code: def __init__(self, num_features, num_classes):
      super(GAT, self).__init__()
      self.conv1 = GATConv(
          num_features,
          8,
          8,
          feat_drop=0.6,
          attn_drop=0.6,
          activation=F.relu,
      )
      self.conv2 = GATConv(
          8 * 8, num_classes, 1, feat_drop=0.6, attn_drop=0.6
      )
  
imports: import numpy
  from tqdm import tqdm
  import pickle
  import torch
  import torch.nn.functional
  from dgl.data import CoraGraphDataset, PubmedGraphDataset, CiteseerGraphDataset
  from dgl.nn.pytorch import GraphConv, 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)