code: def __init__(self, config):
      super(TransformerAttention, self).__init__()
  
      # self.xxx = config.xxx
      self.hidden_size = config.hidden_size
      self.num_heads = config.num_heads
      self.dropout = config.dropout
      self.output_attentions = config.output_attentions
      self.layer_norm_eps = config.layer_norm_eps
  
      self.multihead_attention = MultiHeadAttention(
          self.hidden_size,
          self.num_heads,
          self.dropout,
          self.output_attentions,
      )
      self.dense = nn.Linear(self.hidden_size, self.hidden_size)
      self.dropout = nn.Dropout(self.dropout)
      self.layerNorm = nn.LayerNorm(
          self.hidden_size, eps=self.layer_norm_eps
      )
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from .Attention import MultiHeadAttention
label_desc: Use image node_id 1 to create a new TransformerAttention object from inherited base classes: nn with example: obj = TransformerAttention(config)