code: def predict(self, edges, num_nodes, feature):
      if args.model == "GraphSage":
          self.input_handles[0].copy_from_cpu(edges)
          self.input_handles[1].copy_from_cpu(feature)
      else:
          self.input_handles[0].copy_from_cpu(edges)
          self.input_handles[1].copy_from_cpu(num_nodes)
          self.input_handles[2].copy_from_cpu(feature)
      self.predictor.run()
  
      logits = self.output_handle.copy_to_cpu()
      return logits
  
file_path: PGL/examples/gnn_depoly/node_classification_with_full_graph/python_deploy.py
imports: import argparse
  import os
  import sys
  import time
  import numpy
  import paddle
  import paddle.nn
  import pgl
label_desc: Use image node_id 2 for calling the Predictor obj's underlying member method code with example usage: obj.predict(edges, num_nodes, feature) and returns: logits