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 layers of the transformer head.
docstr_tok: ["Initialize","layers","of","the","transformer","head","."]
code: def _init_layers(self) -> None:
      """Initialize layers of the transformer head."""
      # cls branch
      self.fc_cls = Linear(self.embed_dims, self.cls_out_channels)
      # reg branch
      self.fc_reg = MLP(self.embed_dims, self.embed_dims, 4, 3)
  
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 1 for calling the DABDETRHead obj's underlying member method code with example usage: obj._init_layers() without return types