code: def forward(
      self,
      tgt,
      reference_points,
      memory,
      memory_spatial_shapes,
      memory_mask=None,
      query_pos_embed=None,
  ):
      output = tgt
      intermediate = []
      for lid, layer in enumerate(self.layers):
          output = layer(
              output,
              reference_points,
              memory,
              memory_spatial_shapes,
              memory_mask,
              query_pos_embed,
          )
  
          if self.return_intermediate:
              intermediate.append(output)
  
      if self.return_intermediate:
          return paddle.stack(intermediate)
  
      return output.unsqueeze(0)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from ppdet.core.workspace import register
  from ..layers import MultiHeadAttention, _convert_attention_mask
  from .utils import _get_clones
  from ..initializer import linear_init_, normal_, constant_, xavier_uniform_
label_desc: Use image node_id 2 for calling the PETR_DeformableTransformerDecoder obj's underlying member method code with example usage: obj.forward(tgt, reference_points, memory, memory_spatial_shapes, memory_mask, query_pos_embed) and returns: output, paddle