code: def train_handlers(self, context: Context):
      handlers = super().train_handlers(context)
      if self.debug_mode and context.local_rank == 0:
          handlers.append(
              TensorBoardImageHandler(log_dir=context.events_dir)
          )
      return handlers
  
imports: import logging
  import torch
  from lib.transforms.transforms import NormalizeLabelsInDatasetd
  from monai.apps.deepedit.interaction import Interaction
  from monai.apps.deepedit.transforms import AddGuidanceSignalDeepEditd, AddInitialSeedPointMissingLabelsd, AddRandomGuidanceDeepEditd, FindAllValidSlicesMissingLabelsd, FindDiscrepancyRegionsDeepEditd, SplitPredsLabeld
  from monai.handlers import MeanDice, from_engine
  from monai.inferers import SimpleInferer
  from monai.losses import DiceCELoss
  from monai.transforms import Activationsd, AsDiscreted, EnsureChannelFirstd, LoadImaged, Orientationd, RandFlipd, RandRotate90d, RandShiftIntensityd, Resized, ScaleIntensityRanged, SelectItemsd, ToNumpyd, ToTensord
  from monailabel.deepedit.handlers import TensorBoardImageHandler
  from monailabel.tasks.train.basic_train import BasicTrainTask, Context
label_desc: Use image node_id 14 for calling the DeepEdit obj's underlying member method code with example usage: obj.train_handlers(context) and returns: handlers