diff --git a/matrix.c b/matrix.c index ad00628..02f2473 100644 --- a/matrix.c +++ b/matrix.c @@ -6,30 +6,122 @@ Matrix createMatrix(unsigned int rows, unsigned int cols) { - + Matrix matrix; + + 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) +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) { - + if((matrix1.rows != matrix2.rows) || (matrix1.cols != matrix2.cols)) + { + printf("Fehler bei Addition: Matrix Dimensionen passen nicht ueberein!\n"); + Matrix empty = {0, 0, NULL}; + return empty; + } + + float matrix1Wert = 0; + float matrix2Wert = 0; + float summe = 0; + + Matrix ergebnisMatrix = createMatrix(matrix1.rows, matrix1.cols); + + for(int row = 0; row < ergebnisMatrix.rows; row++) + { + for(int col = 0; col < ergebnisMatrix.cols; col++) + { + matrix1Wert = getMatrixAt(matrix1, row, col); + matrix2Wert = getMatrixAt(matrix2, row, col); + summe = matrix1Wert + matrix2Wert; + + setMatrixAt(summe, &ergebnisMatrix, row, col); + } + } + + return ergebnisMatrix; } Matrix multiply(const Matrix matrix1, const Matrix matrix2) { - -} \ No newline at end of file + 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; +} diff --git a/matrix.h b/matrix.h index cc640d1..42879d5 100644 --- a/matrix.h +++ b/matrix.h @@ -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); diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c index 21ab370..589f8d2 100644 --- a/neuralNetworkTests.c +++ b/neuralNetworkTests.c @@ -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)