class_docstr: Implements the decoder in DETR transformer.
  
  Args:
      return_intermediate (bool): Whether to return intermediate outputs.
      coder_norm_cfg (dict): Config of last normalization layer. Default：
          `LN`.
class_docstr_tok: ["Implements","the","decoder","in","DETR","transformer",".","Args",":","return_intermediate","(","bool",")",":","Whether","to","return","intermediate","outputs",".","coder_norm_cfg","(","dict",")",":","Config","of","last","normalization","layer",".","Default\uff1a","`","LN","`","."]
code: def __init__(self, *args, return_intermediate=False, **kwargs):
      super(DeformableDetrTransformerDecoder, self).__init__(
          *args, **kwargs
      )
      self.return_intermediate = return_intermediate
  
imports: import math
  import warnings
  import torch
  import torch.nn
  from mmcv.cnn import build_norm_layer
  from mmcv.cnn.bricks.transformer import BaseTransformerLayer, TransformerLayerSequence, build_transformer_layer_sequence
  from mmcv.ops import MultiScaleDeformableAttention
  from mmengine.model import BaseModule
  from mmengine.model.weight_init import xavier_init
  from torch.nn.init import normal_
  from mmdet.models.layers.transformer import inverse_sigmoid
  from mmdet.registry import MODELS
label_desc: Use image node_id 1 to create a new DeformableDetrTransformerDecoder object from inherited base classes: TransformerLayerSequence with example: obj = DeformableDetrTransformerDecoder()