code: def validate(device, A, ndata, dataset, model, batch_size):
      inf_id = dataset.test_idx.to(device)
      inf_dataloader = torch.utils.data.DataLoader(
          inf_id, batch_size=batch_size
      )
      acc = evaluate(
          model, A, inf_dataloader, ndata, dataset.num_classes
      )
      return acc
  
imports: import argparse
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  import torchmetrics.functional
  from dgl.data import AsNodePredDataset
  from ogb.nodeproppred import DglNodePropPredDataset
label_desc: Use image node_id 3 for calling a global function with example usage: validate(device, A, ndata, dataset, model, batch_size) and returns: acc