code: def build_decoder_layer(
      self,
      d_model_dec=512,
      nhead=8,
      num_decoder_layers=6,
      dim_feedforward=2048,
      dropout=0.1,
      activation="relu",
      normalize_before=False,
      return_intermediate_dec=False,
  ):
      decoder_layer = TransformerDecoderLayer(
          d_model_dec,
          nhead,
          dim_feedforward,
          dropout,
          activation,
          normalize_before,
      )
      decoder_norm = nn.LayerNorm(d_model_dec)
      return TransformerDecoder(
          decoder_layer,
          num_decoder_layers,
          decoder_norm,
          return_intermediate=return_intermediate_dec,
      )
  
imports: import copy
  from typing import Optional
  import torch
  import torch.nn.functional
  from torch import nn, Tensor
label_desc: Use image node_id 2 for calling the UniTTransformer obj's underlying member method code with example usage: obj.build_decoder_layer(d_model_dec, nhead, num_decoder_layers, dim_feedforward, dropout, activation, normalize_before, return_intermediate_dec) and returns: TransformerDecoder