code: def attn_train_fn(
      model: nn.Module,
      *args,
      **kwargs,
  ):
      model.train()
      criterion = nn.MSELoss()
      logits, attn_weights = model(*args, **kwargs)
      y = torch.zeros_like(logits)
      loss = criterion(logits, y)
      loss.backward()
  
file_path: opacus/opacus/tests/dp_layers/dp_multihead_attention_test.py
imports: from typing import Optional
  import hypothesis.strategies
  import torch
  import torch.nn
  from hypothesis import given, settings
  from opacus.layers import DPMultiheadAttention
  from .common import DPModules_test
label_desc: Use image node_id 2 for calling a global function with example usage: attn_train_fn(model) without return types