class_docstr: SSD head used in https://arxiv.org/abs/1512.02325.
  
  Args:
      num_classes (int): Number of categories excluding the background
          category.
      in_channels (int): Number of channels in the input feature map.
      anchor_generator (dict): Config dict for anchor generator
      bbox_coder (dict): Config of bounding box coder.
      reg_decoded_bbox (bool): If true, the regression loss would be
          applied on decoded bounding boxes. Default: False
      train_cfg (dict): Training config of anchor head.
      test_cfg (dict): Testing config of anchor head.
docstr: Initialize weights of the head.
docstr_tok: ["Initialize","weights","of","the","head","."]
code: def init_weights(self):
      """Initialize weights of the head."""
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              xavier_init(m, distribution="uniform", bias=0)
  
file_path: insightface/detection/scrfd/mmdet/models/dense_heads/ssd_head.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import xavier_init
  from mmcv.runner import force_fp32
  from mmdet.core import build_anchor_generator, build_assigner, build_bbox_coder, build_sampler, multi_apply
  from ..builder import HEADS
  from ..losses import smooth_l1_loss
  from .anchor_head import AnchorHead
label_desc: Use image node_id 2 for calling the SSDHead obj's underlying member method code with example usage: obj.init_weights() without return types