class_docstr: The ModelGraph represents the network that is being processed by hls4ml.
  
  Args:
      config (dict):  The configuration dictionary
      layer_list (list(dict)):  The list contains a dictionary for each input layer
      inputs (list, optional):  The inputs to the model. If None, determined from layer_list
      outputs (list, optional):  The outputs to the model. If None, determined from layer_list
docstr: Update the model outputs
  
  All node outputs and inputs are found. The model outputs are set to all node outputs
  that are not also node inputs.
docstr_tok: ["Update","the","model","outputs","All","node","outputs","and","inputs","are","found",".","The","model","outputs","are","set","to","all","node","outputs","that","are","not","also","node","inputs","."]
code: def _update_model_outputs(self):
      """Update the model outputs
  
      All node outputs and inputs are found. The model outputs are set to all node outputs
      that are not also node inputs.
      """
      node_outputs = [
          out for node in self.graph.values() for out in node.outputs
      ]
      node_inputs = [
          inp for node in self.graph.values() for inp in node.inputs
      ]
      self.outputs = [
          out for out in node_outputs if out not in node_inputs
      ]
  
imports: import ctypes
  import os
  import platform
  from collections import OrderedDict
  import numpy
  import numpy.ctypeslib
  from hls4ml.backends import get_backend
  from hls4ml.model.flow import get_flow
  from hls4ml.model.layers import layer_map
  from hls4ml.model.optimizer import get_available_passes, optimize_model
label_desc: Use image node_id 10 for calling the ModelGraph obj's underlying member method code with example usage: obj._update_model_outputs() without return types