code: def config(self):
      # Add models and param optiom to train option panel
      pytorch_models = [
          os.path.basename(p)
          for p in glob.glob(
              os.path.join(self.bundle_path, "models", "*.pt")
          )
      ]
      pytorch_models.sort(key=len)
  
      config_options = {
          "device": device_list(),  # DEVICE
          "pretrained": True,  # USE EXISTING CHECKPOINT/PRETRAINED MODEL
          "max_epochs": 50,  # TOTAL EPOCHS TO RUN
          "val_split": 0.2,  # VALIDATION SPLIT; -1 TO USE DEFAULT FROM BUNDLE
          "multi_gpu": True,  # USE MULTI-GPU
          "gpus": "all",  # COMMA SEPARATE DEVICE INDEX
          "tracking": ["mlflow", "None"]
          if self.enable_tracking
          and settings.MONAI_LABEL_TRACKING_ENABLED
          else ["None", "mlflow"],
          "tracking_uri": settings.MONAI_LABEL_TRACKING_URI,
          "tracking_experiment_name": "",
          "run_id": "",  # bundle run id, if different from default
          "model_filename": pytorch_models,
      }
  
      for k in self.const.key_displayable_configs():
          if self.bundle_config.get(k):
              config_options.update(self.bundle_config.get_parsed_content(k, instantiate=True))  # type: ignore
  
      return config_options
  
imports: import glob
  import json
  import logging
  import os
  import subprocess
  import sys
  from typing import Dict, Optional, Sequence
  import monai.bundle
  import torch
  from monai.bundle import ConfigParser
  from monai.data import partition_dataset
  from monai.handlers import CheckpointLoader
  from monailabel.config import settings
  from monailabel.interfaces.datastore import Datastore
  from monailabel.interfaces.tasks.train import TrainTask
  from monailabel.utils.others.class_utils import unload_module
  from monailabel.utils.others.generic import device_list, name_to_device
label_desc: Use image node_id 4 for calling the BundleTrainTask obj's underlying member method code with example usage: obj.config() and returns: config_options