code: def _parse_model(topology, scope, model, inputs=None, outputs=None):
      '''
      This is a delegate function of all top-level parsing functions. It does nothing but call a proper function
      to parse the given model.
      '''
  
      if inputs is None:
          inputs = list()
      if outputs is None:
          outputs = list()
  
      model_type = model.WhichOneof('Type')
      if model_type in ['pipeline', 'pipelineClassifier', 'pipelineRegressor']:
          _parse_pipeline_model(topology, scope, model, inputs, outputs)
      elif model_type in ['neuralNetworkClassifier', 'neuralNetworkRegressor', 'neuralNetwork']:
          _parse_neural_network_model(topology, scope, model, inputs, outputs)
      else:
          _parse_simple_model(topology, scope, model, inputs, outputsf _parse_model(topology, scope, model, inputs=None, outputs=None):
      '''
      This is a delegate function of all top-level parsing functions. It does nothing but call a proper function
      to parse the given model.
      '''
  
      if inputs is None:
          inputs = list()
      if outputs is None:
          outputs = list()
  
      model_type = model.WhichOneof('Type')
      if model_type in ['pipeline', 'pipelineClassifier', 'pipelineRegressor']:
          _parse_pipeline_model(topology, scope, model, inputs, outputs)
      elif model_type in ['neuralNetworkClassifier', 'neuralNetworkRegressor', 'neuralNetwork']:
          _parse_neural_network_model(topology, scope, model, inputs, outputs)
      else:
          _parse_simple_model(topology, scope, model, inputs, outputs)
docs: This is a delegate function of all top-level parsing functions. It does nothing but call a proper function
      to parse the given model.