code: def initialize_weights(self):
      if self.conditional:
          if self.hidden_units is not None:
              if self.hidden_initializer == "normal":
                  torch.nn.init.normal(self.hidden_dense.weight)
              elif (
                  self.hidden_initializer == "xavier"
              ):  # glorot_uniform
                  torch.nn.init.xavier_uniform_(
                      self.hidden_dense.weight
                  )
  
          if self.center:
              torch.nn.init.constant_(self.beta_dense.weight, 0)
          if self.scale:
              torch.nn.init.constant_(self.gamma_dense.weight, 0)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
  from transformers import AutoModel
label_desc: Use image node_id 2 for calling the LayerNorm obj's underlying member method code with example usage: obj.initialize_weights() without return types