code: def __init__(
      self,
      decoder_layer,
      num_layers,
      norm=None,
      return_intermediate=False,
  ):
      super(TransformerDecoder, self).__init__()
      self.layers = _get_clones(decoder_layer, num_layers)
      self.num_layers = num_layers
      self.norm = norm
      self.return_intermediate = return_intermediate
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ..layers import MultiHeadAttention, _convert_attention_mask
  from .position_encoding import PositionEmbedding
  from .utils import _get_clones
  from ..initializer import linear_init_, conv_init_, xavier_uniform_, normal_
label_desc: Use image node_id 1 to create a new TransformerDecoder object from inherited base classes: nn with example: obj = TransformerDecoder(decoder_layer, num_layers, norm, return_intermediate)