class_docstr: docstring for Discriminator.
class_docstr_tok: ["docstring","for","Discriminator","."]
code: def __init__(
      self,
      fft_size=1024,
      hop_length=120,
      win_length=600,
      use_spectral_norm=False,
  ):
      super().__init__()
      norm_f = (
          weight_norm if use_spectral_norm is False else spectral_norm
      )
      self.fft_size = fft_size
      self.hop_length = hop_length
      self.win_length = win_length
      self.stft = TorchSTFT(fft_size, hop_length, win_length)
      self.discriminators = nn.ModuleList(
          [
              norm_f(
                  nn.Conv2d(1, 32, kernel_size=(3, 9), padding=(1, 4))
              ),
              norm_f(
                  nn.Conv2d(
                      32,
                      32,
                      kernel_size=(3, 9),
                      stride=(1, 2),
                      padding=(1, 4),
                  )
              ),
              norm_f(
                  nn.Conv2d(
                      32,
                      32,
                      kernel_size=(3, 9),
                      stride=(1, 2),
                      padding=(1, 4),
                  )
              ),
              norm_f(
                  nn.Conv2d(
                      32,
                      32,
                      kernel_size=(3, 9),
                      stride=(1, 2),
                      padding=(1, 4),
                  )
              ),
              norm_f(
                  nn.Conv2d(
                      32,
                      32,
                      kernel_size=(3, 3),
                      stride=(1, 1),
                      padding=(1, 1),
                  )
              ),
          ]
      )
  
      self.out = norm_f(nn.Conv2d(32, 1, 3, 1, 1))
  
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 SpecDiscriminator object from inherited base classes: nn with example: obj = SpecDiscriminator(fft_size, hop_length, win_length, use_spectral_norm)