class_docstr: A ready-to-use model for speech enhancement.
  
  Arguments
  ---------
  See ``Pretrained``.
  
  Example
  -------
  >>> import torch
  >>> from speechbrain.inference.enhancement import SpectralMaskEnhancement
  >>> # Model is downloaded from the speechbrain HuggingFace repo
  >>> tmpdir = getfixture("tmpdir")
  >>> enhancer = SpectralMaskEnhancement.from_hparams(
  ...     source="speechbrain/metricgan-plus-voicebank",
  ...     savedir=tmpdir,
  ... )
  >>> enhanced = enhancer.enhance_file(
  ...     "speechbrain/metricgan-plus-voicebank/example.wav"
  ... )
docstr: Compute the log spectral magnitude features for masking.
  
  Arguments
  ---------
  wavs : torch.Tensor
      A batch of waveforms to convert to log spectral mags.
docstr_tok: ["Compute","the","log","spectral","magnitude","features","for","masking",".","Arguments","--","--","--","--","-","wavs",":","torch.Tensor","A","batch","of","waveforms","to","convert","to","log","spectral","mags","."]
code: def compute_features(self, wavs):
      """Compute the log spectral magnitude features for masking.
  
      Arguments
      ---------
      wavs : torch.Tensor
          A batch of waveforms to convert to log spectral mags.
      """
      feats = self.hparams.compute_stft(wavs)
      feats = self.hparams.spectral_magnitude(feats)
      return torch.log1p(feats)
  
file_path: speechbrain/speechbrain/inference/enhancement.py
imports: import torch
  import torchaudio
  from speechbrain.inference.interfaces import Pretrained
  from speechbrain.utils.callchains import lengths_arg_exists
label_desc: Use image node_id 1 for calling the SpectralMaskEnhancement obj's underlying member method code with example usage: obj.compute_features(wavs) and returns: torch