gramppto99138/NeuesNeuesNeuralesNetzwerk
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Lukas Weber 2025-11-27 15:21:35 +01:00
parent 0aa42abd43
commit e544da140e
2 changed files with 2 additions and 3 deletions
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2
neuralNetwork.c
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@ -133,7 +133,6 @@ NeuralNetwork loadModel(const char *path)
while(inputDimension > 0 && outputDimension > 0) while(inputDimension > 0 && outputDimension > 0)
{ {
printf("\nID: %d, OD: %d\n", inputDimension, outputDimension);
Layer layer = readLayer(file, inputDimension, outputDimension); Layer layer = readLayer(file, inputDimension, outputDimension);
Layer *layerBuffer = NULL; Layer *layerBuffer = NULL;
@ -156,7 +155,6 @@ NeuralNetwork loadModel(const char *path)
model.layers[model.numberOfLayers] = layer; model.layers[model.numberOfLayers] = layer;
model.numberOfLayers++; model.numberOfLayers++;
printf("\nNumber of Layers is now: %d\n", model.numberOfLayers);
inputDimension = outputDimension; inputDimension = outputDimension;
outputDimension = readDimension(file); outputDimension = readDimension(file);
} }

3
neuralNetworkTests.c
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@ -14,7 +14,7 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
printf("Failed to open file"); printf("Failed to open file");
return; return;
} }
printf("\nLayers in pNNF: %d\n", nn.numberOfLayers);
const char* header = "__info2_neural_network_file_format__"; const char* header = "__info2_neural_network_file_format__";
fwrite(header, sizeof(const char), strlen(header), file); fwrite(header, sizeof(const char), strlen(header), file);
@ -48,6 +48,7 @@ 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);