code: def init_weights(model):
      for m in model.modules():
          if isinstance(m, nn.Conv2d):
              n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
              m.weight.data.normal_(0, math.sqrt(2.0 / n))
          elif isinstance(m, nn.BatchNorm2d):
              m.weight.data.fill_(1)
              m.bias.data.zero_()
          elif isinstance(m, nn.BatchNorm1d):
              m.weight.data.fill_(1)
              m.bias.data.zero_()
          elif isinstance(m, nn.Linear):
              m.weight.data.normal_(0, 0.02)
              m.bias.data.zero_()
  
file_path: insightface/body/human_pose/ambiguity_aware/lib/utils/misc.py
imports: import os
  import os.path
  import h5py
  import math
  import time
  import logging
  import pickle
  import torch.nn
  from pathlib import Path
label_desc: Use image node_id 2 for calling a global function with example usage: init_weights(model) without return types