code: def save_checkpoint(state, is_best, filename="checkpoint.tar"):
      torch.save(state, filename)
      if is_best:
          shutil.copyfile(filename, "model_best.pth.tar")
  
imports: import argparse
  import logging
  import os
  import shutil
  import sys
  from datetime import datetime, timedelta
  import numpy
  import torch
  import torch.nn
  import torch.optim
  import torch.utils.data
  import torch.utils.data.distributed
  import torchvision.transforms
  from opacus import PrivacyEngine
  from opacus.distributed import DifferentiallyPrivateDistributedDataParallel
  from opacus.grad_sample.functorch import make_functional
  from torch.func import grad, grad_and_value, vmap
  from torch.nn.parallel import DistributedDataParallel
  from torchvision.datasets import CIFAR10
  from tqdm import tqdm
label_desc: Use image node_id 4 for calling a global function with example usage: save_checkpoint(state, is_best, filename) without return types