code: def test(model, xs, y_true, evaluator):
      model.eval()
  
      y_preds = []
      loader = DataLoader(range(y_true.size(0)), batch_size=400000)
      for perm in loader:
          y_pred = model([x[perm] for x in xs]).argmax(
              dim=-1, keepdim=True
          )
          y_preds.append(y_pred.cpu())
      y_pred = torch.cat(y_preds, dim=0)
  
      return evaluator.eval(
          {
              "y_true": y_true,
              "y_pred": y_pred,
          }
      )["acc"]
  
file_path: ogb/examples/nodeproppred/products/sign.py
imports: import argparse
  import torch
  import torch.nn.functional
  from torch.utils.data import DataLoader
  from torch_geometric.transforms import SIGN
  from ogb.nodeproppred import PygNodePropPredDataset, Evaluator
  from logger import Logger
label_desc: Use image node_id 2 for calling a global function with example usage: test(model, xs, y_true, evaluator) and returns: evaluator