class_docstr: HiFi-GAN scale discriminator module.
docstr: Remove spectral normalization module from all of the layers.
docstr_tok: ["Remove","spectral","normalization","module","from","all","of","the","layers","."]
code: def remove_spectral_norm(self):
      """Remove spectral normalization module from all of the layers."""
  
      def _remove_spectral_norm(m):
          try:
              logging.debug(f"Spectral norm is removed from {m}.")
              torch.nn.utils.remove_spectral_norm(m)
          except ValueError:  # this module didn't have weight norm
              return
  
      self.apply(_remove_spectral_norm)
  
imports: import copy
  import logging
  from typing import Any, Dict, List, Optional
  import numpy
  import torch
  import torch.nn.functional
  from espnet2.gan_tts.hifigan.residual_block import ResidualBlock
label_desc: Use image node_id 6 for calling the HiFiGANScaleDiscriminator obj's underlying member method code with example usage: obj.remove_spectral_norm() without return types