code: def test_gradient_noclip_zeronoise(self) -> None:
      # Tests that gradient is the same with DP or with DDP
      weight_dp, weight_nodp = torch.zeros(10, 10), torch.zeros(10, 10)
  
      run_function(demo_basic, weight_dp, dp=True)
      run_function(demo_basic, weight_nodp, dp=False)
  
      self.assertTrue(torch.norm(weight_dp - weight_nodp) < 1e-7)
  
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 2 for calling the GradientComputationTest obj's underlying member method code with example usage: obj.test_gradient_noclip_zeronoise() without return types