code: def test(model, graph, mask, label):
      model.eval()
  
      pred = model(graph)[mask].max(1)[1]
      acc = pred.eq(label[mask]).sum().item() / mask.sum().item()
      return acc
  
imports: import numpy
  from tqdm import tqdm
  import pickle
  import torch
  import torch.nn.functional
  from dgl.data import CoraGraphDataset, PubmedGraphDataset, CiteseerGraphDataset
  from dgl.nn.pytorch import GraphConv, GATConv, SAGEConv
  import logging
label_desc: Use image node_id 1 for calling a global function with example usage: test(model, graph, mask, label) and returns: acc