generated from freudenreichan/info2Praktikum-NeuronalesNetz
Added some stuff to pNNF again
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0f28ee3f02
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@ -133,6 +133,7 @@ NeuralNetwork loadModel(const char *path)
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while(inputDimension > 0 && outputDimension > 0)
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{
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printf("\nID: %d, OD: %d\n", inputDimension, outputDimension);
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Layer layer = readLayer(file, inputDimension, outputDimension);
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Layer *layerBuffer = NULL;
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@ -155,7 +156,7 @@ NeuralNetwork loadModel(const char *path)
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model.layers[model.numberOfLayers] = layer;
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model.numberOfLayers++;
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printf("\nNumber of Layers is now: %d\n", model.numberOfLayers);
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inputDimension = outputDimension;
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outputDimension = readDimension(file);
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}
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@ -17,17 +17,18 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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const char* header = "__info2_neural_network_file_format__";
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fwrite(header, sizeof(const char), strlen(header), file);
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fwrite(&(nn.numberOfLayers), sizeof(unsigned int), 1, file);
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fwrite(&(nn.numberOfLayers), sizeof(unsigned int), 1, file);
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for (int i = 0; i < nn.numberOfLayers; i++) {
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fwrite(&(nn.layers[i].weights.cols), sizeof(unsigned int), 1, file);
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fwrite(&(nn.layers[i].weights.rows), sizeof(unsigned int), 1, file);
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}
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for(int i = 0; i < nn.numberOfLayers; i++) {
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//write everything to do with weights
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fwrite(&(nn.layers[i].weights.rows), sizeof(unsigned int), 1, file);
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fwrite(&(nn.layers[i].weights.cols), sizeof(unsigned int), 1, file);
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fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), nn.layers[i].weights.rows * nn.layers[i].weights.cols, file);
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//write everything to do with biases
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fwrite(&(nn.layers[i].biases.rows), sizeof(unsigned int), 1, file);
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fwrite(&(nn.layers[i].biases.cols), sizeof(unsigned int), 1, file);
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fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), nn.layers[i].biases.rows * nn.layers[i].biases.cols, file);
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}
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fclose(file);
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