code: def _weight_init(m):
      if isinstance(m, nn.Conv2d):
          nn.init.kaiming_normal_(
              m.weight, mode="fan_out", nonlinearity="relu"
          )
      elif isinstance(m, nn.BatchNorm2d):
          nn.init.constant_(m.weight, 1.0)
          nn.init.constant_(m.bias, 0.0)
  
imports: import math
  from collections import OrderedDict
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 for calling a global function with example usage: _weight_init(m) without return types