docstr: Feature computation pipeline
docstr_tok: ["Feature","computation","pipeline"]
code: def compute_feats(self, wavs):
      """Feature computation pipeline"""
      feats = self.hparams.compute_STFT(wavs)
      feats = spectral_magnitude(feats, power=0.5)
      feats = torch.log1p(feats)
      return feats
  
imports: import os
  import sys
  import shutil
  import pickle
  import torch
  import torchaudio
  import speechbrain
  from pesq import pesq
  from enum import Enum, auto
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.utils.metric_stats import MetricStats
  from speechbrain.processing.features import spectral_magnitude
  from speechbrain.nnet.loss.stoi_loss import stoi_loss
  from speechbrain.utils.distributed import run_on_main
  from speechbrain.dataio.sampler import ReproducibleWeightedRandomSampler
label_desc: Use image node_id 2 for calling the MetricGanBrain obj's underlying member method code with example usage: obj.compute_feats(wavs) and returns: feats