code: def test(loader):
      model.eval()
  
      corrects, total_ratio = [], 0
      for data in loader:
          data = data.to(device)
          out, _, ratio = model(data)
          pred = out.round().to(torch.long)
          corrects.append(pred.eq(data.y.to(torch.long)))
          total_ratio += ratio
      return torch.cat(corrects, dim=0), total_ratio / len(loader)
  
file_path: pytorch_geometric/examples/triangles_sag_pool.py
imports: import copy
  import os.path
  import torch
  import torch.nn.functional
  from torch.nn import Linear
  from torch.nn import ReLU
  from torch.nn import Sequential
  import torch_geometric.transforms
  from torch_geometric.datasets import TUDataset
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import GCNConv, GINConv, SAGPooling, global_max_pool
  from torch_geometric.utils import scatter
label_desc: Use image node_id 2 for calling a global function with example usage: test(loader) and returns: torch,  unknown