code: def forward_pre(
      self,
      src,
      src_mask: Optional[Tensor] = None,
      src_key_padding_mask: Optional[Tensor] = None,
      pos: Optional[Tensor] = None,
  ):
      src2 = self.norm1(src)
      q = k = self.with_pos_embed(src2, pos)
      src2 = self.self_attn(
          q,
          k,
          value=src2,
          attn_mask=src_mask,
          key_padding_mask=src_key_padding_mask,
      )[0]
      src = src + self.dropout1(src2)
      src2 = self.norm2(src)
      src2 = self.linear2(
          self.dropout(self.activation(self.linear1(src2)))
      )
      src = src + self.dropout2(src2)
      return src
  
imports: import copy
  from typing import Optional
  import torch
  import torch.nn.functional
  from torch import nn, Tensor
label_desc: Use image node_id 4 for calling the TransformerEncoderLayer obj's underlying member method code with example usage: obj.forward_pre(src, src_mask, src_key_padding_mask, pos) and returns: src