generated from freudenreichan/info2Praktikum-NeuronalesNetz
Added a prepareNeuralNetwork funktion, that compiles but fails 6/8 tests
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0a8349d722
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06782431a4
10
matrix.c
10
matrix.c
@ -131,4 +131,14 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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}
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}
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return result;
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}
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void writeMatrix(Matrix matrix, FILE *file)//Added for neuralNetworkTests
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{
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for(int i = 0; i < matrix.rows; i++)
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{
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for(int j = 0; j < matrix.cols; j++)
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{
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fprintf(file, (char*)(matrix.buffer + (j+i)*sizeof(MatrixType)));
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}
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}
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}
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1
matrix.h
1
matrix.h
@ -21,6 +21,7 @@ void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned
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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
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Matrix add(const Matrix matrix1, const Matrix matrix2);
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Matrix multiply(const Matrix matrix1, const Matrix matrix2);
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void writeMatrix(Matrix matrix, FILE *file);//Added for neuralNetworkTests
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#endif
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@ -4,11 +4,20 @@
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#include <math.h>
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#include "unity.h"
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#include "neuralNetwork.h"
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#include "matrix.h"
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static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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{
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// TODO
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FILE *testDatei = fopen(path, "w");
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fprintf(testDatei, "__info2_neural_network_file_format__");
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for(int i = 0; i < nn.numberOfLayers; i++)
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{
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fprintf(testDatei, "\n");
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writeMatrix(nn.layers[i].weights, testDatei);
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writeMatrix(nn.layers[i].biases, testDatei);
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}
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fclose(testDatei);
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}
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void test_loadModelReturnsCorrectNumberOfLayers(void)
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