code: def _initialize_weights(self):
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
              m.weight.data.normal_(0, math.sqrt(2.0 / n))
              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):
              n = m.weight.size(1)
              m.weight.data.normal_(0, 0.01)
              m.bias.data.zero_()
  
file_path: nni/test/ut/sdk/models/pytorch_models/mobilenet.py
imports: import torch.nn
  import math
label_desc: Use image node_id 4 for calling the MobileNet obj's underlying member method code with example usage: obj._initialize_weights() without return types