code: def __init__(
      self, in_size, out_size, hidden_size=8, num_heads=8, dropout=0.6
  ):
      super().__init__()
  
      self.in_conv = GATConv(
          in_size, hidden_size, num_heads=num_heads, dropout=dropout
      )
      self.out_conv = GATConv(
          hidden_size * num_heads,
          out_size,
          num_heads=1,
          dropout=dropout,
      )
  
file_path: dgl/examples/sparse/gat.py
imports: import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data import CoraGraphDataset
  from torch.optim import Adam
label_desc: Use image node_id 1 to create a new GAT object from inherited base classes: nn with example: obj = GAT(in_size, out_size, hidden_size, num_heads, dropout)