class_docstr: Head of DAB-DETR. DAB-DETR: Dynamic Anchor Boxes are Better Queries for
  DETR.
  
  More details can be found in the `paper
  <https://arxiv.org/abs/2201.12329>`_ .
docstr: initialize weights.
docstr_tok: ["initialize","weights","."]
code: def init_weights(self) -> None:
      """initialize weights."""
      if self.loss_cls.use_sigmoid:
          bias_init = bias_init_with_prob(0.01)
          nn.init.constant_(self.fc_cls.bias, bias_init)
      constant_init(self.fc_reg.layers[-1], 0.0, bias=0.0)
  
file_path: mmdetection/mmdet/models/dense_heads/dab_detr_head.py
imports: from typing import Tuple
  import torch.nn
  from mmcv.cnn import Linear
  from mmengine.model import bias_init_with_prob, constant_init
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures import SampleList
  from mmdet.utils import InstanceList
  from ..layers import MLP, inverse_sigmoid
  from .conditional_detr_head import ConditionalDETRHead
label_desc: Use image node_id 2 for calling the DABDETRHead obj's underlying member method code with example usage: obj.init_weights() without return types