code: def apply_weight_norm(self):
      for _, layer in enumerate(self.dblocks):
          if len(layer.state_dict()) != 0:
              layer.apply_weight_norm()
  
      for _, layer in enumerate(self.film):
          if len(layer.state_dict()) != 0:
              layer.apply_weight_norm()
  
      for _, layer in enumerate(self.ublocks):
          if len(layer.state_dict()) != 0:
              layer.apply_weight_norm()
  
      self.x_conv = weight_norm(self.x_conv)
      self.out_conv = weight_norm(self.out_conv)
      self.y_conv = weight_norm(self.y_conv)
  
file_path: TTS/TTS/vocoder/models/wavegrad.py
imports: import numpy
  import torch
  from torch import nn
  from torch.nn.utils import weight_norm
  from ..layers.wavegrad import DBlock, FiLM, UBlock, Conv1d
label_desc: Use image node_id 8 for calling the Wavegrad obj's underlying member method code with example usage: obj.apply_weight_norm() without return types