code: def _epoch(
      model: nn.Module, optim: torch.optim.Optimizer, dl: DataLoader
  ):
      for (x,) in dl:
          optim.zero_grad()
          out = model(x)
          loss = out.sum()
          loss.backward()
          optim.step()
  
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 1 for calling a global function with example usage: _epoch(model, optim, dl) without return types