code: def init_trainers(self) -> Dict[str, TrainTask]:
      trainers: Dict[str, TrainTask] = {}
      if strtobool(self.conf.get("skip_trainers", "false")):
          return trainers
  
      for n, b in self.models.items():
          t = BundleTrainTask(b, self.conf)
          if not t or not t.is_valid():
              continue
  
          logger.info(f"+++ Adding Trainer:: {n} => {t}")
          trainers[n] = t
      return trainers
  
imports: import logging
  import os
  from typing import Dict
  from monai.transforms import Invertd, SaveImaged
  import monailabel
  from monailabel.interfaces.app import MONAILabelApp
  from monailabel.interfaces.tasks.infer_v2 import InferTask
  from monailabel.interfaces.tasks.scoring import ScoringMethod
  from monailabel.interfaces.tasks.strategy import Strategy
  from monailabel.interfaces.tasks.train import TrainTask
  from monailabel.tasks.activelearning.first import First
  from monailabel.tasks.activelearning.random import Random
  from monailabel.tasks.infer.bundle import BundleInferTask
  from monailabel.tasks.scoring.epistemic_v2 import EpistemicScoring
  from monailabel.tasks.train.bundle import BundleTrainTask
  from monailabel.utils.others.generic import get_bundle_models, strtobool
label_desc: Use image node_id 3 for calling the MyApp obj's underlying member method code with example usage: obj.init_trainers() and returns: trainers, trainers