class_docstr: UHiFiGAN generator module.
class_docstr_tok: ["UHiFiGAN","generator","module","."]
docstr: Remove weight normalization module from all of the layers.
docstr_tok: ["Remove","weight","normalization","module","from","all","of","the","layers","."]
code: def remove_weight_norm(self):
      """Remove weight normalization module from all of the layers."""
  
      def _remove_weight_norm(m):
          try:
              logging.debug(f"Weight norm is removed from {m}.")
              torch.nn.utils.remove_weight_norm(m)
          except ValueError:  # this module didn't have weight norm
              return
  
      self.apply(_remove_weight_norm)
  
file_path: espnet/espnet2/gan_svs/uhifigan/uhifigan.py
imports: import logging
  from typing import List, Optional
  import numpy
  import torch
  import torch.nn.functional
label_desc: Use image node_id 4 for calling the UHiFiGANGenerator obj's underlying member method code with example usage: obj.remove_weight_norm() without return types