code: def get_meta_net_def(predictor_export_meta, ws=None, db_type=None):
      """ """
  
      ws = ws or workspace.C.Workspace.current
      meta_net_def = metanet_pb2.MetaNetDef()
  
      # Predict net is the core network that we use.
      utils.AddNet(
          meta_net_def,
          predictor_export_meta.predict_init_name(),
          utils.create_predict_init_net(ws, predictor_export_meta),
      )
      utils.AddNet(
          meta_net_def,
          predictor_export_meta.global_init_name(),
          _global_init_net(predictor_export_meta, db_type),
      )
      utils.AddNet(
          meta_net_def,
          predictor_export_meta.predict_net_name(),
          utils.create_predict_net(predictor_export_meta),
      )
      utils.AddBlobs(
          meta_net_def,
          predictor_export_meta.parameters_name(),
          predictor_export_meta.parameters,
      )
      utils.AddBlobs(
          meta_net_def,
          predictor_export_meta.inputs_name(),
          predictor_export_meta.inputs,
      )
      utils.AddBlobs(
          meta_net_def,
          predictor_export_meta.outputs_name(),
          predictor_export_meta.outputs,
      )
      return meta_net_def
  
imports: from caffe2.proto import caffe2_pb2
  from caffe2.proto import metanet_pb2
  from caffe2.python import workspace, core, scope
  from caffe2.python.predictor_constants import predictor_constants
  import caffe2.python.predictor.serde
  import caffe2.python.predictor.predictor_py_utils
  import collections
label_desc: Use image node_id 4 for calling a global function with example usage: get_meta_net_def(predictor_export_meta, ws, db_type) and returns: meta_net_def