code: def weights_init(m):
      """
      Applies Xavier initialization to network weights.
  
      Arguments
      ---------
      m : nn.Module
          Module to initialize.
      """
      classname = m.__class__.__name__
      if classname.find("Conv") != -1:
          try:
              nn.init.xavier_uniform_(m.weight.data)
              m.bias.data.fill_(0)
          except AttributeError:
              print("Skipping initialization of ", classname)
  
imports: import torch.nn
  import torch.nn.functional
  import torch
  from speechbrain.lobes.models.PIQ import ResBlockAudio
label_desc: Use image node_id 1 for calling a global function with example usage: weights_init(m) without return types