code: def initialize_weights(*models):
      for model in models:
          for module in model.modules():
              if isinstance(module, (nn.Conv2d, nn.Linear)):
                  nn.init.kaiming_normal_(module.weight)
                  if module.bias is not None:
                      module.bias.data.zero_()
              elif isinstance(module, nn.BatchNorm2d):
                  module.weight.data.fill_(1)
                  module.bias.data.zero_()
  
imports: from ..None import resnext101_64x4d
  from math import floor
  import numpy
  import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the GCN_Resnext obj's underlying member method code with example usage: obj.initialize_weights() without return types