code: def val_additional_metrics(self, context: Context):
      return {
          "val_acc": Accuracy(
              output_transform=from_engine(["pred", "label"])
          )
      }
  
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 10 for calling the SegmentationNuclei obj's underlying member method code with example usage: obj.val_additional_metrics(context) and returns: dict