Compare commits

..
4 changed files with 29 additions and 26 deletions
+13
View File
@@ -132,3 +132,16 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
} }
return result; return result;
} }
void writeMatrix(Matrix matrix, FILE *file)//Added for neuralNetworkTests
{
//fprintf(file, "%d%d", matrix.rows, matrix.cols);
for(int i = 0; i < matrix.rows; i++)
{
for(int j = 0; j < matrix.cols; j++)
{
putw(*(matrix.buffer + (j+i)*sizeof(MatrixType)), file);
//fprintf(file, "%f", *(matrix.buffer + (j+i)*sizeof(MatrixType)));
printf("%f", *(matrix.buffer + (j+i)*sizeof(MatrixType)));
}
}
}
+1
View File
@@ -21,6 +21,7 @@ void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned
MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx); MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
Matrix add(const Matrix matrix1, const Matrix matrix2); Matrix add(const Matrix matrix1, const Matrix matrix2);
Matrix multiply(const Matrix matrix1, const Matrix matrix2); Matrix multiply(const Matrix matrix1, const Matrix matrix2);
void writeMatrix(Matrix matrix, FILE *file);//Added for neuralNetworkTests
#endif #endif
+2 -1
View File
@@ -155,6 +155,7 @@ NeuralNetwork loadModel(const char *path)
model.layers[model.numberOfLayers] = layer; model.layers[model.numberOfLayers] = layer;
model.numberOfLayers++; model.numberOfLayers++;
inputDimension = outputDimension; inputDimension = outputDimension;
outputDimension = readDimension(file); outputDimension = readDimension(file);
} }
@@ -169,7 +170,7 @@ NeuralNetwork loadModel(const char *path)
static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count) static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count)
{ {
Matrix matrix = {0, 0, NULL}; // TODO changed this line to fit our functionality Matrix matrix = {NULL, 0, 0};
if(count > 0 && images != NULL) if(count > 0 && images != NULL)
{ {
+13 -25
View File
@@ -4,34 +4,23 @@
#include <math.h> #include <math.h>
#include "unity.h" #include "unity.h"
#include "neuralNetwork.h" #include "neuralNetwork.h"
#include "matrix.h"
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
{ {
// TODO FILE *testDatei = fopen(path, "w");
FILE* file = fopen(path, "wb"); fprintf(testDatei, "__info2_neural_network_file_format__");
if(file == NULL) { fprintf(testDatei, "%d%d", nn.layers->weights.rows, nn.layers->weights.cols);
printf("Failed to open file"); // fprintf(testDatei, (char*) nn.numberOfLayers);
return; for(int i = 0; i < nn.numberOfLayers; i++)
{
//fprintf(testDatei, "\n");
//putw((nn.layers + sizeof(Layer) * i), testDatei);
writeMatrix(nn.layers[i].weights, testDatei);
writeMatrix(nn.layers[i].biases, testDatei);
} }
printf("\nLayers in pNNF: %d\n", nn.numberOfLayers); fclose(testDatei);
const char* header = "__info2_neural_network_file_format__";
fwrite(header, sizeof(const char), strlen(header), file);
for (int i = 0; i < nn.numberOfLayers; i++) {
fwrite(&(nn.layers[i].weights.cols), sizeof(unsigned int), 1, file);
fwrite(&(nn.layers[i].weights.rows), sizeof(unsigned int), 1, file);
}
for(int i = 0; i < nn.numberOfLayers; i++) {
//write everything to do with weights
fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), nn.layers[i].weights.rows * nn.layers[i].weights.cols, file);
//write everything to do with biases
fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), nn.layers[i].biases.rows * nn.layers[i].biases.cols, file);
}
fclose(file);
} }
void test_loadModelReturnsCorrectNumberOfLayers(void) void test_loadModelReturnsCorrectNumberOfLayers(void)
@@ -48,14 +37,13 @@ void test_loadModelReturnsCorrectNumberOfLayers(void)
Layer layers[] = {{.weights=weights1, .biases=biases1}, {.weights=weights2, .biases=biases2}}; Layer layers[] = {{.weights=weights1, .biases=biases1}, {.weights=weights2, .biases=biases2}};
NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=2}; NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=2};
printf("\nexpectedNetLayers: %d", expectedNet.numberOfLayers);
NeuralNetwork netUnderTest; NeuralNetwork netUnderTest;
prepareNeuralNetworkFile(path, expectedNet); prepareNeuralNetworkFile(path, expectedNet);
netUnderTest = loadModel(path); netUnderTest = loadModel(path);
remove(path); remove(path);
printf("\n%d\n%d\n", netUnderTest.numberOfLayers, expectedNet.numberOfLayers);
TEST_ASSERT_EQUAL_INT(expectedNet.numberOfLayers, netUnderTest.numberOfLayers); TEST_ASSERT_EQUAL_INT(expectedNet.numberOfLayers, netUnderTest.numberOfLayers);
clearModel(&netUnderTest); clearModel(&netUnderTest);
} }