code: def __init__(
      self,
      hidden_channels,
      num_layers,
      alpha,
      theta,
      shared_weights=True,
      dropout=0.0,
  ):
      super().__init__()
  
      self.lins = torch.nn.ModuleList()
      self.lins.append(Linear(dataset.num_features, hidden_channels))
      self.lins.append(Linear(hidden_channels, dataset.num_classes))
  
      self.convs = torch.nn.ModuleList()
      for layer in range(num_layers):
          self.convs.append(
              GCN2Conv(
                  hidden_channels,
                  alpha,
                  theta,
                  layer + 1,
                  shared_weights,
                  normalize=False,
              )
          )
  
      self.dropout = dropout
  
file_path: pytorch_geometric/examples/gcn2_cora.py
imports: import os.path
  import time
  import torch
  import torch.nn.functional
  from torch.nn import Linear
  import torch_geometric.transforms
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import GCN2Conv
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: torch.nn with example: obj = Net(hidden_channels, num_layers, alpha, theta, shared_weights, dropout)