class_docstr: Conformer Encoder class, consisting of feature projection and conformer modules.
  
  Args:
      feature_projection (nn.Module):
          Projects feature to encoder dimension.
      conformer (nn.ModuleList)
          List of Conformer layers.
code: def _preprocess(
      self,
      features: Tensor,
      lengths: Optional[Tensor] = None,
  ) -> Tuple[Tensor, Optional[Tensor]]:
      x = self.feature_projection(features)
      if lengths is not None:
          mask = components._get_padding_mask(x, lengths)
      else:
          mask = None
      return x, mask
  
imports: from typing import List, Optional, Tuple, Union
  import torch
  from torch import nn, Tensor
  from torch.nn import Module, ModuleList
  from torchaudio.models import Wav2Vec2Model
  from torchaudio.models.conformer import ConformerLayer
  from torchaudio.models.rnnt import _TimeReduction
  from torchaudio.models.wav2vec2 import components
label_desc: Use image node_id 2 for calling the ConformerEncoder obj's underlying member method code with example usage: obj._preprocess(features, lengths) and returns: x,  mask