code: def __init__(self, num_features, num_classes):
      super(GAT, self).__init__()
  
      self.conv1 = GATConv(num_features, 8, heads=8, dropout=0.6)
      self.conv2 = GATConv(
          8 * 8, num_classes, heads=1, concat=False, dropout=0.6
      )
  
imports: import os
  import random
  import numpy
  from tqdm import tqdm
  import pickle
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Planetoid
  import torch_geometric.transforms
  from torch_geometric.nn import GCNConv, GATConv, SAGEConv
  import logging
label_desc: Use image node_id 1 to create a new GAT object from inherited base classes: torch.nn with example: obj = GAT(num_features, num_classes)