code: def forward(
      self,
      tgt,
      ref_points_unact,
      memory,
      memory_spatial_shapes,
      memory_level_start_index,
      bbox_head,
      query_pos_head,
      dec_norm,
      valid_ratios=None,
      attn_mask=None,
      memory_mask=None,
  ):
      if valid_ratios is None:
          valid_ratios = paddle.ones(
              [memory.shape[0], memory_spatial_shapes.shape[0], 2]
          )
  
      output = tgt
      intermediate = []
      inter_bboxes = []
      ref_points = F.sigmoid(ref_points_unact)
      for i, layer in enumerate(self.layers):
          reference_points_input = ref_points.detach().unsqueeze(
              2
          ) * valid_ratios.tile([1, 1, 2]).unsqueeze(1)
          query_pos_embed = get_sine_pos_embed(
              reference_points_input[..., 0, :], self.hidden_dim // 2
          )
          query_pos_embed = query_pos_head(query_pos_embed)
  
          output = layer(
              output,
              reference_points_input,
              memory,
              memory_spatial_shapes,
              memory_level_start_index,
              attn_mask,
              memory_mask,
              query_pos_embed,
          )
  
          ref_points = F.sigmoid(
              bbox_head(output) + inverse_sigmoid(ref_points.detach())
          )
  
          intermediate.append(dec_norm(output))
          inter_bboxes.append(ref_points)
  
      return paddle.stack(intermediate), paddle.stack(inter_bboxes)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from ppdet.core.workspace import register
  from .position_encoding import PositionEmbedding
  from ..heads.detr_head import MLP
  from .deformable_transformer import DeformableTransformerEncoderLayer, DeformableTransformerEncoder
  from .dino_transformer import DINOTransformerDecoderLayer
  from ..initializer import linear_init_, constant_, xavier_uniform_, bias_init_with_prob
  from .utils import _get_clones, get_valid_ratio, get_denoising_training_group, get_sine_pos_embed, inverse_sigmoid, mask_to_box_coordinate
label_desc: Use image node_id 2 for calling the MaskDINOTransformerDecoder obj's underlying member method code with example usage: obj.forward(tgt, ref_points_unact, memory, memory_spatial_shapes, memory_level_start_index, bbox_head, query_pos_head, dec_norm, valid_ratios, attn_mask, memory_mask) and returns: paddle,  paddle