code: def train_handlers(self, context: Context):
      handlers = super().train_handlers(context)
      if context.local_rank == 0:
          handlers.append(
              TensorBoardImageHandler(
                  log_dir=context.events_dir,
                  batch_limit=4,
                  tag_name="train",
              )
          )
      return handlers
  
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 12 for calling the SegmentationNuclei obj's underlying member method code with example usage: obj.train_handlers(context) and returns: handlers