add some comments

Reviewed-on: freudenreichan/info2Praktikum-NeuronalesNetz#4

.gitignore

@@ -1,4 +1,8 @@
 mnist
 runTests
 *.o
-*.exe
+*.exe
+runMatrixTests
+runImageInputTests
+runNeuralNetworkTests
+.vscode

imageInput.c

@@ -6,17 +6,165 @@
 #define BUFFER_SIZE 100
 #define FILE_HEADER_STRING "__info2_image_file_format__"
 
-// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
+typedef enum
+{
+    IMG_SUCCESS = 0,
+    IMG_ERR_INVALID_HEADER, // Header did not match
+    IMG_ERR_READ,           // Failed to read from file, maybe it's too short
+    IMG_ERR,                // General Error
+} ImageError;
+
+static ImageError checkHeader(FILE *file);
+static ImageError readPictureParams(unsigned short *number, unsigned short *width, unsigned short *height, FILE *file);
+static ImageError readImage(size_t numPixels, GrayScalePixelType *pixelBuffer, unsigned char *label, FILE *file);
+static ImageError parseImageFile(FILE *file, GrayScaleImageSeries *series);
 
-// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
 GrayScaleImageSeries *readImages(const char *path)
 {
-    GrayScaleImageSeries *series = NULL;
-    
+    // It's very important to call calloc here because otherwise clearSeries() might try to free random memory
+    GrayScaleImageSeries *series = calloc(1, sizeof(GrayScaleImageSeries));
+    if (series == NULL)
+    {
+        return NULL;
+    }
+
+    FILE *file = fopen(path, "rb");
+    // If fopen() failed
+    if (file == NULL)
+    {
+        clearSeries(series);
+        series = NULL;
+        return NULL;
+    }
+
+    // Try to parse the whole file. If anything fails memory is freed
+    if (parseImageFile(file, series))
+    {
+        clearSeries(series);
+        series = NULL; // Return NULL after the file is properly closed 
+    }
+
+    fclose(file);
     return series;
 }
 
-// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
+static ImageError parseImageFile(FILE *file, GrayScaleImageSeries *series)
+{
+    if (checkHeader(file))
+    {
+        return IMG_ERR; // header check failed
+    }
+
+    unsigned short imgCNT, width, height;
+    if (readPictureParams(&imgCNT, &width, &height, file))
+    {
+        return IMG_ERR; // read failed
+    }
+    size_t pixels = width * height;
+
+    // The images contain more pointers, definitely use calloc here
+    series->images = calloc(imgCNT, sizeof(GrayScaleImage));
+    if (series->images == NULL)
+    {
+        return IMG_ERR;
+    }
+
+    series->labels = malloc(imgCNT * sizeof(unsigned char));
+    if (series->labels == NULL)
+    {
+        return IMG_ERR;
+    }
+
+    series->count = imgCNT;
+    // Read every image and it's label
+    for (size_t imageIdx = 0; imageIdx < imgCNT; imageIdx++)
+    {
+        GrayScaleImage *curImage = &series->images[imageIdx];
+
+        curImage->buffer = malloc(sizeof(GrayScalePixelType) * pixels);
+        if (curImage->buffer == NULL)
+        {
+            return IMG_ERR;
+        }
+
+        curImage->width = width;
+        curImage->height = height;
+
+        if (readImage(pixels, curImage->buffer, &series->labels[imageIdx], file))
+        {
+            return IMG_ERR;
+        }
+    }
+    return IMG_SUCCESS;
+}
+
+static ImageError checkHeader(FILE *file)
+{
+    size_t len = strlen(FILE_HEADER_STRING);
+    char headerBuf[len + 1];
+    size_t charsRead = fread(headerBuf, 1, len, file);
+    // Check if the file is to short
+    if (charsRead < len)
+    {
+        return IMG_ERR_READ;
+    }
+    headerBuf[len] = '\0'; // Terminate string
+    return strcmp(headerBuf, FILE_HEADER_STRING) == 0 ? IMG_SUCCESS : IMG_ERR_INVALID_HEADER;
+}
+
+static ImageError readPictureParams(unsigned short *number, unsigned short *width, unsigned short *height, FILE *file)
+{
+    // number of images
+    if (1 != fread(number, sizeof(unsigned short), 1, file))
+    {
+        return IMG_ERR_READ;
+    }
+
+    // image width
+    if (1 != fread(width, sizeof(unsigned short), 1, file))
+    {
+        return IMG_ERR_READ;
+    }
+
+    // height
+    if (1 != fread(height, sizeof(unsigned short), 1, file))
+    {
+        return IMG_ERR_READ;
+    }
+
+    return IMG_SUCCESS;
+}
+
+// Read 1 image and it's label
+static ImageError readImage(size_t numPixels, GrayScalePixelType *pixelBuffer, unsigned char *label, FILE *file)
+{
+    if (numPixels > fread(pixelBuffer, sizeof(GrayScalePixelType), numPixels, file))
+    {
+        return IMG_ERR_READ;
+    }
+
+    if (1 != fread(label, sizeof(unsigned char), 1, file))
+    {
+        return IMG_ERR_READ;
+    }
+
+    return IMG_SUCCESS;
+}
+
+// Frees memory for each image buffer, image, label and finally series
 void clearSeries(GrayScaleImageSeries *series)
 {
+    if (series)
+    {
+
+        int seriesLen = series->count;
+        for (size_t imageIdx = 0; imageIdx < seriesLen; imageIdx++)
+        {
+            free(series->images[imageIdx].buffer);
+        }
+
+        free(series->images);
+        free(series->labels);
+        free(series);
+    }
 }

matrix.c

@@ -1,35 +1,152 @@
 #include <stdlib.h>
 #include <string.h>
 #include "matrix.h"
-
-// TODO Matrix-Funktionen implementieren
+#include <stdio.h>
 
 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)
 {
-    
+    free(matrix->buffer);
+    matrix->buffer = NULL;
+    matrix->cols = 0;
+    matrix->rows = 0;
 }
 
 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)
 {
-    
-}
+    // 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 resMat = (matrix1.cols > matrix2.cols) ? createMatrix(matrix1.rows, matrix1.cols) : createMatrix(matrix2.rows, matrix2.cols);
+
+    if (resMat.buffer == NULL)
+    {
+        return createMatrix(0, 0);
+    }
+
+    if (matrix1.cols != matrix2.cols)
+    {
+        if (matrix1.rows != matrix2.rows)
+        {
+            clearMatrix(&resMat);
+            return resMat;
+        }
+        else 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;
+        }
+        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;
+        }
+        else
+        {
+            clearMatrix(&resMat);
+            return resMat;
+        }
+    }
+
+    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, n), resMat, m, n);
+        }
+    }
+
+    return resMat;
 }
 
-Matrix multiply(const Matrix matrix1, const Matrix matrix2)
+Matrix multiply(const Matrix A, const Matrix B)
 {
-    
+    if (A.cols != B.rows || A.buffer == NULL || B.buffer == NULL)
+    {
+        return createMatrix(0, 0);
+    }
+
+    int rows = A.rows, cols = B.cols;
+    Matrix C = createMatrix(rows, cols);
+
+    if (C.buffer == NULL)
+    {
+        return createMatrix(0, 0);
+    }
+
+    // M = Rows, K = Common Dim, N = Cols
+    size_t M = A.rows, K = A.cols, N = B.cols;
+
+    for (size_t i = 0; i < M; i++)
+    {
+        for (size_t k = 0; k < K; k++)
+
+        {
+            MatrixType valA = A.buffer[i * K + k];
+            for (size_t j = 0; j < N; j++)
+            {
+                // C[i, j] += A[i, k] * B[k, j];
+                // M x N,     M x K,    K x N
+                C.buffer[i * N + j] += valA * B.buffer[k * N + j];
+            }
+        }
+    }
+    return C;
 }

matrix.h

@@ -5,8 +5,14 @@
 
 typedef float MatrixType;
 
-// TODO Matrixtyp definieren
+// Matrixtyp
+typedef struct Matrix
+{
+    size_t rows;
+    size_t cols;
+    MatrixType *buffer;
 
+} Matrix;
 
 Matrix createMatrix(unsigned int rows, unsigned int cols);
 void clearMatrix(Matrix *matrix);
@@ -15,5 +21,4 @@ MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int co
 Matrix add(const Matrix matrix1, const Matrix matrix2);
 Matrix multiply(const Matrix matrix1, const Matrix matrix2);
 
-
 #endif

matrixTests.c

@@ -71,6 +71,32 @@ void test_addFailsOnDifferentInputDimensions(void)
     TEST_ASSERT_EQUAL_UINT32(0, result.cols);
 }
 
+void test_addSupportsBroadcasting(void)
+{
+    MatrixType buffer1[] = {1, 2, 3, 4, 5, 6};
+    MatrixType buffer2[] = {7, 8};
+    Matrix matrix1 = {.rows=2, .cols=3, .buffer=buffer1};
+    Matrix matrix2 = {.rows=2, .cols=1, .buffer=buffer2};
+
+    Matrix result1 = add(matrix1, matrix2);
+    Matrix result2 = add(matrix2, matrix1);
+
+    float expectedResults[] = {8, 9, 10, 12, 13, 14};
+
+    TEST_ASSERT_EQUAL_UINT32(matrix1.rows, result1.rows);
+    TEST_ASSERT_EQUAL_UINT32(matrix1.cols, result1.cols);
+    TEST_ASSERT_EQUAL_UINT32(matrix1.rows, result2.rows);
+    TEST_ASSERT_EQUAL_UINT32(matrix1.cols, result2.cols);
+
+    TEST_ASSERT_EQUAL_INT(sizeof(expectedResults)/sizeof(expectedResults[0]), result1.rows * result1.cols);
+    TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, result1.buffer, result1.cols * result1.rows);
+    TEST_ASSERT_EQUAL_INT(sizeof(expectedResults)/sizeof(expectedResults[0]), result2.rows * result2.cols);
+    TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, result2.buffer, result2.cols * result2.rows);
+
+    free(result1.buffer);
+    free(result2.buffer);
+}
+
 void test_multiplyReturnsCorrectResults(void)
 {
     MatrixType buffer1[] = {1, 2, 3, 4, 5, 6};
@@ -138,7 +164,7 @@ void test_setMatrixAtFailsOnIndicesOutOfRange(void)
     Matrix matrixToTest = {.rows=2, .cols=3, .buffer=buffer};
 
     setMatrixAt(-1, matrixToTest, 2, 3);
-    TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, matrixToTest.buffer, matrixToTest.cols * matrixToTest.rows);
+    TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, matrixToTest.buffer, sizeof(buffer)/sizeof(MatrixType));
 }
 
 void setUp(void) {
@@ -159,6 +185,7 @@ int main()
     RUN_TEST(test_clearMatrixSetsMembersToNull);
     RUN_TEST(test_addReturnsCorrectResult);
     RUN_TEST(test_addFailsOnDifferentInputDimensions);
+    RUN_TEST(test_addSupportsBroadcasting);
     RUN_TEST(test_multiplyReturnsCorrectResults);
     RUN_TEST(test_multiplyFailsOnWrongInputDimensions);
     RUN_TEST(test_getMatrixAtReturnsCorrectResult);

neuralNetworkTests.c

@@ -6,9 +6,30 @@
 #include "neuralNetwork.h"
 
 
+static void erzeugeMatrix(FILE *file, const Matrix *m)
+{
+    fwrite(&m->rows, sizeof(int), 1, file);
+    fwrite(&m->cols, sizeof(int), 1, file);
+    fwrite(m->buffer, sizeof(MatrixType), m->rows * m->cols, file);
+}
+
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *file = fopen(path, "wb");
+    if (!file)
+        return;
+
+    const char *header = "__info2_neural_network_file_format__";
+    fwrite(header, sizeof(char), strlen(header), file);
+    fwrite(&nn.numberOfLayers, sizeof(int), 1, file);
+
+    for (int i = 0; i < nn.numberOfLayers; i++)
+    {
+        erzeugeMatrix(file, &nn.layers[i].weights);
+        erzeugeMatrix(file, &nn.layers[i].biases);
+    }
+
+    fclose(file);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)