docstr: Feature computation pipeline
docstr_tok: ["Feature","computation","pipeline"]
code: def compute_feats(self, wavs):
      """Feature computation pipeline"""
      feats = self.hparams.Encoder(wavs)
      feats = spectral_magnitude(feats, power=0.5)
      feats = torch.log1p(feats)
      return feats
  
imports: import os
  import sys
  import torch
  import torch.nn.functional
  import torchaudio
  import speechbrain
  import speechbrain.nnet.schedulers
  from speechbrain.utils.distributed import run_on_main
  from hyperpyyaml import load_hyperpyyaml
  import numpy
  from tqdm import tqdm
  import csv
  import logging
  from speechbrain.processing.features import spectral_magnitude
  from speechbrain.utils.metric_stats import MetricStats
  from pesq import pesq
  from speechbrain.core import AMPConfig
label_desc: Use image node_id 2 for calling the Separation obj's underlying member method code with example usage: obj.compute_feats(wavs) and returns: feats