I2_NeuronalerAbsturz/Start_Mac/imageInputTests.c

@@ -6,20 +6,23 @@
 #include "imageInput.h"
 
 
-static void prepareImageFile(const char *path, unsigned short int width, unsigned short int height, unsigned int short numberOfImages, unsigned char label)
+static void prepareImageFile(const char *path, unsigned short int width, unsigned short int height, unsigned int short numberOfImages, unsigned char label, unsigned short greyScaleTest)
 {
     FILE *file = fopen(path, "wb");
 
     if(file != NULL)
     {
         const char *fileTag = "__info2_image_file_format__";
-        GrayScalePixelType *buffer = (GrayScalePixelType *)calloc(numberOfImages * width * height, sizeof(GrayScalePixelType));
+        GrayScalePixelType *zeroBuffer = (GrayScalePixelType *)calloc(numberOfImages * width * height, sizeof(GrayScalePixelType));
 
-        if(buffer != NULL)
+        if(zeroBuffer != NULL)
         {
-            for(unsigned int i = 0; i < (numberOfImages * width * height); i++)
+            if(greyScaleTest)
             {
-                buffer[i] = (GrayScalePixelType)i;
+                for(unsigned int i = 0; i < (numberOfImages * width * height); i++)
+                {
+                    zeroBuffer[i] = (GrayScalePixelType)i;
+                }
             }
 
             fwrite(fileTag, sizeof(fileTag[0]), strlen(fileTag), file);
@@ -29,11 +32,11 @@ static void prepareImageFile(const char *path, unsigned short int width, unsigne
 
             for(int i = 0; i < numberOfImages; i++)
             {
-                fwrite(buffer, sizeof(GrayScalePixelType), width * height, file);
+                fwrite(zeroBuffer, sizeof(GrayScalePixelType), width * height, file);
                 fwrite(&label, sizeof(unsigned char), 1, file);
             }
 
-            free(buffer);
+            free(zeroBuffer);
         }
 
         fclose(file);
@@ -46,7 +49,7 @@ void test_readImagesReturnsCorrectNumberOfImages(void)
     GrayScaleImageSeries *series = NULL;
     const unsigned short expectedNumberOfImages = 2;
     const char *path = "testFile.info2";
-    prepareImageFile(path, 8, 8, expectedNumberOfImages, 1);
+    prepareImageFile(path, 8, 8, expectedNumberOfImages, 1, 0);
     series = readImages(path);
     TEST_ASSERT_NOT_NULL(series);
     TEST_ASSERT_EQUAL_UINT16(expectedNumberOfImages, series->count);
@@ -59,7 +62,7 @@ void test_readImagesReturnsCorrectImageWidth(void)
     GrayScaleImageSeries *series = NULL;
     const unsigned short expectedWidth = 10;
     const char *path = "testFile.info2";
-    prepareImageFile(path, expectedWidth, 8,  2, 1);
+    prepareImageFile(path, expectedWidth, 8,  2, 1, 0);
     series = readImages(path);
     TEST_ASSERT_NOT_NULL(series);
     TEST_ASSERT_NOT_NULL(series->images);
@@ -75,7 +78,7 @@ 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, 0);
     series = readImages(path);
     TEST_ASSERT_NOT_NULL(series);
     TEST_ASSERT_NOT_NULL(series->images);
@@ -92,7 +95,7 @@ void test_readImagesReturnsCorrectLabels(void)
 
     GrayScaleImageSeries *series = NULL;
     const char *path = "testFile.info2";
-    prepareImageFile(path, 8, 8, 2, expectedLabel);
+    prepareImageFile(path, 8, 8, 2, expectedLabel, 0);
     series = readImages(path);
     TEST_ASSERT_NOT_NULL(series);
     TEST_ASSERT_NOT_NULL(series->labels);
@@ -129,7 +132,7 @@ void test_readImagesReadsCorrectGrayScales(void)
     GrayScaleImageSeries *series = NULL;
     const char *path = "testFile.info2";
     
-    prepareImageFile(path, 8, 8, 1, 1);
+    prepareImageFile(path, 8, 8, 1, 1, 1);
     series = readImages(path);
 
     TEST_ASSERT_NOT_NULL(series);

I2_NeuronalerAbsturz/Start_Mac/makefile

@@ -40,8 +40,8 @@ mnistVisualization.o: mnistVisualization.c
 matrixTests: matrix.o matrixTests.c
 	$(CC) $(CFLAGS) -I$(unityfolder) -o runMatrixTests matrixTests.c matrix.o $(BINARIES)/libunity.a
 
-neuralNetworkTests: neuralNetwork.o neuralNetworkTests.c matrix.o
+neuralNetworkTests: neuralNetwork.o neuralNetworkTests.c
-	$(CC) $(CFLAGS) -I$(unityfolder) -o runNeuralNetworkTests neuralNetworkTests.c neuralNetwork.o matrix.o $(BINARIES)/libunity.a
+	$(CC) $(CFLAGS) -I$(unityfolder) -o runNeuralNetworkTests neuralNetworkTests.c neuralNetwork.o $(BINARIES)/libunity.a
 
 imageInputTests: imageInput.o imageInputTests.c
 	$(CC) $(CFLAGS) -I$(unityfolder) -o runImageInputTests imageInputTests.c imageInput.o $(BINARIES)/libunity.a

I2_NeuronalerAbsturz/Start_Mac/matrix.c

@@ -42,7 +42,7 @@ void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned
 {
     if (matrix.buffer != NULL)
     {
-        if (rowIdx < matrix.rows && colIdx < matrix.cols)
+        if (rowIdx < matrix.rows || colIdx < matrix.cols)
         {
             matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
         }
@@ -63,7 +63,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
 {
     Matrix result;
 
-    if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.rows != matrix2.rows)
+    if (matrix1.buffer == NULL || matrix2.buffer == NULL || matrix1.rows != matrix2.rows || matrix1.cols != matrix2.cols) 
     {
         result.rows = 0;
         result.cols = 0;
@@ -71,51 +71,17 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
         return result;
     }
 
-    if (matrix1.cols == matrix2.cols)
+    result = createMatrix(matrix1.rows, matrix1.cols);
+
+    for (int i = 0; i < matrix1.rows; i++) 
     {
-        result = createMatrix(matrix1.rows, matrix1.cols);
+        for (int j = 0; j < matrix1.cols; j++) 
-        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);
-                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;
 }
 

I2_NeuronalerAbsturz/Start_Mac/matrixTests.c

@@ -141,32 +141,6 @@ void test_setMatrixAtFailsOnIndicesOutOfRange(void)
     TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, matrixToTest.buffer, matrixToTest.cols * matrixToTest.rows);
 }
 
-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 setUp(void) {
     // Falls notwendig, kann hier Vorbereitungsarbeit gemacht werden
 }
@@ -191,7 +165,6 @@ int main()
     RUN_TEST(test_getMatrixAtFailsOnIndicesOutOfRange);
     RUN_TEST(test_setMatrixAtSetsCorrectValue);
     RUN_TEST(test_setMatrixAtFailsOnIndicesOutOfRange);
-    RUN_TEST(test_addSupportsBroadcasting);
 
     return UNITY_END();
 }

I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c

@@ -5,89 +5,12 @@
 #include "unity.h"
 #include "neuralNetwork.h"
 
-/* 
-################
-Aufbau Test File 
-################
-
-
-HEADER
-
-inputDim
-outputDim
-
--- Layer 1 --
-weights (outputDim * inputDim * MatrixType)
-biases  (outputDim * MatrixType)
-
-outputDim
-
--- Layer 2 --
-weights
-biases
-
-...
-...
--- Layer n --
-weights
-biases
-
-outputDim = 0  => Ende 
-*/
-
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    FILE *file = fopen(path, "wb");
+    // TODO
-    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;
-        int outputDim = nn.layers[0].weights.rows;
-        fwrite(&inputDim, sizeof(int), 1, file);
-        fwrite(&outputDim, sizeof(int), 1, file);
-
-        // erstes Layer schreiben
-        int weightCount = nn.layers[0].weights.rows * nn.layers[0].weights.cols;
-        fwrite(nn.layers[0].weights.buffer, sizeof(MatrixType), weightCount, file);
-
-        int biasesCount = nn.layers[0].biases.rows * nn.layers[0].biases.cols;
-        fwrite(nn.layers[0].biases.buffer, sizeof(MatrixType), biasesCount, file);
-
-        // für weiter Layer nur outputDimension schreiben
-        for (unsigned int i = 1; i < nn.numberOfLayers; i++)
-        {
-            outputDim = nn.layers[i].weights.rows;
-            fwrite(&outputDim, sizeof(int), 1, file);
-
-            weightCount = nn.layers[i].weights.rows * nn.layers[i].weights.cols;
-            fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), weightCount, file);
-
-            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";