code: def __init__(
      self,
      path: str,
      conf: Dict[str, str],
      const: Optional[BundleConstants] = None,
      enable_tracking=False,
      model_dict_key="model",
      load_strict=False,
  ):
      self.valid: bool = False
      self.conf = conf
      self.const = const if const else BundleConstants()
      self.enable_tracking = enable_tracking
      self.model_dict_key = model_dict_key
      self.load_strict = load_strict
  
      config_paths = [
          c
          for c in self.const.configs()
          if os.path.exists(os.path.join(path, "configs", c))
      ]
      if not config_paths:
          logger.warning(
              f"Ignore {path} as there is no train config {self.const.configs()} exists"
          )
          return
  
      self.bundle_path = path
      self.bundle_config_path = os.path.join(
          path, "configs", config_paths[0]
      )
      self.bundle_config = self._load_bundle_config(
          self.bundle_path, self.bundle_config_path
      )
  
      # https://docs.monai.io/en/latest/mb_specification.html#metadata-json-file
      self.bundle_metadata_path = os.path.join(
          path, "configs", "metadata.json"
      )
      with open(
          os.path.join(path, "configs", self.const.metadata_json())
      ) as fp:
          metadata = json.load(fp)
  
      super().__init__(metadata.get("description", ""))
      self.valid = True
      self.version = metadata.get("version")
  
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 1 to create a new BundleTrainTask object from inherited base classes: TrainTask with example: obj = BundleTrainTask(path, conf, const, enable_tracking, model_dict_key, load_strict)