code: def norm_labels(self):
      # This should be applied along with NormalizeLabelsInDatasetd transform
      new_label_nums = {}
      for idx, (key_label, val_label) in enumerate(
          self._labels.items(), start=1
      ):
          if key_label != "background":
              new_label_nums[key_label] = idx
          if key_label == "background":
              new_label_nums["background"] = 0
      return new_label_nums
  
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 11 for calling the LocalizationSpine obj's underlying member method code with example usage: obj.norm_labels() and returns: new_label_nums