code: def xavier_normal_initialization(module):
      r"""using `xavier_normal_`_ in PyTorch to initialize the parameters in
      nn.Embedding and nn.Linear layers. For bias in nn.Linear layers,
      using constant 0 to initialize.
  
      .. _`xavier_normal_`:
          https://pytorch.org/docs/stable/nn.init.html?highlight=xavier_normal_#torch.nn.init.xavier_normal_
  
      Examples:
          >>> self.apply(xavier_normal_initialization)
      """
      if isinstance(module, nn.Embedding):
          xavier_normal_(module.weight.data)
      elif isinstance(module, nn.Linear):
          xavier_normal_(module.weight.data)
          if module.bias is not None:
              constant_(module.bias.data, 0)
  
imports: import torch.nn
  from torch.nn.init import xavier_normal_, xavier_uniform_, constant_
label_desc: Use image node_id 1 for calling a global function with example usage: xavier_normal_initialization(module) without return types