docstr: Apply weight normalization module from all of the layers.
docstr_tok: ["Apply","weight","normalization","module","from","all","of","the","layers","."]
code: def apply_weight_norm(self):
      """Apply weight normalization module from all of the layers."""
  
      def _apply_weight_norm(m):
          if isinstance(m, (torch.nn.Conv1d, torch.nn.Conv2d)):
              torch.nn.utils.parametrizations.weight_norm(m)
              # print(f"Weight norm is applied to {m}.")
  
      self.apply(_apply_weight_norm)
  
file_path: TTS/TTS/vocoder/models/univnet_generator.py
imports: from typing import List
  import numpy
  import torch
  import torch.nn.functional
  from torch.nn.utils import parametrize
  from TTS.vocoder.layers.lvc_block import LVCBlock
label_desc: Use image node_id 4 for calling the UnivnetGenerator obj's underlying member method code with example usage: obj.apply_weight_norm() without return types