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vinnsl_decoder.py
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vinnsl_decoder.py
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import json
def parse_vinnsl(vinnsl):
nn_structure = {}
parsed_json = json.loads(vinnsl)
parameters = parsed_json['parameters']['input']
structure = parsed_json['structure']
learning_rate = parameters[0]['defaultValue']
biasInput = parameters[1]['defaultValue']
biasHidden = parameters[2]['defaultValue']
momentum = parameters[3]['defaultValue']
activationFunctionOutput = parameters[4]['defaultValue']
activationFunctionHidden = parameters[5]['defaultValue']
threshold = parameters[6]['defaultValue']
target_data = parameters[7]['defaultValue']
number_epochs = parameters[8]['defaultValue']
connections = parsed_json['connections']
fully_connected = connections['fullyConnected']['isConnected']
shortcuts = connections['shortcuts']
shortcuts_connections = shortcuts['connections']
print(fully_connected)
input_layer = structure['inputLayer']
input_neurons = input_layer['amount']
outputLayer = structure['outputLayer']
output_neurons = outputLayer['amount']
hidden_layers = structure['hiddenLayer']
hidden_layers_neurons = []
for layer in hidden_layers:
hidden_layers_neurons.append(layer['amount'])
nn_structure['input_neurons'] = input_neurons
nn_structure['output_neurons'] = output_neurons
nn_structure['hidden_layers'] = hidden_layers_neurons
nn_structure['learning_rate'] = learning_rate
nn_structure['biasInput'] = biasInput
nn_structure['biasHidden'] = biasHidden
nn_structure['momentum'] = momentum
nn_structure['activationFunctionOutput'] = activationFunctionOutput
nn_structure['activationFunctionHidden'] = activationFunctionHidden
nn_structure['threshold'] = threshold
nn_structure['target_data'] = target_data
nn_structure['number_epochs'] = number_epochs
print(nn_structure)
return nn_structure