generated from freudenreichan/info2Praktikum-NeuronalesNetz
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2 Commits
0f28ee3f02
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e544da140e
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| e544da140e | |||
| 0aa42abd43 |
@ -155,7 +155,6 @@ NeuralNetwork loadModel(const char *path)
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model.layers[model.numberOfLayers] = layer;
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model.layers[model.numberOfLayers] = layer;
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model.numberOfLayers++;
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model.numberOfLayers++;
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inputDimension = outputDimension;
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inputDimension = outputDimension;
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outputDimension = readDimension(file);
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outputDimension = readDimension(file);
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}
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}
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@ -14,20 +14,21 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
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printf("Failed to open file");
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printf("Failed to open file");
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return;
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return;
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}
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}
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printf("\nLayers in pNNF: %d\n", nn.numberOfLayers);
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const char* header = "__info2_neural_network_file_format__";
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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(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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for(int i = 0; i < nn.numberOfLayers; i++) {
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//write everything to do with weights
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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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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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//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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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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}
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fclose(file);
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fclose(file);
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@ -47,6 +48,7 @@ void test_loadModelReturnsCorrectNumberOfLayers(void)
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Layer layers[] = {{.weights=weights1, .biases=biases1}, {.weights=weights2, .biases=biases2}};
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Layer layers[] = {{.weights=weights1, .biases=biases1}, {.weights=weights2, .biases=biases2}};
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NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=2};
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NeuralNetwork expectedNet = {.layers=layers, .numberOfLayers=2};
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printf("\nexpectedNetLayers: %d", expectedNet.numberOfLayers);
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NeuralNetwork netUnderTest;
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NeuralNetwork netUnderTest;
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prepareNeuralNetworkFile(path, expectedNet);
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prepareNeuralNetworkFile(path, expectedNet);
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