code: def train_torch_lightning(model, root_dir, batch_size):
      train_loader, val_loader = create_data_loader(
          root_dir, batch_size
      )
      net = Net(model)
      trainer = pl.Trainer(max_epochs=10)
      trainer.fit(net, train_loader)
      trainer.test(net, val_loader)
      print("pass")
  
file_path: BigDL/python/nano/test/pytorch/utils/_train_imagefolder.py
imports: import os
  import torch
  from bigdl.nano.pytorch.vision.datasets import ImageFolder
  from bigdl.nano.pytorch.vision.transforms import transforms
  import pytorch_lightning
  from torch.utils.data import DataLoader
  from bigdl.nano.pytorch.vision.models import ImageClassifier
label_desc: Use image node_id 2 for calling a global function with example usage: train_torch_lightning(model, root_dir, batch_size) without return types