code: def setUp(self):
      n_data, dim = 100, 10
      data = torch.randn(n_data, dim)
      model = nn.Linear(10, 10)
      optimizer = optim.SGD(model.parameters(), lr=0.1)
      data_loader = DataLoader(TensorDataset(data), batch_size=10)
      self.engine = PrivacyEngine()
  
      (
          self.module,
          self.optimizer,
          self.data_loader,
      ) = self.engine.make_private(
          module=model,
          optimizer=optimizer,
          data_loader=data_loader,
          noise_multiplier=1.0,
          max_grad_norm=1.0,
      )
  
file_path: opacus/opacus/tests/schedulers/grad_clip_scheduler_test.py
imports: import unittest
  import torch
  from opacus import PrivacyEngine
  from opacus.schedulers import ExponentialGradClip, LambdaGradClip, StepGradClip
  from torch import nn, optim
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 1 for calling the GradClipSchedulerTest obj's underlying member method code with example usage: obj.setUp() without return types