code: def configure(self, data, model, args):
      super(ONNXMLBackend, self).configure(data, model, args)
      self.params.update({"operator": args.operator})
  
imports: from abc import ABC, abstractmethod
  import numpy
  from benchmarks.timer import Timer
  from benchmarks.datasets import LearningTask
  from hummingbird.ml import constants
  from hummingbird.ml import convert, convert_batch
label_desc: Use image node_id 2 for calling the ONNXMLBackend obj's underlying member method code with example usage: obj.configure(data, model, args) without return types