code: def _initialize_weights(self):
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              nn.init.kaiming_normal_(
                  m.weight, mode="fan_out", nonlinearity="relu"
              )
              if m.bias is not None:
                  m.bias.data.zero_()
          elif isinstance(m, nn.BatchNorm2d):
              m.weight.data.fill_(1)
              m.bias.data.zero_()
          elif isinstance(m, nn.Linear):
              nn.init.kaiming_normal_(
                  m.weight, mode="fan_out", nonlinearity="relu"
              )
              if m.bias is not None:
                  m.bias.data.zero_()
  
imports: import torch.nn
  from torch.nn import Linear, Conv2d, BatchNorm1d, BatchNorm2d, PReLU, Sequential, Module
  import torch
label_desc: Use image node_id 2 for calling the MobileFaceNet obj's underlying member method code with example usage: obj._initialize_weights() without return types