parameters: (spec)
return_statement: return layers
docstring: Returns a list of neural network layers if the model contains any.
  
      Parameters
      ----------
      spec: Model_pb
          A model protobuf specification.
  
      Returns
      -------
      [NN layer]
          list of all layers (including layers from elements of a pipeline
docstring_summary: Returns a list of neural network layers if the model contains any.
docstring_tokens: Returns a list of neural network layers if the model contains any .
function: def _get_nn_layers(spec):
      """
      Returns a list of neural network layers if the model contains any.
  
      Parameters
      ----------
      spec: Model_pb
          A model protobuf specification.
  
      Returns
      -------
      [NN layer]
          list of all layers (including layers from elements of a pipeline
  
      """
  
      layers = []
      if spec.WhichOneof("Type") == "pipeline":
          layers = []
          for model_spec in spec.pipeline.models:
              if not layers:
                  return _get_nn_layers(model_spec)
              else:
                  layers.extend(_get_nn_layers(model_spec))
  
      elif spec.WhichOneof("Type") in ["pipelineClassifier", "pipelineRegressor"]:
          layers = []
          for model_spec in spec.pipeline.models:
              if not layers:
                  return _get_nn_layers(model_spec)
              else:
                  layers.extend(_get_nn_layers(model_spec))
  
      elif spec.neuralNetwork.layers:
          layers = spec.neuralNetwork.layers
      elif spec.neuralNetworkClassifier.layers:
          layers = spec.neuralNetworkClassifier.layers
      elif spec.neuralNetworkRegressor.layers:
          layers = spec.neuralNetworkRegressor.layers
  
      return layers
function_tokens: def _get_nn_layers ( spec ) : layers = [ ] if spec . WhichOneof ( "Type" ) == "pipeline" : layers = [ ] for model_spec in spec . pipeline . models : if not layers : return _get_nn_layers ( model_spec ) else : layers . extend ( _get_nn_layers ( model_spec ) ) elif spec . WhichOneof ( "Type" ) in [ "pipelineClassifier" , "pipelineRegressor" ] : layers = [ ] for model_spec in spec . pipeline . models : if not layers : return _get_nn_layers ( model_spec ) else : layers . extend ( _get_nn_layers ( model_spec ) ) elif spec . neuralNetwork . layers : layers = spec . neuralNetwork . layers elif spec . neuralNetworkClassifier . layers : layers = spec . neuralNetworkClassifier . layers elif spec . neuralNetworkRegressor . layers : layers = spec . neuralNetworkRegressor . layers return layers