updating

Reviewed-on: freudenreichan/info2Praktikum-NeuronalesNetz#4

.gitignore

@@ -1,4 +1,61 @@
-mnist
-runTests
+# ---> C
+# Prerequisites
+*.d
+
+# Object files
 *.o
-*.exe
+*.ko
+*.obj
+*.elf
+
+# Linker output
+*.ilk
+*.map
+*.exp
+
+# Precompiled Headers
+*.gch
+*.pch
+
+# Libraries
+*.lib
+*.la
+*.lo
+
+# Shared objects (inc. Windows DLLs)
+*.dll
+*.so
+*.so.*
+*.dylib
+
+# Executables
+*.exe
+*.out
+*.app
+*.i*86
+*.x86_64
+*.hex
+Startcode/mnist
+Startcode/runTests
+
+# Debug files
+*.dSYM/
+*.su
+*.idb
+*.pdb
+
+# Kernel Module Compile Results
+*.mod*
+*.cmd
+.tmp_versions/
+modules.order
+Module.symvers
+Mkfile.old
+dkms.conf
+
+# IDE folders
+.vscode/
+.idea/
+
+# macOS
+.DS_Store

Startcode/imageInput.c

@@ -0,0 +1,22 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include "imageInput.h"
+
+#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
+
+// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
+GrayScaleImageSeries *readImages(const char *path)
+{
+    GrayScaleImageSeries *series = NULL;
+    
+    return series;
+}
+
+// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
+void clearSeries(GrayScaleImageSeries *series)
+{
+}

Startcode/imageInput.h

@@ -19,5 +19,5 @@ typedef struct
 
 GrayScaleImageSeries *readImages(const char *path);
 void clearSeries(GrayScaleImageSeries *series);
-FILE *checkFile(const char *path);
+
 #endif

Startcode/imageInputTests.c

@@ -70,7 +70,7 @@ void test_readImagesReturnsCorrectImageHeight(void)
     GrayScaleImageSeries *series = NULL;
     const unsigned short expectedHeight = 10;
     const char *path = "testFile.info2";
-    prepareImageFile(path,8, expectedHeight, 2, 1);
+    prepareImageFile(path, 8, expectedHeight, 2, 1);
     series = readImages(path);
     TEST_ASSERT_NOT_NULL(series);
     TEST_ASSERT_NOT_NULL(series->images);

Startcode/main.c

@@ -1,4 +1,3 @@
-
 #include <stdio.h>
 #include <stdlib.h>
 #include "imageInput.h"
@@ -7,8 +6,6 @@
 
 int main(int argc, char *argv[])
 {
-    //readImages("mnist_test.info2");
-    
     const unsigned int windowWidth = 800;
     const unsigned int windowHeight = 600;
 
@@ -32,7 +29,7 @@ int main(int argc, char *argv[])
                 unsigned char *predictions = NULL;
                 
                 printf("Processing %u images ...\n", series->count);
-                
+
                 predictions = predict(model, series->images, series->count);
 
                 if(predictions != NULL)
@@ -68,5 +65,4 @@ int main(int argc, char *argv[])
     }
 
     return exitCode;
-    
-}
+}

Startcode/matrix.c

@@ -0,0 +1,35 @@
+#include <stdlib.h>
+#include <string.h>
+#include "matrix.h"
+
+// TODO Matrix-Funktionen implementieren
+
+Matrix createMatrix(unsigned int rows, 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)
+{
+    
+}
+
+Matrix add(const Matrix matrix1, const Matrix matrix2)
+{
+    
+}
+
+Matrix multiply(const Matrix matrix1, const Matrix matrix2)
+{
+    
+}

Startcode/matrix.h

@@ -6,13 +6,6 @@
 typedef float MatrixType;
 
 // TODO Matrixtyp definieren
-typedef struct 
-{
-    MatrixType *buffer;
-    unsigned int rows;
-    unsigned int cols;
-    
-} Matrix; 
 
 
 Matrix createMatrix(unsigned int rows, unsigned int cols);

Startcode/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);

Startcode/neuralNetwork.c

@@ -197,7 +197,7 @@ static Matrix forward(const NeuralNetwork model, Matrix inputBatch)
 
     if(result.buffer != NULL)
     {
-                for(int i = 0; i < model.numberOfLayers; i++)
+        for(int i = 0; i < model.numberOfLayers; i++)
         {
             Matrix biasResult;
             Matrix weightResult;
@@ -246,7 +246,7 @@ unsigned char *predict(const NeuralNetwork model, const GrayScaleImage images[],
 {
     Matrix inputBatch = imageBatchToMatrixOfImageVectors(images, numberOfImages);
     Matrix outputBatch = forward(model, inputBatch);
-    
+
     unsigned char *result = argmax(outputBatch);
     
     clearMatrix(&outputBatch);

Startcode/neuralNetworkTests.c

@@ -8,58 +8,7 @@
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO : Fehlerbehandlung
-    // Öffne die Datei zum Schreiben im Binärmodus
-  FILE *file = fopen(path, "wb");
-    if (!file) return;
-
-    // Schreibe den Datei-Tag
-    const char *tag = "__info2_neural_network_file_format__";
-    fwrite(tag, 1, strlen(tag), file);
-
-    // Schreibe die Anzahl der Layer
-    if (nn.numberOfLayers == 0) {
-        fclose(file);
-        return;
-    }  
-
-    // Schreibe die Eingabe- und Ausgabegrößen des Netzwerks
-    int input  = nn.layers[0].weights.cols;
-    int output = nn.layers[0].weights.rows;
-
-    fwrite(&input,  sizeof(int), 1, file);
-    fwrite(&output, sizeof(int), 1, file);
-
-    // Schreibe die Layer-Daten
-    for (int i = 0; i < nn.numberOfLayers; i++)
-    {
-        const Layer *layer = &nn.layers[i];
-        int out = layer->weights.rows;
-        int in  = layer->weights.cols;
-
-        
-        fwrite(layer->weights.buffer, sizeof(MatrixType), out * in, file);
-
-        
-        fwrite(layer->biases.buffer, sizeof(MatrixType), out * 1, file);
-
-        if (i + 1 < nn.numberOfLayers)
-        {
-            int nextOut = nn.layers[i + 1].weights.rows;
-            fwrite(&nextOut, sizeof(int), 1, file);
-        }
-    }
-
-    fclose(file);
-
-    // Debuging-Ausgabe
-    printf("prepareNeuralNetworkFile: Datei '%s' erstellt mit %u Layer(n)\n", path, nn.numberOfLayers);
-    for (unsigned int i = 0; i < nn.numberOfLayers; i++) {
-        Layer layer = nn.layers[i];
-        printf("Layer %u: weights (%u x %u), biases (%u x %u)\n", 
-               i, layer.weights.rows, layer.weights.cols, layer.biases.rows, layer.biases.cols);
-    }
-
+    // TODO
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)

imageInput.c

@@ -1,99 +0,0 @@
-#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 FILE_HEADER_SIZE (sizeof(FILE_HEADER_STRING)-1)
- 
-
-// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
-FILE *checkFile(const char *path)
-{
-    FILE *datei = fopen(path,"rb");
-    if (datei == NULL) 
-    {
-        perror("Datei konnte nicht geoeffnet werden");
-        return NULL;
-    }
-    char buffer[FILE_HEADER_SIZE+1];
-    if (fread(buffer,1,FILE_HEADER_SIZE,datei)!=FILE_HEADER_SIZE)
-    {
-        perror("Header konnte nicht eingelessen werden");
-        fclose(datei);
-        return NULL;
-    }
-    buffer[FILE_HEADER_SIZE] = '\0';
-    if (strcmp(buffer,FILE_HEADER_STRING)!=0)
-    {
-        printf("Falscher Dateikopf");
-        //printf("\n%s",buffer);
-        //printf("\n%s",FILE_HEADER_STRING);
-        //printf("\n%d",strcmp(buffer,FILE_HEADER_STRING));
-        fclose(datei);
-        return NULL;
-    }
-    return datei;
-}
-
-// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
-GrayScaleImageSeries *readImages(const char *path)
-{
-    FILE *datei = checkFile(path);
-    if (datei==NULL)
-    {
-        return NULL;
-    }
-    unsigned short image_count, width, height;
-    fread(&image_count,sizeof(unsigned short),1,datei);
-    fread(&width,sizeof(unsigned short),1,datei);
-    fread(&height,sizeof(unsigned short),1,datei);
-    //printf("%u Bilder und %u mal %u",image_count,width,height);
-    GrayScaleImageSeries *series = NULL;
-    series = malloc(sizeof(GrayScaleImageSeries));
-    series->count = image_count;
-    series->images = malloc(image_count*sizeof(GrayScaleImage));
-    series->labels = malloc(image_count*sizeof(unsigned char));
-    for(unsigned short i = 0;i<image_count;i++)
-    {
-        series->images[i].width  = width;
-        series->images[i].height = height;
-        series->images[i].buffer = malloc(width*height);
-    }
-    for(unsigned short i = 0;i<image_count;i++)
-    {
-        for (unsigned int j=0;j<(width*height);j++)
-        {
-            fread(&series->images[i].buffer[j],1,1,datei);
-        }
-        fread(&series->labels[i],1,1,datei);
-        //printf("%d\n",series->labels[i]);
-    }
-    fclose(datei);
-
-    return series;
-
-}
-
-// TODO Vervollständigen Sie die Funktion clearSeries, welche eine Bildserie vollständig aus dem Speicher freigibt
-void clearSeries(GrayScaleImageSeries *series)
-{
-    if(series == NULL)
-    {
-        printf("Serie nicht vorhanden\n");
-        return;
-    }
-    
-    unsigned short anzahl = series->count;
-    for(unsigned short i = 0;i<anzahl;i++)
-    {
-        free(series->images[i].buffer );
-    }
-    free(series->images);
-    free(series->labels);
-    free(series);
-    printf("Serie freigegeben\n");
-    return;
-    
-}

matrix.c

@@ -1,128 +0,0 @@
-#include <stdlib.h>
-#include <string.h>
-#include "matrix.h"
-#include <stdio.h>
-
-
-// Matrix erzeugen
-Matrix createMatrix(unsigned int rows, unsigned int cols)
-{
-    Matrix matrix;
-    matrix.buffer = NULL;
-    matrix.rows = 0;
-    matrix.cols = 0;
-
-    if (rows == 0 || cols == 0)
-        return matrix; // leere Matrix
-
-    matrix.buffer = (MatrixType *)malloc(rows * cols * sizeof(MatrixType));
-    if (!matrix.buffer)
-        return matrix; // Speicher konnte nicht reserviert werden
-
-    matrix.rows = rows;
-    matrix.cols = cols;
-
-    // Initialisiere alle Werte auf UNDEFINED_MATRIX_VALUE
-    for (unsigned int i = 0; i < rows * cols; i++)
-        matrix.buffer[i] = UNDEFINED_MATRIX_VALUE;
-
-    return matrix;
-}
-
-// Matrix Speicher freigeben
-void clearMatrix(Matrix *matrix)
-{
-    if (!matrix) return;
-
-    if (matrix->buffer)
-        free(matrix->buffer);
-
-    matrix->buffer = NULL;
-    matrix->rows = 0;
-    matrix->cols = 0;
-}
-
-// Wert setzen
-void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
-{
-    if (!matrix.buffer) return;
-    if (rowIdx >= matrix.rows || colIdx >= matrix.cols) return;
-
-    matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
-}
-
-// Wert auslesen
-MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
-{
-    if (!matrix.buffer) return UNDEFINED_MATRIX_VALUE;
-    if (rowIdx >= matrix.rows || colIdx >= matrix.cols) return UNDEFINED_MATRIX_VALUE;
-
-    return matrix.buffer[rowIdx * matrix.cols + colIdx];
-}
-// Matrizen addieren
-Matrix add(const Matrix m1, const Matrix m2)
-{
-    if (!m1.buffer || !m2.buffer) return createMatrix(0,0);
-
-    // gleiche Dimension
-    if (m1.rows == m2.rows && m1.cols == m2.cols)
-    {
-        Matrix result = createMatrix(m1.rows, m1.cols);
-        if (!result.buffer) return result;
-
-        for (unsigned int r = 0; r < m1.rows; r++)
-            for (unsigned int c = 0; c < m1.cols; c++)
-                result.buffer[r * result.cols + c] = m1.buffer[r * m1.cols + c] + m2.buffer[r * m2.cols + c];
-
-        return result;
-    }
-
-    // Matrix2 ist ein Spaltenvektor
-    if (m1.rows == m2.rows && m2.cols == 1)
-    {
-        Matrix result = createMatrix(m1.rows, m1.cols);
-        if (!result.buffer) return result;
-
-        for (unsigned int r = 0; r < m1.rows; r++)
-            for (unsigned int c = 0; c < m1.cols; c++)
-                result.buffer[r * result.cols + c] = m1.buffer[r * m1.cols + c] + m2.buffer[r];
-
-        return result;
-    }
-
-    // Matrix1 ist ein Spaltenvektor
-    if (m1.rows == m2.rows && m1.cols == 1)
-    {
-        Matrix result = createMatrix(m2.rows, m2.cols);
-        if (!result.buffer) return result;
-
-        for (unsigned int r = 0; r < m2.rows; r++)
-            for (unsigned int c = 0; c < m2.cols; c++)
-                result.buffer[r * result.cols + c] = m1.buffer[r] + m2.buffer[r * m2.cols + c];
-
-        return result;
-    }
-
-    // passt nicht
-    return createMatrix(0,0);
-}
-// Matrizen multiplizieren
-Matrix multiply(const Matrix m1, const Matrix m2)
-{
-    if (!m1.buffer || !m2.buffer) return createMatrix(0,0);
-    if (m1.cols != m2.rows) return createMatrix(0,0);
-
-    Matrix result = createMatrix(m1.rows, m2.cols);
-    if (!result.buffer) return result;
-
-    for (unsigned int r = 0; r < m1.rows; r++)
-        for (unsigned int c = 0; c < m2.cols; c++)
-        {
-            MatrixType sum = 0;
-            for (unsigned int k = 0; k < m1.cols; k++)
-                sum += m1.buffer[r * m1.cols + k] * m2.buffer[k * m2.cols + c];
-            result.buffer[r * result.cols + c] = sum;
-        }
-
-    return result;
-}