code: def create_predict_net(predictor_export_meta):
      """
      Return the input prediction net.
      """
      # Construct a new net to clear the existing settings.
      net = core.Net(
          predictor_export_meta.predict_net.name or "predict"
      )
      net.Proto().op.extend(predictor_export_meta.predict_net.op)
      net.Proto().partition_info.extend(
          predictor_export_meta.predict_net.partition_info
      )
      net.Proto().external_input.extend(
          predictor_export_meta.inputs
          + predictor_export_meta.parameters
      )
      net.Proto().external_output.extend(predictor_export_meta.outputs)
      net.Proto().arg.extend(predictor_export_meta.predict_net.arg)
      if predictor_export_meta.net_type is not None:
          net.Proto().type = predictor_export_meta.net_type
      if predictor_export_meta.num_workers is not None:
          net.Proto().num_workers = predictor_export_meta.num_workers
      return net.Proto()
  
imports: from caffe2.python import core, scope
label_desc: Use image node_id 1 for calling a global function with example usage: create_predict_net(predictor_export_meta) and returns: net