code: def test():  # Inference should be performed on the full graph.
      model.eval()
  
      out = model.inference(data.x)
      y_pred = out.argmax(dim=-1)
  
      accs = []
      for mask in [data.train_mask, data.val_mask, data.test_mask]:
          correct = y_pred[mask].eq(data.y[mask]).sum().item()
          accs.append(correct / mask.sum().item())
      return accs
  
file_path: pytorch_geometric/examples/cluster_gcn_reddit.py
imports: import time
  import torch
  import torch.nn.functional
  from torch.nn import ModuleList
  from tqdm import tqdm
  from torch_geometric.datasets import Reddit
  from torch_geometric.loader import ClusterData, ClusterLoader, NeighborLoader
  from torch_geometric.nn import SAGEConv
label_desc: Use image node_id 2 for calling a global function with example usage: test() and returns: accs