code: def init_weights(self):
      for m in self.modules():
          if isinstance(m, nn.Linear):
              nn.init.normal_(m.weight, 0, 0.01)
              nn.init.constant_(m.bias, 0)
          if isinstance(m, nn.Conv3d):
              pass
          if isinstance(m, nn.BatchNorm3d):
              m.weight.data.fill_(1)
              m.bias.data.fill_(0)
  
imports: import numpy
  import torch
  import torch.nn
  import torch.utils.checkpoint
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the AuxHead obj's underlying member method code with example usage: obj.init_weights() without return types