code: def _init_private_training():
      model = MyCustomModel()
      optimizer = torch.optim.SGD(model.parameters(), lr=0.05)
      data_loader = create_demo_dataloader()
      privacy_engine = PrivacyEngine()
  
      model, optimizer, data_loader = privacy_engine.make_private(
          module=model,
          optimizer=optimizer,
          data_loader=data_loader,
          noise_multiplier=1.0,
          max_grad_norm=1.0,
      )
  
      return model, optimizer, data_loader
  
file_path: opacus/conftest.py
imports: import pytest
  import torch
  from opacus import PrivacyEngine
  from torch import nn
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 2 for calling a global function with example usage: _init_private_training() and returns: model,  optimizer,  data_loader