code: def nondefault_trainer_args(opt):
      parser = argparse.ArgumentParser()
      parser = Trainer.add_argparse_args(parser)
      args = parser.parse_args([])
      return sorted(
          k for k in vars(args) if getattr(opt, k) != getattr(args, k)
      )
  
imports: import argparse, os, sys, datetime, glob, importlib, csv
  import numpy
  import time
  import torch
  import torchvision
  import pytorch_lightning
  from packaging import version
  from omegaconf import OmegaConf
  from torch.utils.data import random_split, DataLoader, Dataset, Subset
  from functools import partial
  from PIL import Image
  from pytorch_lightning import seed_everything
  from pytorch_lightning.trainer import Trainer
  from pytorch_lightning.callbacks import ModelCheckpoint, Callback, LearningRateMonitor
  from pytorch_lightning.utilities.distributed import rank_zero_only
  from pytorch_lightning.utilities import rank_zero_info
  from ldm.data.base import Txt2ImgIterableBaseDataset
  from ldm.util import instantiate_from_config
label_desc: Use image node_id 2 for calling a global function with example usage: nondefault_trainer_args(opt) and returns: sorted