code: def forward(self, x, attn_mask=None):
      new_x, attn = self.attention(x, x, x, attn_mask=attn_mask)
  
      x = x + self.dropout(new_x)
  
      y = x = self.norm1(x)
      y = self.dropout(self.activation(self.conv1(y.transpose(-1, 1))))
      y = self.dropout(self.conv2(y).transpose(-1, 1))
  
      return self.norm2(x + y), attn
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the TransEncoderLayer obj's underlying member method code with example usage: obj.forward(x, attn_mask) and returns: self,  attn