code: def val_dataloader(self):
      return NeighborSampler(
          self.adj_t,
          node_idx=self.val_idx,
          sizes=self.sizes,
          return_e_id=False,
          transform=self.convert_batch,
          batch_size=self.batch_size,
          num_workers=2,
      )
  
imports: import argparse
  import glob
  import os
  import os.path
  import time
  from typing import List, NamedTuple, Optional
  import numpy
  import torch
  import torch.nn.functional
  from ogb.lsc import MAG240MDataset, MAG240MEvaluator
  import pytorch_lightning
  from pytorch_lightning import LightningDataModule, LightningModule, Trainer, seed_everything
  from pytorch_lightning.callbacks import ModelCheckpoint
  from torchmetrics import Accuracy
  from torch import Tensor
  from torch.nn import BatchNorm1d, Dropout, Linear, ModuleList, ReLU, Sequential
  from torch.optim.lr_scheduler import StepLR
  from torch_geometric.data import NeighborSampler
  from torch_geometric.nn import GATConv, SAGEConv
  from torch_sparse import SparseTensor
  from tqdm.auto import tqdm
  from root import ROOT
label_desc: Use image node_id 8 for calling the MAG240M obj's underlying member method code with example usage: obj.val_dataloader() and returns: NeighborSampler