code: def forward_post(
      self,
      tgt,
      memory,
      memory_mask: Optional[Tensor] = None,
      memory_key_padding_mask: Optional[Tensor] = None,
      pos: Optional[Tensor] = None,
      query_pos: Optional[Tensor] = None,
  ):
      tgt2, avg_attn = self.multihead_attn(
          query=self.with_pos_embed(tgt, query_pos),
          key=self.with_pos_embed(memory, pos),
          value=memory,
          attn_mask=memory_mask,
          key_padding_mask=memory_key_padding_mask,
      )
      tgt = tgt + self.dropout(tgt2)
      tgt = self.norm(tgt)
      return tgt, avg_attn
  
imports: import copy
  import math
  from typing import Optional
  import torch
  import torch.nn.functional
  from torch import Tensor, nn
label_desc: Use image node_id 4 for calling the CrossAttentionLayer obj's underlying member method code with example usage: obj.forward_post(tgt, memory, memory_mask, memory_key_padding_mask, pos, query_pos) and returns: tgt,  avg_attn