code: def __init__(self, use_spectral_norm=False, debug=False):
      super().__init__()
      norm_f = (
          weight_norm if use_spectral_norm == False else spectral_norm
      )
      conv_ch = [128, 256, 512, 1024] if not debug else [16, 32, 32, 64]
      self.convs = nn.ModuleList(
          [
              norm_f(Conv1d(1, conv_ch[0], 15, 1, padding=7)),
              norm_f(
                  Conv1d(
                      conv_ch[0],
                      conv_ch[0],
                      41,
                      2,
                      groups=4,
                      padding=20,
                  )
              ),
              norm_f(
                  Conv1d(
                      conv_ch[0],
                      conv_ch[1],
                      41,
                      2,
                      groups=16,
                      padding=20,
                  )
              ),
              norm_f(
                  Conv1d(
                      conv_ch[1],
                      conv_ch[2],
                      41,
                      4,
                      groups=16,
                      padding=20,
                  )
              ),
              norm_f(
                  Conv1d(
                      conv_ch[2],
                      conv_ch[3],
                      41,
                      4,
                      groups=16,
                      padding=20,
                  )
              ),
              norm_f(
                  Conv1d(
                      conv_ch[3],
                      conv_ch[3],
                      41,
                      1,
                      groups=16,
                      padding=20,
                  )
              ),
              norm_f(Conv1d(conv_ch[3], conv_ch[3], 5, 1, padding=2)),
          ]
      )
      self.conv_post = norm_f(Conv1d(conv_ch[3], 1, 3, 1, padding=1))
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
  from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
  from nemo.core.classes.common import typecheck
  from nemo.core.classes.module import NeuralModule
  from nemo.core.neural_types.elements import AudioSignal, MelSpectrogramType, VoidType
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 1 to create a new DiscriminatorS object from inherited base classes: NeuralModule with example: obj = DiscriminatorS(use_spectral_norm, debug)