code: def init_weights(self):
      for m in [self.upsample, self.conv_logits]:
          if m is None:
              continue
          elif isinstance(m, CARAFEPack):
              m.init_weights()
          else:
              nn.init.kaiming_normal_(
                  m.weight, mode="fan_out", nonlinearity="relu"
              )
              nn.init.constant_(m.bias, 0)
  
file_path: insightface/detection/scrfd/mmdet/models/roi_heads/mask_heads/fcn_mask_head.py
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import Conv2d, ConvModule, build_upsample_layer
  from mmcv.ops.carafe import CARAFEPack
  from mmcv.runner import auto_fp16, force_fp32
  from torch.nn.modules.utils import _pair
  from mmdet.core import mask_target
  from mmdet.models.builder import HEADS, build_loss
label_desc: Use image node_id 2 for calling the FCNMaskHead obj's underlying member method code with example usage: obj.init_weights() without return types