code: def test(loader):
      model.eval()
      total_correct = total_examples = 0
      for data in loader:
          data = data.to(device)
          out = model(
              data.x, data.edge_index, data.batch, data.root_n_id
          )
          total_correct += int((out.argmax(dim=-1) == data.y).sum())
          total_examples += data.num_graphs
      return total_correct / total_examples
  
file_path: pytorch_geometric/examples/shadow.py
imports: import os.path
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Flickr
  from torch_geometric.loader import ShaDowKHopSampler
  from torch_geometric.nn import SAGEConv, global_mean_pool
label_desc: Use image node_id 2 for calling a global function with example usage: test(loader) and returns: unknown