code: def _initialize_weights(self):
      # weight initialization
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              nn.init.kaiming_normal_(m.weight, mode="fan_out")
              if m.bias is not None:
                  nn.init.zeros_(m.bias)
          elif isinstance(m, nn.BatchNorm2d):
              nn.init.ones_(m.weight)
              nn.init.zeros_(m.bias)
          elif isinstance(m, nn.Linear):
              nn.init.normal_(m.weight, 0, 0.01)
              if m.bias is not None:
                  nn.init.zeros_(m.bias)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the MobileNetV3 obj's underlying member method code with example usage: obj._initialize_weights() without return types