code: def prepare(cls, model, device='CPU', **kwargs):
          
          graph = GraphProto()
          sym, params = graph.from_onnx(model.graph)
          return MXNetBackendRep(sym, params, device)
docs: For running end to end model(used for onnx test backend)
  
          Parameters
          ----------
          model  : onnx ModelProto object
              loaded onnx graph
          device : 'CPU'
              specifying device to run test on
          kwargs :
              other arguments
  
          Returns
          -------
          MXNetBackendRep : object
              Returns object of MXNetBackendRep class which will be in turn
              used to run inference on the input model and return the result for comparison.