code: def test(loader):
      model.eval()
  
      correct = 0
      for data in loader:
          data = data.to(device)
          pred = model(data.x, data.pos, data.batch).max(dim=1)[1]
          correct += pred.eq(data.y).sum().item()
      return correct / len(loader.dataset)
  
imports: import os.path
  import torch
  import torch.nn.functional
  from torch.nn import Linear
  import torch_geometric.transforms
  from torch_geometric.datasets import ModelNet
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import MLP, PointTransformerConv, fps, global_mean_pool, knn, knn_graph
  from torch_geometric.typing import WITH_TORCH_CLUSTER
  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: unknown