code: def __init__(
      self,
      filter_length=1024,
      hop_length=256,
      win_length=1024,
      n_mel_channels=80,
      sampling_rate=22050,
      mel_fmin=0.0,
      mel_fmax=8000.0,
  ):
      super(TacotronSTFT, self).__init__()
      self.n_mel_channels = n_mel_channels
      self.sampling_rate = sampling_rate
      self.stft_fn = STFT(filter_length, hop_length, win_length)
      mel_basis = librosa_mel_fn(
          sampling_rate,
          filter_length,
          n_mel_channels,
          mel_fmin,
          mel_fmax,
      )
      mel_basis = torch.from_numpy(mel_basis).float()
      self.register_buffer("mel_basis", mel_basis)
  
imports: import torch
  from librosa.filters import mel
  from .audio_processing import dynamic_range_compression
  from .audio_processing import dynamic_range_decompression
  from .stft import STFT
  from .utils import get_mask_from_lengths
label_desc: Use image node_id 1 to create a new TacotronSTFT object from inherited base classes: torch.nn with example: obj = TacotronSTFT(filter_length, hop_length, win_length, n_mel_channels, sampling_rate, mel_fmin, mel_fmax)