code: def _get_pred_class_and_mask(self, query_embed, mask_feat):
      out_query = self.dec_norm(query_embed)
      out_logits = self.class_head(out_query)
      mask_query_embed = self.mask_query_head(out_query)
      _, _, h, w = paddle.shape(mask_feat)
      # [b, q, c] x [b, c, h, w] -> [b, q, h, w]
      out_mask = paddle.bmm(
          mask_query_embed, mask_feat.flatten(2)
      ).reshape([0, 0, h, w])
      return out_logits, out_mask
  
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 10 for calling the MaskDINO obj's underlying member method code with example usage: obj._get_pred_class_and_mask(query_embed, mask_feat) and returns: out_logits,  out_mask