code: def __init__(
      self,
      pos_conv_embed: Module,
      dropout: float,
      layers: Module,
      layer_norm_first: bool,
      layer_drop: float,
  ):
      super().__init__()
      self.pos_conv_embed = pos_conv_embed
      self.layer_norm = nn.LayerNorm(pos_conv_embed.embed_dim)
      self.layer_norm_first = layer_norm_first
      self.layer_drop = layer_drop
      self.dropout = nn.Dropout(dropout)
      self.layers = layers
  
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 1 to create a new Transformer object from inherited base classes: Module with example: obj = Transformer(pos_conv_embed, dropout, layers, layer_norm_first, layer_drop)