code: def _initialize_weights(self, m):
      classname = m.__class__.__name__
      if classname.find("Conv") != -1:
          nn.init.kaiming_normal_(m.weight.data)
      elif classname.find("BatchNorm") != -1:
          m.weight.data.fill_(1.0)
          m.bias.data.fill_(1e-4)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the ScaleFeatureSelection obj's underlying member method code with example usage: obj._initialize_weights(m) without return types