code: def eval_acc(model, loader):
      model.eval()
  
      correct = 0
      for data in loader:
          data = data.to(device)
          with torch.no_grad():
              pred = model(data).max(1)[1]
          correct += pred.eq(data.y.view(-1)).sum().item()
      return correct / len(loader.dataset)
  
file_path: pytorch_geometric/benchmark/kernel/train_eval.py
imports: import time
  import torch
  import torch.nn.functional
  from sklearn.model_selection import StratifiedKFold
  from torch import tensor
  from torch.optim import Adam
  from torch_geometric.loader import DataLoader
  from torch_geometric.loader import DenseDataLoader
label_desc: Use image node_id 5 for calling a global function with example usage: eval_acc(model, loader) and returns: unknown