code: def spectrogram(self, x):
      n_fft, hop_length, win_length = self.resolution
      x = F.pad(
          x,
          (
              int((n_fft - hop_length) / 2),
              int((n_fft - hop_length) / 2),
          ),
          mode="reflect",
      )
      x = x.squeeze(1)
      x = torch.view_as_real(
          torch.stft(
              x,
              n_fft=n_fft,
              hop_length=hop_length,
              win_length=win_length,
              center=False,
              return_complex=True,
          )
      )  # [B, F, TT, 2] (Note: torch.stft() returns complex tensor [B, F, TT]; converted via view_as_real)
      mag = torch.norm(x, p=2, dim=-1)  # [B, F, TT]
  
      return mag
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Conv2d
  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 5 for calling the DiscriminatorR obj's underlying member method code with example usage: obj.spectrogram(x) and returns: mag