code: def inference(self, loader, device, progress_bar=False, **kwargs):
      self.model.eval()
      if progress_bar:
          loader = tqdm(loader, desc="Inference")
      for batch in loader:
          batch = batch.to(device)
          if "adj_t" in batch:
              self.model(batch.x_dict, batch.adj_t_dict)
          else:
              self.model(batch.x_dict, batch.edge_index_dict)
  
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 3 for calling the HeteroGAT obj's underlying member method code with example usage: obj.inference(loader, device, progress_bar) without return types