code: def __init__(
      self,
      metadata,
      hidden_channels,
      num_layers,
      output_channels,
      num_heads,
  ):
      super().__init__()
      self.model = to_hetero(
          GAT(
              (-1, -1),
              hidden_channels,
              num_layers,
              output_channels,
              add_self_loops=False,
              heads=num_heads,
          ),
          metadata,
      )
  
file_path: pytorch_geometric/benchmark/utils/hetero_gat.py
imports: import torch
  from tqdm import tqdm
  from torch_geometric.nn import GAT, to_hetero
label_desc: Use image node_id 1 to create a new HeteroGAT object from inherited base classes: torch.nn with example: obj = HeteroGAT(metadata, hidden_channels, num_layers, output_channels, num_heads)