code: def _init_weights(self):
      for m in self.mask_convs.modules():
          if isinstance(m, nn.Conv2d):
              kaiming_init(m)
      kaiming_init(self.projection)
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from mmengine.model.weight_init import caffe2_xavier_init, kaiming_init
  from torch.nn import init
  from mmdet.registry import MODELS
label_desc: Use image node_id 2 for calling the MaskBranch obj's underlying member method code with example usage: obj._init_weights() without return types