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_transform=from_engine(["image", "label"]),
                  output_transform=from_engine(["pred"]),
                  interval=20,
                  epoch_level=True,
              )
          )
      return handlers
  
imports: import logging
  import torch
  from lib.transforms.transforms import NormalizeLabelsInDatasetd
  from monai.handlers import TensorBoardImageHandler, from_engine
  from monai.inferers import SlidingWindowInferer
  from monai.losses import DiceCELoss
  from monai.transforms import Activationsd, AsDiscreted, EnsureChannelFirstd, EnsureTyped, GaussianSmoothd, LoadImaged, RandSpatialCropd, ScaleIntensityd, ScaleIntensityRanged, SelectItemsd, Spacingd
  from monailabel.tasks.train.basic_train import BasicTrainTask, Context
  from monailabel.tasks.train.utils import region_wise_metrics
label_desc: Use image node_id 14 for calling the LocalizationSpine obj's underlying member method code with example usage: obj.train_handlers(context) and returns: handlers