code: def _init_weights(self):
      layers = [*self.additional_blocks, *self.loc, *self.conf]
      for layer in layers:
          for param in layer.parameters():
              if param.dim() > 1:
                  nn.init.xavier_uniform_(param)
  
imports: import torch
  import torch.nn
  from torchvision.models.resnet import resnet18, resnet34, resnet50, resnet101, resnet152
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 3 for calling the SSD300 obj's underlying member method code with example usage: obj._init_weights() without return types