code: def forward(
      self,
      features: Tensor,
      lengths: Optional[Tensor] = None,
  ) -> Tensor:
      x, mask = self._preprocess(features, lengths)
      x = self.transformer(x, attention_mask=mask)
      return x
  
imports: import logging
  from typing import List, Optional, Tuple
  import torch
  from torch import nn, Tensor
  from torch.nn import Module, Parameter
  from .wavlm_attention import WavLMSelfAttention
label_desc: Use image node_id 3 for calling the Encoder obj's underlying member method code with example usage: obj.forward(features, lengths) and returns: x