class_docstr: Detection Head of RTMDet-Ins with sep-bn layers.
  
  Args:
      num_classes (int): Number of categories excluding the background
          category.
      in_channels (int): Number of channels in the input feature map.
      share_conv (bool): Whether to share conv layers between stages.
          Defaults to True.
      norm_cfg (:obj:`ConfigDict` or dict)): Config dict for normalization
          layer. Defaults to dict(type='BN').
      act_cfg (:obj:`ConfigDict` or dict)): Config dict for activation layer.
          Defaults to dict(type='SiLU', inplace=True).
      pred_kernel_size (int): Kernel size of prediction layer. Defaults to 1.
docstr: Initialize weights of the head.
code: def init_weights(self) -> None:
      """Initialize weights of the head."""
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              normal_init(m, mean=0, std=0.01)
          if is_norm(m):
              constant_init(m, 1)
      bias_cls = bias_init_with_prob(0.01)
      for rtm_cls, rtm_reg, rtm_kernel in zip(
          self.rtm_cls, self.rtm_reg, self.rtm_kernel
      ):
          normal_init(rtm_cls, std=0.01, bias=bias_cls)
          normal_init(rtm_reg, std=0.01, bias=1)
      if self.with_objectness:
          for rtm_obj in self.rtm_obj:
              normal_init(rtm_obj, std=0.01, bias=bias_cls)
  
imports: import copy
  import math
  from typing import List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import ConvModule, is_norm
  from mmcv.ops import batched_nms
  from mmengine.model import BaseModule, bias_init_with_prob, constant_init, normal_init
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.models.layers.transformer import inverse_sigmoid
  from mmdet.models.utils import filter_scores_and_topk, multi_apply, select_single_mlvl, sigmoid_geometric_mean
  from mmdet.registry import MODELS
  from mmdet.structures.bbox import cat_boxes, distance2bbox, get_box_tensor, get_box_wh, scale_boxes
  from mmdet.utils import ConfigType, InstanceList, OptInstanceList, reduce_mean
  from .rtmdet_head import RTMDetHead
label_desc: Use image node_id 3 for calling the RTMDetInsSepBNHead obj's underlying member method code with example usage: obj.init_weights() without return types