code: def validate(device, dataset, model, num_classes):
      test_set = dataset.tasks[0].test_set
      test_dataloader = create_dataloader(
          A, [10, 10, 10], test_set, features, device
      )
      acc = evaluate(model, test_dataloader, num_classes)
      return acc
  
imports: import argparse
  from functools import partial
  import dgl.graphbolt
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  import torchmetrics.functional
  from dgl.graphbolt.subgraph_sampler import SubgraphSampler
  from torch.utils.data import functional_datapipe
label_desc: Use image node_id 3 for calling a global function with example usage: validate(device, dataset, model, num_classes) and returns: acc