code: def init_weights(self):
      for m in self.modules():
          if isinstance(m, nn.Conv2d) or isinstance(m, nn.Linear):
              # TODO: compare mode = "fan_in" or "fan_out"
              kaiming_init(m)
      for m in self.modules():
          if isinstance(m, nn.ConvTranspose2d):
              normal_init(m, std=0.001)
      nn.init.constant_(self.deconv2.bias, -np.log(0.99 / 0.01))
  
file_path: insightface/detection/scrfd/mmdet/models/roi_heads/mask_heads/grid_head.py
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import ConvModule, kaiming_init, normal_init
  from mmdet.models.builder import HEADS, build_loss
label_desc: Use image node_id 2 for calling the GridHead obj's underlying member method code with example usage: obj.init_weights() without return types