code: def forward(
      self,
      tgt,
      memory,
      tgt_mask: Optional[Tensor] = None,
      memory_mask: Optional[Tensor] = None,
      tgt_key_padding_mask: Optional[Tensor] = None,
      memory_key_padding_mask: Optional[Tensor] = None,
      pos: Optional[Tensor] = None,
      query_pos: Optional[Tensor] = None,
  ):
      if self.normalize_before:
          return self.forward_pre(
              tgt,
              memory,
              tgt_mask,
              memory_mask,
              tgt_key_padding_mask,
              memory_key_padding_mask,
              pos,
              query_pos,
          )
      return self.forward_post(
          tgt,
          memory,
          tgt_mask,
          memory_mask,
          tgt_key_padding_mask,
          memory_key_padding_mask,
          pos,
          query_pos,
      )
  
imports: import copy
  from typing import Optional, List
  import torch
  import torch.nn.functional
  from torch import nn, Tensor
label_desc: Use image node_id 5 for calling the TransformerDecoderLayer obj's underlying member method code with example usage: obj.forward(tgt, memory, tgt_mask, memory_mask, tgt_key_padding_mask, memory_key_padding_mask, pos, query_pos) and returns: self, self