code: def optimizer(self):
      if self.__optimizer is None:
          self.__optimizer = torch.optim.Adam(
              self.model.parameters(), lr=0.01, weight_decay=0.0005
          )
      return self.__optimizer
  
imports: from .trainers_pyg import PyGTrainer
  from models.pyg import CuGraphSAGE
  import torch
  import numpy
  from torch.nn.parallel import DistributedDataParallel
  from cugraph.gnn import FeatureStore
  from cugraph_pyg.data import CuGraphStore
  from cugraph_pyg.loader import BulkSampleLoader
  import os
label_desc: Use image node_id 5 for calling the PyGCuGraphTrainer obj's underlying member method code with example usage: obj.optimizer() and returns: self