generated from freudenreichan/info2Praktikum-NeuronalesNetz
added some alternatives, however non of them work
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parent
06782431a4
commit
4272d04f0d
5
matrix.c
5
matrix.c
@ -134,11 +134,14 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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}
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}
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void writeMatrix(Matrix matrix, FILE *file)//Added for neuralNetworkTests
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void writeMatrix(Matrix matrix, FILE *file)//Added for neuralNetworkTests
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{
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{
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//fprintf(file, "%d%d", matrix.rows, matrix.cols);
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for(int i = 0; i < matrix.rows; i++)
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for(int i = 0; i < matrix.rows; i++)
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{
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{
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for(int j = 0; j < matrix.cols; j++)
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for(int j = 0; j < matrix.cols; j++)
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{
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{
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fprintf(file, (char*)(matrix.buffer + (j+i)*sizeof(MatrixType)));
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putw(*(matrix.buffer + (j+i)*sizeof(MatrixType)), file);
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//fprintf(file, "%f", *(matrix.buffer + (j+i)*sizeof(MatrixType)));
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printf("%f", *(matrix.buffer + (j+i)*sizeof(MatrixType)));
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}
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}
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}
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}
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}
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}
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@ -11,9 +11,12 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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{
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{
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FILE *testDatei = fopen(path, "w");
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FILE *testDatei = fopen(path, "w");
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fprintf(testDatei, "__info2_neural_network_file_format__");
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fprintf(testDatei, "__info2_neural_network_file_format__");
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fprintf(testDatei, "%d%d", nn.layers->weights.rows, nn.layers->weights.cols);
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// fprintf(testDatei, (char*) nn.numberOfLayers);
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for(int i = 0; i < nn.numberOfLayers; i++)
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for(int i = 0; i < nn.numberOfLayers; i++)
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{
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{
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fprintf(testDatei, "\n");
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//fprintf(testDatei, "\n");
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//putw((nn.layers + sizeof(Layer) * i), testDatei);
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writeMatrix(nn.layers[i].weights, testDatei);
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writeMatrix(nn.layers[i].weights, testDatei);
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writeMatrix(nn.layers[i].biases, testDatei);
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writeMatrix(nn.layers[i].biases, testDatei);
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}
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}
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@ -40,7 +43,7 @@ void test_loadModelReturnsCorrectNumberOfLayers(void)
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netUnderTest = loadModel(path);
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netUnderTest = loadModel(path);
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remove(path);
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remove(path);
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printf("\n%d\n%d\n", netUnderTest.numberOfLayers, expectedNet.numberOfLayers);
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TEST_ASSERT_EQUAL_INT(expectedNet.numberOfLayers, netUnderTest.numberOfLayers);
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TEST_ASSERT_EQUAL_INT(expectedNet.numberOfLayers, netUnderTest.numberOfLayers);
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clearModel(&netUnderTest);
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clearModel(&netUnderTest);
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}
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}
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