code: def _init_dp_training(
      self,
      secure_mode: bool,
      dl_seed: Optional[int] = None,
      noise_seed: Optional[int] = None,
      noise: float = 1.0,
      poisson_sampling: bool = True,
  ):
      dl_generator = _init_generator(dl_seed)
      noise_generator = _init_generator(noise_seed)
  
      model, optim, dl = self._init_training(dl_generator=dl_generator)
      privacy_engine = PrivacyEngine(secure_mode=secure_mode)
  
      return privacy_engine.make_private(
          module=model,
          optimizer=optim,
          data_loader=dl,
          noise_multiplier=noise,
          max_grad_norm=1.0,
          noise_generator=noise_generator,
          poisson_sampling=poisson_sampling,
      )
  
imports: import unittest
  from typing import Optional
  import torch
  import torch.nn
  from opacus import PrivacyEngine
  from opacus.data_loader import DPDataLoader, switch_generator
  from opacus.grad_sample import GradSampleModule
  from opacus.optimizers import DPOptimizer
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 3 for calling the PrivacyEngineSecureModeTest obj's underlying member method code with example usage: obj._init_dp_training(secure_mode, dl_seed, noise_seed, noise, poisson_sampling) and returns: privacy_engine