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17 Commits

Author SHA1 Message Date
51d02f32c2 testing 2025-11-24 12:56:31 +01:00
a23369ea4c auskommentieren von initalversion aus makefile 2025-11-22 20:20:20 +01:00
e2375c4844 corrected mistake from merging in matrix.c 2025-11-22 20:12:10 +01:00
dd2a621f11 merged branchjens and resolved issues 2025-11-22 20:04:24 +01:00
648cbb1777 Merge branch 'branchflorian' 2025-11-22 20:00:38 +01:00
Florian Wetzel
fcdcef7e88 Änderung Definition und Vorbereitung merge zu master 2025-11-22 18:03:53 +01:00
Jens Burger
5776f52662 Optisch leicht verbessert 2025-11-22 12:59:54 +01:00
Jens Burger
18c917193c broadcasting mal versucht 2025-11-20 18:56:31 +01:00
Jens Burger
72dab86dd9 abschließender Commit Termin 18.11. 2025-11-18 11:12:43 +01:00
Jens Burger
9d7ec2dc0d Bis auf Broadcasting alles fertig 2025-11-18 11:00:22 +01:00
Florian Wetzel
24c7ac65ce Mit branchjens gemerged und Definition nochmal geändert 2025-11-18 10:36:22 +01:00
Jens Burger
78579ded18 Kleiner Fix 2 2025-11-18 10:27:39 +01:00
Florian Wetzel
19a811515b Def FILE_HEADER_STRING 2025-11-18 10:19:49 +01:00
Jens Burger
5f52f6eef2 Kleine Fixes 2025-11-18 10:18:07 +01:00
Florian Wetzel
734b72d346 Erste Version neuralNetworksTests.c 2025-11-18 10:04:35 +01:00
Jens Burger
6594829227 Addition und Multiplikation hinzugefügt 2025-11-16 14:46:33 +01:00
Jens Burger
80481f037d Matrix Strct erstellt/Erste Matrixfunktionen geschrieben 2025-11-13 15:54:04 +01:00
6 changed files with 263 additions and 13 deletions

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@ -41,24 +41,31 @@ GrayScaleImageSeries *readImages(const char *path)
if (expectedHeader)
{
printf("expected Header!\n");
// reallocate memory so that each image width can be saved seperately
series->images = realloc(series->images, series->count * 2 * sizeof(unsigned int) + sizeof(headerString));
printf("count: %d", series->count);
series->images[2].width = series->images->width;
series->images[2].height = series->images->height;
/*
for (int i = 0; i < series->count; i++)
{
series->images[i].width = series->images->width;
series->images[i].height = series->images->height;
}
*/
printf("afer for Loop! \n");
readImagedata(readSource, series, numberOfBytesToRead);
}
else
{
series = NULL;
}
printf("before read Source\n");
fclose(readSource);
}
printf("finished reading!\n");
return series;
}

2
main.c
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@ -23,7 +23,7 @@ int main(int argc, char *argv[])
printf("Loaded %u images ... \n", series->count);
model = loadModel(pathToModel);
if(model.numberOfLayers > 0)
{
unsigned char *predictions = NULL;

View File

@ -18,8 +18,8 @@ unityfolder = ./unity
# --------------------------
# Initiales Programm bauen (zum ausprobieren)
# --------------------------
mnist_initial: $(BINARIES)/libmnist_complete.a
$(CC) -o mnist $(BINARIES)/libmnist_complete.a $(BINARIES)/libraylib.a ${LDFLAGS}
#mnist_initial: $(BINARIES)/libmnist_complete.a
# $(CC) -o mnist $(BINARIES)/libmnist_complete.a $(BINARIES)/libraylib.a ${LDFLAGS}
# --------------------------
# Selbst implementiertes Programm bauen

217
matrix.c
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@ -1,35 +1,238 @@
#include <stdlib.h>
#include <string.h>
#include <stdio.h>
#include "matrix.h"
// TODO Matrix-Funktionen implementieren
Matrix createMatrix(unsigned int rows, unsigned int cols)
{
Matrix matrix;
Matrix empty = {0, 0, NULL};
if(rows == 0 || cols == 0)
{
//print("Fehler: Dimensionen muessen >= 1 sein!");
return empty;
}
matrix.rows = rows;
matrix.cols = cols;
matrix.buffer = malloc(rows * cols * sizeof(float));
if(matrix.buffer == NULL)
{
//printf("Fehler bei der Speicherreservierung! Keine Matrix erstellt!");
matrix.rows = 0;
matrix.cols = 0;
}
return matrix;
}
void clearMatrix(Matrix *matrix)
{
free(matrix->buffer);
matrix->buffer = NULL;
matrix->rows = 0;
matrix->cols = 0;
}
void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
{
if(matrix.buffer == NULL)
{
//printf("Fehler beim Setzen! Matrix nicht initialisiert");
return;
}
if(rowIdx >= matrix.rows || colIdx >= matrix.cols)
{
//printf("Ungueltige Indizes beim Setzen!\n");
return;
}
matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
}
MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
{
if(matrix.buffer == NULL)
{
//printf("Fehler beim Lesen! Matrix nicht initialisiert");
return 0;
}
if(rowIdx >= matrix.rows || colIdx >= matrix.cols)
{
//printf("Ungueltige Indizes beim Lesen!\n");
return 0;
}
return matrix.buffer[rowIdx * matrix.cols + colIdx];
}
Matrix add(const Matrix matrix1, const Matrix matrix2)
{
float matrix1Wert = 0;
float matrix2Wert = 0;
float summe = 0;
int broadcasting = 0;
Matrix broadcastedmatrix1 = {0,0,NULL};
Matrix broadcastedmatrix2 = {0,0,NULL};
if((matrix1.rows != matrix2.rows) || (matrix1.cols != matrix2.cols))
{
if((matrix1.rows != matrix2.rows) && (matrix1.cols == matrix2.cols))
{
if(matrix1.rows == 1)
{
broadcastedmatrix1 = createMatrix(matrix2.rows, matrix2.cols);
for(int row = 0; row<matrix2.rows; row++)
{
for(int col = 0; col<matrix2.cols; col++)
{
matrix1Wert = getMatrixAt(matrix1, 0, col);
setMatrixAt(matrix1Wert, broadcastedmatrix1, row, col);
}
}
broadcasting = 1;
}
else if(matrix2.rows == 1)
{
broadcastedmatrix2 = createMatrix(matrix1.rows, matrix1.cols);
for(int row = 0; row<matrix1.rows; row++)
{
for(int col = 0; col<matrix1.cols; col++)
{
matrix2Wert = getMatrixAt(matrix2, 0, col);
setMatrixAt(matrix2Wert, broadcastedmatrix2, row, col);
}
}
broadcasting = 2;
}
}
else if((matrix1.rows == matrix2.rows) && (matrix1.cols != matrix2.cols))
{
if(matrix1.cols == 1)
{
broadcastedmatrix1 = createMatrix(matrix2.rows, matrix2.cols);
for(int row = 0; row<matrix2.rows; row++)
{
for(int col = 0; col<matrix2.cols; col++)
{
matrix1Wert = getMatrixAt(matrix1, row, 0);
setMatrixAt(matrix1Wert, broadcastedmatrix1, row, col);
}
}
broadcasting = 1;
}
else if(matrix2.cols == 1)
{
broadcastedmatrix2 = createMatrix(matrix1.rows, matrix1.cols);
for(int row = 0; row<matrix1.rows; row++)
{
for(int col = 0; col<matrix1.cols; col++)
{
matrix2Wert = getMatrixAt(matrix2, row, 0);
setMatrixAt(matrix2Wert, broadcastedmatrix2, row, col);
}
}
broadcasting = 2;
}
}
else
{
//printf("Fehler bei Addition: Matrix Dimensionen stimmen nicht ueberein!\n");
Matrix empty = {0, 0, NULL};
return empty;
}
}
Matrix ergebnisMatrix;
switch (broadcasting)
{
case 0:
case 2:
ergebnisMatrix = createMatrix(matrix1.rows, matrix1.cols);
break;
case 1:
ergebnisMatrix = createMatrix(matrix2.rows, matrix2.cols);
break;
}
for(int row = 0; row < ergebnisMatrix.rows; row++)
{
for(int col = 0; col < ergebnisMatrix.cols; col++)
{
if(broadcasting == 0)
{
matrix1Wert = getMatrixAt(matrix1, row, col);
matrix2Wert = getMatrixAt(matrix2, row, col);
summe = matrix1Wert + matrix2Wert;
}
else if(broadcasting == 1)
{
matrix1Wert = getMatrixAt(broadcastedmatrix1, row, col);
matrix2Wert = getMatrixAt(matrix2, row, col);
summe = matrix1Wert + matrix2Wert;
}
else if(broadcasting == 2)
{
matrix1Wert = getMatrixAt(matrix1, row, col);
matrix2Wert = getMatrixAt(broadcastedmatrix2, row, col);
summe = matrix1Wert + matrix2Wert;
}
setMatrixAt(summe, ergebnisMatrix, row, col);
}
}
clearMatrix(&broadcastedmatrix1);
clearMatrix(&broadcastedmatrix2);
return ergebnisMatrix;
}
Matrix multiply(const Matrix matrix1, const Matrix matrix2)
{
}
if(matrix1.cols != matrix2.rows)
{
//printf("Fehler bei Multiplikation: Matrix Dimensionen passen nicht ueberein!\n");
Matrix empty = {0, 0, NULL};
return empty;
}
float erg = 0;
Matrix ergebnisMatrix = createMatrix(matrix1.rows, matrix2.cols);
for(int row = 0; row < ergebnisMatrix.rows; row++)
{
for(int col = 0; col < ergebnisMatrix.cols; col++)
{
erg = 0;
for(int k = 0; k < matrix1.cols; k++)
{
erg += getMatrixAt(matrix1, row, k) * getMatrixAt(matrix2, k, col);
}
setMatrixAt(erg, ergebnisMatrix, row, col);
}
}
return ergebnisMatrix;
}

View File

@ -6,7 +6,12 @@
typedef float MatrixType;
// TODO Matrixtyp definieren
typedef struct
{
int rows;
int cols;
float *buffer;
} Matrix;
Matrix createMatrix(unsigned int rows, unsigned int cols);
void clearMatrix(Matrix *matrix);

View File

@ -5,10 +5,45 @@
#include "unity.h"
#include "neuralNetwork.h"
#define FILE_HEADER_STRING "__info2_neural_network_file_format__"
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
{
// TODO
FILE *f = fopen(path, "wb");
if (!f) return;
fwrite(FILE_HEADER_STRING, sizeof(char), strlen(FILE_HEADER_STRING), f);
int inputDim = nn.layers[0].weights.cols;
int outputDim = nn.layers[0].weights.rows;
fwrite(&inputDim, sizeof(int), 1, f);
fwrite(&outputDim, sizeof(int), 1, f);
for (int i = 0; i < nn.numberOfLayers; i++)
{
Matrix weights = nn.layers[i].weights;
Matrix biases = nn.layers[i].biases;
int numWeightValues = weights.rows * weights.cols;
int numBiasValues = biases.rows * biases.cols;
fwrite(weights.buffer, sizeof(MatrixType), numWeightValues, f);
fwrite(biases.buffer, sizeof(MatrixType), numBiasValues, f);
if (i < nn.numberOfLayers - 1)
{
int nextOutputDim = nn.layers[i + 1].weights.rows;
fwrite(&nextOutputDim, sizeof(int), 1, f);
}
}
int endMarker = 0;
fwrite(&endMarker, sizeof(int), 1, f);
fclose(f);
}
void test_loadModelReturnsCorrectNumberOfLayers(void)