neuralNetwork fixed

Reviewed-on: freudenreichan/info2Praktikum-NeuronalesNetz#4

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);

neuralNetwork.c

@@ -170,7 +170,7 @@ NeuralNetwork loadModel(const char *path)
 
 static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count)
 {
-    Matrix matrix = {NULL, 0, 0};
+    Matrix matrix = {0, 0, NULL};
 
     if(count > 0 && images != NULL)
     {

neuralNetworkTests.c

@@ -5,10 +5,46 @@
 #include "unity.h"
 #include "neuralNetwork.h"
 
+static void writeLayer(FILE *file, const Matrix weights, const Matrix biases, unsigned int inputDim)
+{
+    unsigned int outputDim = (unsigned int)weights.rows;
+    fwrite(&outputDim, sizeof(unsigned int), 1, file);
+    if (weights.buffer != NULL)
+        fwrite(weights.buffer, sizeof(MatrixType), outputDim * inputDim, file);
+
+    if (biases.buffer != NULL)
+        fwrite(biases.buffer, sizeof(MatrixType), outputDim, file);
+}
+
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *file = fopen(path, "wb");
+    if (!file) return;
+
+    const char tag[] = "__info2_neural_network_file_format__";
+    fwrite(tag, sizeof(char), strlen(tag), file);
+
+    if (nn.numberOfLayers == 0)
+    {
+        unsigned int zero = 0;
+        fwrite(&zero, sizeof(unsigned int), 1, file);
+        fclose(file);
+        return;
+    }
+
+    unsigned int inputDim = (unsigned int)nn.layers[0].weights.cols;
+    fwrite(&inputDim, sizeof(unsigned int), 1, file);
+
+    for (int i = 0; i < nn.numberOfLayers; i++)
+    {
+        writeLayer(file, nn.layers[i].weights, nn.layers[i].biases, inputDim);
+        inputDim = (unsigned int)nn.layers[i].weights.rows;
+    }
+    unsigned int zero = 0;
+    fwrite(&zero, sizeof(unsigned int), 1, file);
+
+    fclose(file);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)