From 8efd1a3bfb606f4c3d7d961aeeb161159b99b2b9 Mon Sep 17 00:00:00 2001 From: Jonas Date: Sun, 16 Nov 2025 21:04:47 +0100 Subject: [PATCH] copied files to windows and linux --- I2_NeuronalerAbsturz/Start_Linux/imageInput.c | 105 +++++++++++++- .../Start_Linux/imageInputTests.c | 39 +++++- I2_NeuronalerAbsturz/Start_Linux/matrix.c | 128 +++++++++++++++++- I2_NeuronalerAbsturz/Start_Linux/matrix.h | 7 + .../Start_Linux/neuralNetworkTests.c | 70 +++++++++- .../Start_Mac/neuralNetworkTests.c | 4 +- .../Start_Windows/imageInput.c | 105 +++++++++++++- I2_NeuronalerAbsturz/Start_Windows/matrix.c | 128 +++++++++++++++++- I2_NeuronalerAbsturz/Start_Windows/matrix.h | 7 + .../Start_Windows/neuralNetworkTests.c | 70 +++++++++- 10 files changed, 637 insertions(+), 26 deletions(-) diff --git a/I2_NeuronalerAbsturz/Start_Linux/imageInput.c b/I2_NeuronalerAbsturz/Start_Linux/imageInput.c index bb30de1..664e011 100644 --- a/I2_NeuronalerAbsturz/Start_Linux/imageInput.c +++ b/I2_NeuronalerAbsturz/Start_Linux/imageInput.c @@ -8,15 +8,116 @@ // TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei +/* ---------------- Hilfsfunktionen ---------------- */ + +static int readHeader(FILE *file, unsigned short *count, unsigned short *width, unsigned short *height) +{ + unsigned short headerlength = strlen(FILE_HEADER_STRING); + char buffer[headerlength + 1]; + if (fread(buffer, 1, headerlength, file) != headerlength) + return 0; + + buffer[headerlength] = '\0'; + + if (strcmp(buffer, FILE_HEADER_STRING) != 0) + return 0; + + 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; +} + +static int readSingleImage(FILE *file, GrayScaleImage *image) +{ + unsigned int pixelCount = image->width * image->height; + + if (fread(image->buffer, sizeof(GrayScalePixelType), pixelCount, file) != pixelCount) + return 0; + + return 1; +} + + // TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen GrayScaleImageSeries *readImages(const char *path) { - GrayScaleImageSeries *series = NULL; - + FILE *file = fopen(path, "rb"); + if (!file) + return NULL; + + unsigned short count, width, height; + + if (!readHeader(file, &count, &width, &height)) { + fclose(file); + return NULL; + } + + GrayScaleImageSeries *series = malloc(sizeof(GrayScaleImageSeries)); + series->count = count; + series->images = malloc(count * sizeof(GrayScaleImage)); + series->labels = malloc(count * sizeof(unsigned char)); + + if (!series || !series->images || !series->labels) + { + free(series->images); + free(series->labels); + free(series); + fclose(file); + return NULL; + } + + for (unsigned int i = 0; i < count; i++) + { + series->images[i].width = width; + series->images[i].height = height; + series->images[i].buffer = malloc(width * height * sizeof(GrayScalePixelType)); + + //malloc prüfen + if (!series->images[i].buffer) + { + clearSeries(series); + fclose(file); + return NULL; + } + + //Image einlesen + prüfen + if (!readSingleImage(file, &series->images[i])) { + fclose(file); + clearSeries(series); + return NULL; + } + + // label einlesen + if (fread(&series->labels[i], sizeof(unsigned char), 1, file) != 1) { + fclose(file); + clearSeries(series); + return NULL; + } + } + + fclose(file); return series; } // TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt void clearSeries(GrayScaleImageSeries *series) { + if(series) + { + for(unsigned int i = 0; i < series->count; i++) + { + free(series->images[i].buffer); + } + + free(series->images); + free(series->labels); + free(series); + } } \ No newline at end of file diff --git a/I2_NeuronalerAbsturz/Start_Linux/imageInputTests.c b/I2_NeuronalerAbsturz/Start_Linux/imageInputTests.c index c704271..699b39b 100644 --- a/I2_NeuronalerAbsturz/Start_Linux/imageInputTests.c +++ b/I2_NeuronalerAbsturz/Start_Linux/imageInputTests.c @@ -13,10 +13,15 @@ static void prepareImageFile(const char *path, unsigned short int width, unsigne if(file != NULL) { const char *fileTag = "__info2_image_file_format__"; - GrayScalePixelType *zeroBuffer = (GrayScalePixelType *)calloc(numberOfImages * width * height, sizeof(GrayScalePixelType)); + GrayScalePixelType *buffer = (GrayScalePixelType *)calloc(numberOfImages * width * height, sizeof(GrayScalePixelType)); - if(zeroBuffer != NULL) + if(buffer != NULL) { + for(unsigned int i = 0; i < (numberOfImages * width * height); i++) + { + buffer[i] = (GrayScalePixelType)i; + } + fwrite(fileTag, sizeof(fileTag[0]), strlen(fileTag), file); fwrite(&numberOfImages, sizeof(numberOfImages), 1, file); fwrite(&width, sizeof(width), 1, file); @@ -24,11 +29,11 @@ static void prepareImageFile(const char *path, unsigned short int width, unsigne for(int i = 0; i < numberOfImages; i++) { - fwrite(zeroBuffer, sizeof(GrayScalePixelType), width * height, file); + fwrite(buffer, sizeof(GrayScalePixelType), width * height, file); fwrite(&label, sizeof(unsigned char), 1, file); } - free(zeroBuffer); + free(buffer); } fclose(file); @@ -54,7 +59,7 @@ void test_readImagesReturnsCorrectImageWidth(void) GrayScaleImageSeries *series = NULL; const unsigned short expectedWidth = 10; const char *path = "testFile.info2"; - prepareImageFile(path, 8, expectedWidth, 2, 1); + prepareImageFile(path, expectedWidth, 8, 2, 1); series = readImages(path); TEST_ASSERT_NOT_NULL(series); TEST_ASSERT_NOT_NULL(series->images); @@ -70,7 +75,7 @@ void test_readImagesReturnsCorrectImageHeight(void) GrayScaleImageSeries *series = NULL; const unsigned short expectedHeight = 10; const char *path = "testFile.info2"; - prepareImageFile(path, expectedHeight, 8, 2, 1); + prepareImageFile(path, 8, expectedHeight, 2, 1); series = readImages(path); TEST_ASSERT_NOT_NULL(series); TEST_ASSERT_NOT_NULL(series->images); @@ -119,6 +124,27 @@ void test_readImagesFailsOnWrongFileTag(void) remove(path); } +void test_readImagesReadsCorrectGrayScales(void) +{ + GrayScaleImageSeries *series = NULL; + const char *path = "testFile.info2"; + + prepareImageFile(path, 8, 8, 1, 1); + series = readImages(path); + + TEST_ASSERT_NOT_NULL(series); + TEST_ASSERT_NOT_NULL(series->images); + TEST_ASSERT_EQUAL_UINT16(1, series->count); + + for (unsigned int i = 0; i < (8 * 8); i++) + { + TEST_ASSERT_EQUAL_UINT8((GrayScalePixelType)i, series->images->buffer[i]); + } + + clearSeries(series); + remove(path); +} + void setUp(void) { // Falls notwendig, kann hier Vorbereitungsarbeit gemacht werden } @@ -138,6 +164,7 @@ int main() RUN_TEST(test_readImagesReturnsCorrectLabels); RUN_TEST(test_readImagesReturnsNullOnNotExistingPath); RUN_TEST(test_readImagesFailsOnWrongFileTag); + RUN_TEST(test_readImagesReadsCorrectGrayScales); return UNITY_END(); } \ No newline at end of file diff --git a/I2_NeuronalerAbsturz/Start_Linux/matrix.c b/I2_NeuronalerAbsturz/Start_Linux/matrix.c index ad00628..2a98af6 100644 --- a/I2_NeuronalerAbsturz/Start_Linux/matrix.c +++ b/I2_NeuronalerAbsturz/Start_Linux/matrix.c @@ -6,30 +6,146 @@ Matrix createMatrix(unsigned int rows, unsigned int cols) { + Matrix m; + + if (rows == 0 || cols == 0) + { + m.rows = 0; + m.cols = 0; + m.buffer = NULL; + return m; + } + + m.rows = rows; + m.cols = cols; + m.buffer = (MatrixType *)calloc(rows * cols, sizeof(MatrixType)); + return m; } void clearMatrix(Matrix *matrix) { - + if (matrix != NULL) + { + if (matrix->buffer != NULL) + { + 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) + { + if (rowIdx < matrix.rows && colIdx < matrix.cols) + { + matrix.buffer[rowIdx * matrix.cols + colIdx] = value; + } + } } MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx) { - + if (matrix.buffer == NULL || rowIdx >= matrix.rows || colIdx >= matrix.cols) + { + return UNDEFINED_MATRIX_VALUE; + } + + return matrix.buffer[rowIdx * matrix.cols + colIdx]; } Matrix add(const Matrix matrix1, const Matrix matrix2) { - + Matrix result; + + if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.rows != matrix2.rows) + { + result.rows = 0; + result.cols = 0; + result.buffer = NULL; + return result; + } + + if (matrix1.cols == matrix2.cols) + { + result = createMatrix(matrix1.rows, matrix1.cols); + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix1.cols; j++) + { + MatrixType value = getMatrixAt(matrix1, i, j) + getMatrixAt(matrix2, i, j); + setMatrixAt(value, result, i, j); + } + } + return result; + } + + if (matrix1.cols == 1 && matrix2.cols > 1) + { + result = createMatrix(matrix1.rows, matrix2.cols); + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix2.cols; j++) + { + MatrixType value = getMatrixAt(matrix1, i, 0) + getMatrixAt(matrix2, i, j); + setMatrixAt(value, result, i, j); + } + } + return result; + } + else if (matrix2.cols == 1 && matrix1.cols > 1) + { + result = createMatrix(matrix1.rows, matrix1.cols); + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix1.cols; j++) + { + MatrixType value = getMatrixAt(matrix1, i, j) + getMatrixAt(matrix2, i, 0); + setMatrixAt(value, result, i, j); + } + } + return result; + } + + //Fall: Unterschiedliche Spaltenanzahl, beide ungleich 1 + result.rows = 0; + result.cols = 0; + result.buffer = NULL; + return result; } Matrix multiply(const Matrix matrix1, const Matrix matrix2) { - -} \ No newline at end of file + Matrix result; + + if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.cols != matrix2.rows) + { + result.rows = 0; + result.cols = 0; + result.buffer = NULL; + return result; + } + + result = createMatrix(matrix1.rows, matrix2.cols); + + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix2.cols; j++) + { + MatrixType sum = 0; + + for (int k = 0; k < matrix1.cols; k++) + { + sum += getMatrixAt(matrix1, i, k) * getMatrixAt(matrix2, k, j); + } + setMatrixAt(sum, result, i, j); + } + } + + return result; +} diff --git a/I2_NeuronalerAbsturz/Start_Linux/matrix.h b/I2_NeuronalerAbsturz/Start_Linux/matrix.h index cc640d1..6174048 100644 --- a/I2_NeuronalerAbsturz/Start_Linux/matrix.h +++ b/I2_NeuronalerAbsturz/Start_Linux/matrix.h @@ -7,6 +7,13 @@ typedef float MatrixType; // TODO Matrixtyp definieren +typedef struct +{ + MatrixType *buffer; + int rows; + int cols; +} Matrix; + Matrix createMatrix(unsigned int rows, unsigned int cols); void clearMatrix(Matrix *matrix); diff --git a/I2_NeuronalerAbsturz/Start_Linux/neuralNetworkTests.c b/I2_NeuronalerAbsturz/Start_Linux/neuralNetworkTests.c index 21ab370..d06c430 100644 --- a/I2_NeuronalerAbsturz/Start_Linux/neuralNetworkTests.c +++ b/I2_NeuronalerAbsturz/Start_Linux/neuralNetworkTests.c @@ -5,12 +5,80 @@ #include "unity.h" #include "neuralNetwork.h" +/* +################ +Aufbau Test File +################ + + +HEADER + +inputDim +outputDim + +-- Layer 1 -- +weights +biases + +outputDim + +-- Layer 2 -- +weights +biases + +... +... +-- Layer n -- +weights +biases + +outputDim = 0 => Ende +*/ + static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) { - // TODO + FILE *file = fopen(path, "wb"); + if (file) + { + const char *fileTag = "__info2_neural_network_file_format__"; + fwrite(fileTag, 1, strlen(fileTag), file); + + //Stopt loadModel, falls keine Layer vorhanden + if (nn.numberOfLayers == 0) + { + int zero = 0; + fwrite(&zero, sizeof(int), 1, file); + fclose(file); + return; + } + + // input und output dimension schreiben + int inputDim = nn.layers[0].weights.cols; + fwrite(&inputDim, sizeof(int), 1, file); + + // für weiter Layer nur outputDimension schreiben + for (unsigned int i = 0; i < nn.numberOfLayers; i++) + { + int outputDim = nn.layers[i].weights.rows; + fwrite(&outputDim, sizeof(int), 1, file); + + int weightCount = nn.layers[i].weights.rows * nn.layers[i].weights.cols; + fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), weightCount, file); + + int biasesCount = nn.layers[i].biases.rows * nn.layers[i].biases.cols; + fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), biasesCount, file); + } + + // loadModel ließt 0 ein -> Stop + int fileEnd = 0; + fwrite(&fileEnd, sizeof(int), 1, file); } + fclose(file); +} + + void test_loadModelReturnsCorrectNumberOfLayers(void) { const char *path = "some__nn_test_file.info2"; diff --git a/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c b/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c index c11aa00..d06c430 100644 --- a/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c +++ b/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c @@ -17,8 +17,8 @@ inputDim outputDim -- Layer 1 -- -weights (outputDim * inputDim * MatrixType) -biases (outputDim * MatrixType) +weights +biases outputDim diff --git a/I2_NeuronalerAbsturz/Start_Windows/imageInput.c b/I2_NeuronalerAbsturz/Start_Windows/imageInput.c index bb30de1..664e011 100644 --- a/I2_NeuronalerAbsturz/Start_Windows/imageInput.c +++ b/I2_NeuronalerAbsturz/Start_Windows/imageInput.c @@ -8,15 +8,116 @@ // TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei +/* ---------------- Hilfsfunktionen ---------------- */ + +static int readHeader(FILE *file, unsigned short *count, unsigned short *width, unsigned short *height) +{ + unsigned short headerlength = strlen(FILE_HEADER_STRING); + char buffer[headerlength + 1]; + if (fread(buffer, 1, headerlength, file) != headerlength) + return 0; + + buffer[headerlength] = '\0'; + + if (strcmp(buffer, FILE_HEADER_STRING) != 0) + return 0; + + 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; +} + +static int readSingleImage(FILE *file, GrayScaleImage *image) +{ + unsigned int pixelCount = image->width * image->height; + + if (fread(image->buffer, sizeof(GrayScalePixelType), pixelCount, file) != pixelCount) + return 0; + + return 1; +} + + // TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen GrayScaleImageSeries *readImages(const char *path) { - GrayScaleImageSeries *series = NULL; - + FILE *file = fopen(path, "rb"); + if (!file) + return NULL; + + unsigned short count, width, height; + + if (!readHeader(file, &count, &width, &height)) { + fclose(file); + return NULL; + } + + GrayScaleImageSeries *series = malloc(sizeof(GrayScaleImageSeries)); + series->count = count; + series->images = malloc(count * sizeof(GrayScaleImage)); + series->labels = malloc(count * sizeof(unsigned char)); + + if (!series || !series->images || !series->labels) + { + free(series->images); + free(series->labels); + free(series); + fclose(file); + return NULL; + } + + for (unsigned int i = 0; i < count; i++) + { + series->images[i].width = width; + series->images[i].height = height; + series->images[i].buffer = malloc(width * height * sizeof(GrayScalePixelType)); + + //malloc prüfen + if (!series->images[i].buffer) + { + clearSeries(series); + fclose(file); + return NULL; + } + + //Image einlesen + prüfen + if (!readSingleImage(file, &series->images[i])) { + fclose(file); + clearSeries(series); + return NULL; + } + + // label einlesen + if (fread(&series->labels[i], sizeof(unsigned char), 1, file) != 1) { + fclose(file); + clearSeries(series); + return NULL; + } + } + + fclose(file); return series; } // TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt void clearSeries(GrayScaleImageSeries *series) { + if(series) + { + for(unsigned int i = 0; i < series->count; i++) + { + free(series->images[i].buffer); + } + + free(series->images); + free(series->labels); + free(series); + } } \ No newline at end of file diff --git a/I2_NeuronalerAbsturz/Start_Windows/matrix.c b/I2_NeuronalerAbsturz/Start_Windows/matrix.c index ad00628..2a98af6 100644 --- a/I2_NeuronalerAbsturz/Start_Windows/matrix.c +++ b/I2_NeuronalerAbsturz/Start_Windows/matrix.c @@ -6,30 +6,146 @@ Matrix createMatrix(unsigned int rows, unsigned int cols) { + Matrix m; + + if (rows == 0 || cols == 0) + { + m.rows = 0; + m.cols = 0; + m.buffer = NULL; + return m; + } + + m.rows = rows; + m.cols = cols; + m.buffer = (MatrixType *)calloc(rows * cols, sizeof(MatrixType)); + return m; } void clearMatrix(Matrix *matrix) { - + if (matrix != NULL) + { + if (matrix->buffer != NULL) + { + 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) + { + if (rowIdx < matrix.rows && colIdx < matrix.cols) + { + matrix.buffer[rowIdx * matrix.cols + colIdx] = value; + } + } } MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx) { - + if (matrix.buffer == NULL || rowIdx >= matrix.rows || colIdx >= matrix.cols) + { + return UNDEFINED_MATRIX_VALUE; + } + + return matrix.buffer[rowIdx * matrix.cols + colIdx]; } Matrix add(const Matrix matrix1, const Matrix matrix2) { - + Matrix result; + + if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.rows != matrix2.rows) + { + result.rows = 0; + result.cols = 0; + result.buffer = NULL; + return result; + } + + if (matrix1.cols == matrix2.cols) + { + result = createMatrix(matrix1.rows, matrix1.cols); + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix1.cols; j++) + { + MatrixType value = getMatrixAt(matrix1, i, j) + getMatrixAt(matrix2, i, j); + setMatrixAt(value, result, i, j); + } + } + return result; + } + + if (matrix1.cols == 1 && matrix2.cols > 1) + { + result = createMatrix(matrix1.rows, matrix2.cols); + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix2.cols; j++) + { + MatrixType value = getMatrixAt(matrix1, i, 0) + getMatrixAt(matrix2, i, j); + setMatrixAt(value, result, i, j); + } + } + return result; + } + else if (matrix2.cols == 1 && matrix1.cols > 1) + { + result = createMatrix(matrix1.rows, matrix1.cols); + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix1.cols; j++) + { + MatrixType value = getMatrixAt(matrix1, i, j) + getMatrixAt(matrix2, i, 0); + setMatrixAt(value, result, i, j); + } + } + return result; + } + + //Fall: Unterschiedliche Spaltenanzahl, beide ungleich 1 + result.rows = 0; + result.cols = 0; + result.buffer = NULL; + return result; } Matrix multiply(const Matrix matrix1, const Matrix matrix2) { - -} \ No newline at end of file + Matrix result; + + if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.cols != matrix2.rows) + { + result.rows = 0; + result.cols = 0; + result.buffer = NULL; + return result; + } + + result = createMatrix(matrix1.rows, matrix2.cols); + + for (int i = 0; i < matrix1.rows; i++) + { + for (int j = 0; j < matrix2.cols; j++) + { + MatrixType sum = 0; + + for (int k = 0; k < matrix1.cols; k++) + { + sum += getMatrixAt(matrix1, i, k) * getMatrixAt(matrix2, k, j); + } + setMatrixAt(sum, result, i, j); + } + } + + return result; +} diff --git a/I2_NeuronalerAbsturz/Start_Windows/matrix.h b/I2_NeuronalerAbsturz/Start_Windows/matrix.h index cc640d1..6174048 100644 --- a/I2_NeuronalerAbsturz/Start_Windows/matrix.h +++ b/I2_NeuronalerAbsturz/Start_Windows/matrix.h @@ -7,6 +7,13 @@ typedef float MatrixType; // TODO Matrixtyp definieren +typedef struct +{ + MatrixType *buffer; + int rows; + int cols; +} Matrix; + Matrix createMatrix(unsigned int rows, unsigned int cols); void clearMatrix(Matrix *matrix); diff --git a/I2_NeuronalerAbsturz/Start_Windows/neuralNetworkTests.c b/I2_NeuronalerAbsturz/Start_Windows/neuralNetworkTests.c index 21ab370..d06c430 100644 --- a/I2_NeuronalerAbsturz/Start_Windows/neuralNetworkTests.c +++ b/I2_NeuronalerAbsturz/Start_Windows/neuralNetworkTests.c @@ -5,12 +5,80 @@ #include "unity.h" #include "neuralNetwork.h" +/* +################ +Aufbau Test File +################ + + +HEADER + +inputDim +outputDim + +-- Layer 1 -- +weights +biases + +outputDim + +-- Layer 2 -- +weights +biases + +... +... +-- Layer n -- +weights +biases + +outputDim = 0 => Ende +*/ + static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) { - // TODO + FILE *file = fopen(path, "wb"); + if (file) + { + const char *fileTag = "__info2_neural_network_file_format__"; + fwrite(fileTag, 1, strlen(fileTag), file); + + //Stopt loadModel, falls keine Layer vorhanden + if (nn.numberOfLayers == 0) + { + int zero = 0; + fwrite(&zero, sizeof(int), 1, file); + fclose(file); + return; + } + + // input und output dimension schreiben + int inputDim = nn.layers[0].weights.cols; + fwrite(&inputDim, sizeof(int), 1, file); + + // für weiter Layer nur outputDimension schreiben + for (unsigned int i = 0; i < nn.numberOfLayers; i++) + { + int outputDim = nn.layers[i].weights.rows; + fwrite(&outputDim, sizeof(int), 1, file); + + int weightCount = nn.layers[i].weights.rows * nn.layers[i].weights.cols; + fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), weightCount, file); + + int biasesCount = nn.layers[i].biases.rows * nn.layers[i].biases.cols; + fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), biasesCount, file); + } + + // loadModel ließt 0 ein -> Stop + int fileEnd = 0; + fwrite(&fileEnd, sizeof(int), 1, file); } + fclose(file); +} + + void test_loadModelReturnsCorrectNumberOfLayers(void) { const char *path = "some__nn_test_file.info2";