code: def __init__(self, g, in_channels, out_channels):
      super().__init__()
      self.g = g
      self.conv1 = GATConv(g, in_channels, 8, 8, 0.6, 0.2)
      self.conv2 = GATConv(g, 64, out_channels, 1, 0.6, 0.2)
  
imports: import dgl.function
  import torch
  import torch.nn.functional
  from dgl.nn.pytorch import EdgeSoftmax
  from torch.nn import Parameter
  from torch_geometric.nn.inits import glorot, zeros
label_desc: Use image node_id 1 to create a new GAT object from inherited base classes: torch.nn with example: obj = GAT(g, in_channels, out_channels)