code: def __init__(self):
      super().__init__()
      self.lin0 = torch.nn.Linear(dataset.num_features, dim)
  
      nn = Sequential(Linear(5, 128), ReLU(), Linear(128, dim * dim))
      self.conv = NNConv(dim, dim, nn, aggr="mean")
      self.gru = GRU(dim, dim)
  
      self.set2set = Set2Set(dim, processing_steps=3)
      self.lin1 = torch.nn.Linear(2 * dim, dim)
      self.lin2 = torch.nn.Linear(dim, 1)
  
file_path: pytorch_geometric/examples/qm9_nn_conv.py
imports: import copy
  import os.path
  import torch
  import torch.nn.functional
  from torch.nn import GRU, Linear, ReLU, Sequential
  import torch_geometric.transforms
  from torch_geometric.datasets import QM9
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import NNConv, Set2Set
  from torch_geometric.utils import remove_self_loops
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: torch.nn with example: obj = Net()