code: def forward_backward(self) -> None:
      preds = self.forward_only()
      loss = self._criterion(preds, self._labels)
      loss.backward()
      self._module.zero_grad()
  
imports: from enum import Enum
  from typing import Callable, Dict, Optional, Tuple, Type, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from opacus.grad_sample import GradSampleModule
  from opacus.grad_sample.utils import wrap_model
  from opacus.layers import DPGRU, DPLSTM, DPRNN, DPMultiheadAttention
  from opacus.layers.dp_rnn import DPRNNBase
label_desc: Use image node_id 6 for calling the Layer obj's underlying member method code with example usage: obj.forward_backward() without return types