code: def init(
      self,
      name: str,
      model_dir: str,
      conf: Dict[str, str],
      planner: Any,
      **kwargs,
  ):
      super().init(name, model_dir, conf, planner, **kwargs)
  
      # Labels
      self.labels = [
          "spleen",
          "right kidney",
          "left kidney",
          "liver",
          "stomach",
          "aorta",
          "inferior vena cava",
      ]
  
      # Model Files
      self.path = [
          os.path.join(
              self.model_dir, f"pretrained_{name}.pt"
          ),  # pretrained
          os.path.join(self.model_dir, f"{name}.pt"),  # published
      ]
  
      # Download PreTrained Model
      if strtobool(self.conf.get("use_pretrained_model", "true")):
          url = f"{self.conf.get('pretrained_path', self.PRE_TRAINED_PATH)}"
          url = f"{url}/radiology_deepgrow_3d_bunet.pt"
          download_file(url, self.path[0])
  
      # Network
      self.network = BasicUNet(
          spatial_dims=3,
          in_channels=3,
          out_channels=1,
          features=(32, 64, 128, 256, 512, 32),
      )
  
file_path: MONAILabel/sample-apps/radiology/lib/configs/deepgrow_3d.py
imports: import logging
  import os
  from typing import Any, Dict, Optional, Union
  import lib.infers
  import lib.trainers
  from monai.networks.nets import BasicUNet
  from monailabel.interfaces.config import TaskConfig
  from monailabel.interfaces.tasks.infer_v2 import InferTask
  from monailabel.interfaces.tasks.train import TrainTask
  from monailabel.utils.others.generic import download_file, strtobool
label_desc: Use image node_id 1 for calling the Deepgrow3D obj's underlying member method code with example usage: obj.init(name, model_dir, conf, planner) without return types