code: def test(loader: NeighborLoader, val_steps: Optional[int] = None):
      model.eval()
  
      total_correct = total_examples = 0
      for i, batch in enumerate(loader):
          if val_steps is not None and i >= val_steps:
              break
  
          batch = batch.to(device)
          out = model(batch.x, batch.edge_index)[: batch.batch_size]
          pred = out.argmax(dim=-1)
          y = batch.y[: batch.batch_size].view(-1).to(torch.long)
  
          total_correct += int((pred == y).sum())
          total_examples += y.size(0)
  
      return total_correct / total_examples
  
file_path: pytorch_geometric/examples/ogbn_papers_100m.py
imports: import os
  import time
  from typing import Optional
  import torch
  import torch.nn.functional
  from ogb.nodeproppred import PygNodePropPredDataset
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import GCNConv
label_desc: Use image node_id 3 for calling a global function with example usage: test(loader, val_steps) and returns: unknown