code: def init_weights(self) -> None:
      super(DeformableDETR, self).init_weights()
      """Initialize weights for Transformer and other components."""
      for coder in self.encoder, self.decoder:
          for p in coder.parameters():
              if p.dim() > 1:
                  nn.init.xavier_uniform_(p)
      for m in self.modules():
          if isinstance(m, MultiScaleDeformableAttention):
              m.init_weights()
      nn.init.xavier_uniform_(self.memory_trans_fc.weight)
      normal_(self.level_embed)
  
      if self.method == 1:
          nn.init.xavier_uniform_(self.query_map.weight)
      else:
          nn.init.xavier_uniform_(self.pos_trans_fc.weight)
  
file_path: mmdetection/projects/HDINO/h_dino.py
imports: from typing import Tuple
  import torch
  from torch import Tensor, nn
  from torch.nn.init import normal_
  from mmdet.models.detectors import DINO, DeformableDETR
  from mmdet.models.detectors.deformable_detr import MultiScaleDeformableAttention
  from mmdet.registry import MODELS
  from mmdet.structures import OptSampleList
  from mmdet.utils import OptConfigType
label_desc: Use image node_id 3 for calling the HDINO obj's underlying member method code with example usage: obj.init_weights() without return types