code: def __init__(self, kernel, channel, padding, dilations=[1, 3, 5]):
      super().__init__()
      resstack = []
      for dilation in dilations:
          resstack += [
              nn.LeakyReLU(0.2),
              nn.ReflectionPad1d(dilation),
              nn.utils.parametrizations.weight_norm(
                  nn.Conv1d(
                      channel,
                      channel,
                      kernel_size=kernel,
                      dilation=dilation,
                  )
              ),
              nn.LeakyReLU(0.2),
              nn.ReflectionPad1d(padding),
              nn.utils.parametrizations.weight_norm(
                  nn.Conv1d(channel, channel, kernel_size=1)
              ),
          ]
      self.resstack = nn.Sequential(*resstack)
  
      self.shortcut = nn.utils.parametrizations.weight_norm(
          nn.Conv1d(channel, channel, kernel_size=1)
      )
  
file_path: TTS/TTS/vocoder/layers/hifigan.py
imports: from torch import nn
  from torch.nn.utils.parametrize import remove_parametrizations
label_desc: Use image node_id 1 to create a new ResStack object from inherited base classes: nn with example: obj = ResStack(kernel, channel, padding, dilations)