code: def _preprocess(self, x: Tensor):
      x = x + self.pos_conv_embed(x)
  
      if self.layer_norm_first:
          x = self.layer_norm(x)
  
      x = self.dropout(x)
      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 2 for calling the Transformer obj's underlying member method code with example usage: obj._preprocess(x) and returns: x