code: def init_weights(model):
      for m in model.modules():
          if isinstance(m, nn.Conv2d):
              nn.init.kaiming_normal_(m.weight)
              if m.bias is not None:
                  nn.init.constant_(m.bias, 0)
          elif isinstance(m, nn.Linear):
              nn.init.kaiming_normal_(m.weight)
              if m.bias is not None:
                  nn.init.constant_(m.bias, 0)
          elif isinstance(m, nn.BatchNorm2d):
              nn.init.constant_(m.weight, 1)
              if m.bias is not None:
                  nn.init.constant_(m.weight, 1)
  
file_path: pywick/pywick/models/segmentation/testnets/deeplabv3.py
imports: from collections import OrderedDict
  import torch
  import torch.nn
  import torch.nn.functional
  from .resnet import _ConvBatchNormReLU, _ResBlock
  from .msc import MSC
label_desc: Use image node_id 1 for calling a global function with example usage: init_weights(model) without return types