code: def _init_weights(self, module):
      if isinstance(module, (nn.Linear, nn.Embedding)):
          module.weight.data.normal_(mean=0.0, std=0.02)
          if isinstance(module, nn.Linear) and module.bias is not None:
              module.bias.data.zero_()
      elif isinstance(module, nn.LayerNorm):
          module.bias.data.zero_()
          module.weight.data.fill_(1.0)
  
imports: import math
  import torch
  from torch import nn, Tensor
  import torch.nn.functional
  from typing import Optional
  from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock
  from basicsr.utils.registry import ARCH_REGISTRY
label_desc: Use image node_id 2 for calling the CodeFormer obj's underlying member method code with example usage: obj._init_weights(module) without return types