} NeuralNetwork;*/
/*Layer: Ebene im neuronalen Netzwerk, besteht aus mehreren Neuronen
Input-Layer: Eingabedatei
Hidden-Layer: verarbeiten die Daten
Output-Layer: Ergebnis
Gewichte: bestimmen, wie stark ein Eingangssignal auf ein Neuron wirkt
Dimension: Form der Matrizen für einen Layer*/
/* Gewichtsmatrix der Layer:
*/
// speichert NeuralNetwork nn in binäre Datei->später kann es wieder geöffnet
// werden
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) {
FILE *f = fopen(path, "wb");
if (f == NULL)
return;
FILE *fptr = fopen(path, "wb"); // Binärdatei zum Schreiben öffnen
if (fptr == NULL)
return; // file konnte nicht geöffnet werden
/* 1) Header: exakt das String, ohne '\n' oder abschließendes '\0' */
const char header[] = "__info2_neural_network_file_format__";
fwrite(header, sizeof(char), strlen(header), f);
// Header ist Erkennungsstring am Anfang der Datei, loadmodel erkennt
// Dateiformat
const char header[] = "__info2_neural_network_file_format__"; // header string
fwrite(header, sizeof(char), strlen(header),
fptr); // der header wird am Anfang der Datei platziert
/* Wenn es keine Layer gibt, kein Dimensionspaar schreiben (loadModel
wird beim Lesen dann 0 zurückgeben). Aber wir können auch frühzeitig
mit einem 0-Int terminieren — beides ist in Ordnung. */
// Wenn es keine Layer gibt, 0 eintragen, LoadModel erkennt, dass Datei leer
// ist
if (nn.numberOfLayers == 0) {
/* optional: schreibe ein 0 als next outputDimension (nicht nötig) */
int zero = 0;
fwrite(&zero, sizeof(int), 1, f);
fclose(f);
fwrite(&zero, sizeof(int), 1, fptr);
fclose(fptr);
return;
}
/* 2) Für die erste Layer schreiben wir inputDimension und outputDimension */
/* inputDimension == weights.cols, outputDimension == weights.rows */
// Layer 0, inputDimension: Anzahl Input-Neuronen, outputDimension: Anzahl
// Output-Neuronen wird in Datei eingefügt
int inputDim = (int)nn.layers[0].weights.cols;
int outputDim = (int)nn.layers[0].weights.rows;
fwrite(&inputDim, sizeof(int), 1, f);
fwrite(&outputDim, sizeof(int), 1, f);
fwrite(&inputDim, sizeof(int), 1, fptr);
fwrite(&outputDim, sizeof(int), 1, fptr);
/* 3) Für jede Layer in Reihenfolge: Gewichte (output x input), Biases (output
x 1). Zwischen Layern wird nur die nächste outputDimension (int)
geschrieben. */
for (int i = 0; i < nn.numberOfLayers; i++) {
Layer layer = nn.layers[i];
Layer layer = nn.layers[i]; // kürzer, durch alle layer iterieren
int wrows = (int)layer.weights.rows;
int wcols = (int)layer.weights.cols;
int wcount = wrows * wcols;
int wcount = wrows * wcols; // Anzahl Gewichtseinträge
int bcount =
layer.biases.rows * layer.biases.cols; /* normalerweise rows * 1 */
layer.biases.rows * layer.biases.cols; // Anzahl der Bias-Einträge
/* Gewichte (MatrixType binär) */
/* Gewichte */
if (wcount > 0 && layer.weights.buffer != NULL) {
fwrite(layer.weights.buffer, sizeof(MatrixType), (size_t)wcount, f);
}
fwrite(layer.weights.buffer, sizeof(MatrixType), (size_t)wcount, fptr);
} // Gewichte werden als Matrix gespeichert
/* Biases (MatrixType binär) */
/* Biases */
if (bcount > 0 && layer.biases.buffer != NULL) {
fwrite(layer.biases.buffer, sizeof(MatrixType), (size_t)bcount, f);
}
fwrite(layer.biases.buffer, sizeof(MatrixType), (size_t)bcount, fptr);
} // Biases werden als Vektor gespeichert
/* Für die nächste Layer: falls vorhanden, schreibe deren outputDimension */
/* outputDimensionen der nächsten Layer */
if (i + 1 < nn.numberOfLayers) {
int nextOutput = (int)nn.layers[i + 1].weights.rows;
fwrite(&nextOutput, sizeof(int), 1, f);
fwrite(&nextOutput, sizeof(int), 1, fptr);
} else {
/* Letzte Layer: wir können das Ende signalisieren, indem wir ein 0
schreiben. loadModel liest dann outputDimension = 0 und beendet die
Schleife. */
// loadModel erkennt 0 als Ende der Datei
int zero = 0;
fwrite(&zero, sizeof(int), 1, f);
fwrite(&zero, sizeof(int), 1, fptr);
}
}
fclose(f);
fclose(fptr); // Datei schließen
}
void test_loadModelReturnsCorrectNumberOfLayers(void) {