code: def __init__(  # pylint: disable=dangerous-default-value
      self,
      fft_sizes=[1024, 2048, 512],
      hop_sizes=[120, 240, 50],
      win_lengths=[600, 1200, 240],
      window="hann_window",
  ):
      super().__init__()
      self.discriminators = nn.ModuleList(
          [
              SpecDiscriminator(
                  fft_sizes[0], hop_sizes[0], win_lengths[0], window
              ),
              SpecDiscriminator(
                  fft_sizes[1], hop_sizes[1], win_lengths[1], window
              ),
              SpecDiscriminator(
                  fft_sizes[2], hop_sizes[2], win_lengths[2], window
              ),
          ]
      )
  
file_path: TTS/TTS/vocoder/models/univnet_discriminator.py
imports: import torch
  import torch.nn.functional
  from torch import nn
  from torch.nn.utils import spectral_norm
  from torch.nn.utils.parametrizations import weight_norm
  from TTS.utils.audio.torch_transforms import TorchSTFT
  from TTS.vocoder.models.hifigan_discriminator import MultiPeriodDiscriminator
label_desc: Use image node_id 1 to create a new MultiResSpecDiscriminator object from inherited base classes: torch.nn with example: obj = MultiResSpecDiscriminator(fft_sizes, hop_sizes, win_lengths, window)