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matrix.c
4
matrix.c
@ -67,7 +67,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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return result;
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return result;
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}
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}
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// Case B: matrix1 has shape (rows x cols) and matrix2 is (rows x 1) -> broadcast second across columns
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// Case B: matrix1 besteht aus (rows x cols) und matrix2 ist (rows x 1) -> einmal alle rows einzeln auf die andere Addieren
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if (matrix1.rows == matrix2.rows && matrix2.cols == 1 && matrix1.cols > 1)
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if (matrix1.rows == matrix2.rows && matrix2.cols == 1 && matrix1.cols > 1)
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{
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{
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Matrix result = createMatrix(matrix1.rows, matrix1.cols);
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Matrix result = createMatrix(matrix1.rows, matrix1.cols);
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@ -84,7 +84,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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return result;
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return result;
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}
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}
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// Case C: matrix1 is (rows x 1) and matrix2 is (rows x cols) -> broadcast first across columns
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// Case C: matrix1 ist (rows x 1) und matrix2 ist (rows x cols) -> einmal alle cols einzeln auf die andere Addieren
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if (matrix2.rows == matrix1.rows && matrix1.cols == 1 && matrix2.cols > 1)
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if (matrix2.rows == matrix1.rows && matrix1.cols == 1 && matrix2.cols > 1)
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{
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{
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Matrix result = createMatrix(matrix2.rows, matrix2.cols);
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Matrix result = createMatrix(matrix2.rows, matrix2.cols);
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@ -52,8 +52,6 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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fclose(file);
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fclose(file);
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}
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}
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void test_loadModelReturnsCorrectNumberOfLayers(void)
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void test_loadModelReturnsCorrectNumberOfLayers(void)
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{
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{
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const char *path = "some__nn_test_file.info2";
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const char *path = "some__nn_test_file.info2";
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