code: def val_loader_creator(config, batch_size):
      val_transform = A.Compose(
          [
              A.Resize(width=128, height=128, p=1.0),
              A.HorizontalFlip(p=0.5),
          ]
      )
  
      val_ds = BrainDataset(config["val"], val_transform)
      val_loader = torch.utils.data.DataLoader(
          val_ds, batch_size=batch_size, shuffle=False, num_workers=0
      )
      return val_loader
  
imports: from __future__ import print_function
  from sklearn.model_selection import train_test_split
  import matplotlib.pyplot
  import albumentations
  import pandas
  import argparse
  import glob
  import os
  import torch
  import torch.nn
  import torch.optim
  import torch.utils.data
  from torchvision.utils import make_grid
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.learn.pytorch import Estimator
  from Unet import UNet
  from dataset import *
label_desc: Use image node_id 8 for calling a global function with example usage: val_loader_creator(config, batch_size) and returns: val_loader