updating

.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/neuralNetwork.c

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

Startcode/neuralNetworkTests.c

@@ -5,46 +5,10 @@
 #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)
 {
-    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);
+    // TODO
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)