code: def __init__(
      self, max_epochs: int, backbone: str, cloud_compute: CloudCompute
  ):
      # parallel is set to True to run asynchronously
      super().__init__(parallel=True, cloud_compute=cloud_compute)
      # Number of epochs to run
      self.max_epochs = max_epochs
      # The model backbone to train on
      self.backbone = backbone
      self.best_model_path = None
      self.best_model_score = None
  
file_path: pytorch-lightning/docs/source-app/code_samples/quickstart/app/app_1.py
imports: import flash
  from flash.core.data.utils import download_data
  from flash.image import ImageClassificationData, ImageClassifier
  from lightning.app import LightningWork, LightningFlow, LightningApp, CloudCompute
  from lightning.pytorch.callbacks import ModelCheckpoint
label_desc: Use image node_id 1 to create a new ImageClassifierTrainWork object from inherited base classes: LightningWork with example: obj = ImageClassifierTrainWork(max_epochs, backbone, cloud_compute)