class_docstr: Single Resolution STFT loss.
  
  Args:
      n_fft (int): Nb of FFT.
      hop_length (int): Hop length.
      win_length (int): Window length.
      window (str): Window function type.
      normalized (bool): Whether to use normalized STFT or not.
      epsilon (float): Epsilon for numerical stability.
      factor_sc (float): Coefficient for the spectral loss.
      factor_mag (float): Coefficient for the magnitude loss.
code: def __init__(
      self,
      n_fft: int = 1024,
      hop_length: int = 120,
      win_length: int = 600,
      window: str = "hann_window",
      normalized: bool = False,
      factor_sc: float = 0.1,
      factor_mag: float = 0.1,
      epsilon: float = torch.finfo(torch.float32).eps,
  ):
      super().__init__()
      self.loss = STFTLosses(
          n_fft, hop_length, win_length, window, normalized, epsilon
      )
      self.factor_sc = factor_sc
      self.factor_mag = factor_mag
  
imports: import typing
  import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new STFTLoss object from inherited base classes: nn with example: obj = STFTLoss(n_fft, hop_length, win_length, window, normalized, factor_sc, factor_mag, epsilon)