code: def __init__(
      self, in_channels, hidden_channels, out_channels, num_layers
  ):
      super().__init__()
  
      self.convs = torch.nn.ModuleList()
      for _ in range(num_layers):
          mlp = MLP([in_channels, hidden_channels, hidden_channels])
          self.convs.append(GINConv(nn=mlp, train_eps=False))
          in_channels = hidden_channels
  
      self.mlp = MLP(
          [hidden_channels, hidden_channels, out_channels],
          norm=None,
          dropout=0.5,
      )
  
file_path: pytorch_geometric/examples/compile/gin.py
imports: import os.path
  import time
  import torch
  import torch.nn.functional
  import torch_geometric
  from torch_geometric.datasets import TUDataset
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import MLP, GINConv, global_add_pool
label_desc: Use image node_id 1 to create a new GIN object from inherited base classes: torch.nn with example: obj = GIN(in_channels, hidden_channels, out_channels, num_layers)