code: def val_pre_transforms(self, context: Context):
      return [
          LoadImaged(keys=("image", "label"), dtype=np.uint8),
          EnsureTyped(keys=("image", "label")),
          EnsureChannelFirstd(keys=("image", "label")),
          ScaleIntensityRangeD(
              keys="image",
              a_min=0.0,
              a_max=255.0,
              b_min=-1.0,
              b_max=1.0,
          ),
      ]
  
imports: import logging
  import os
  import numpy
  import torch
  from ignite.metrics import Accuracy
  from lib.handlers import TensorBoardImageHandler
  from lib.utils import split_dataset
  from monai.handlers import from_engine
  from monai.inferers import SimpleInferer
  from monai.losses import DiceCELoss
  from monai.transforms import Activationsd, AsDiscreted, EnsureChannelFirstd, EnsureTyped, LoadImaged, RandFlipd, RandRotate90d, RandTorchVisiond, ScaleIntensityRangeD, ScaleIntensityRanged
  from monailabel.interfaces.datastore import Datastore
  from monailabel.tasks.train.basic_train import BasicTrainTask, Context
label_desc: Use image node_id 8 for calling the SegmentationNuclei obj's underlying member method code with example usage: obj.val_pre_transforms(context) and returns: list