code: def debug(
      rank,
      world_size,
      tensor,
      dp,
      noise_multiplier=0,
      max_grad_norm=1e8,
  ):
      local_rank = setup_and_get_device(rank, world_size)
      print(
          f"Rank: {rank},World size: {world_size}, local_rank: {local_rank}"
      )
      tensor = tensor.to(local_rank)
      print(f"dp: {dp}")
      print(tensor)
  
      cleanup()
  
imports: import os
  import sys
  import unittest
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.nn
  import torch.optim
  from opacus import PrivacyEngine
  from opacus.distributed import DifferentiallyPrivateDistributedDataParallel
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 6 for calling a global function with example usage: debug(rank, world_size, tensor, dp, noise_multiplier, max_grad_norm) without return types