code: def __init__(
      self,
      in_channels,
      hidden_channels,
      out_channels,
      num_layers,
      heads=1,
      groups=1,
  ):
      super().__init__()
      self.hidden_channels = hidden_channels
      self.lin1 = torch.nn.Linear(in_channels, hidden_channels)
      self.convs = torch.nn.ModuleList()
      for i in range(num_layers):
          self.convs.append(
              DNAConv(hidden_channels, heads, groups, dropout=0.8)
          )
      self.lin2 = torch.nn.Linear(hidden_channels, out_channels)
  
file_path: pytorch_geometric/examples/dna.py
imports: import os.path
  import torch
  import torch.nn.functional
  from sklearn.model_selection import StratifiedKFold
  from torch_geometric.datasets import Planetoid
  from torch_geometric.nn import DNAConv
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: torch.nn with example: obj = Net(in_channels, hidden_channels, out_channels, num_layers, heads, groups)