code: def pesq_eval(pred_wav, target_wav):
      """Normalized PESQ (to 0-1)"""
      return (
          pesq(
              fs=16000,
              ref=target_wav.numpy(),
              deg=pred_wav.numpy(),
              mode="wb",
          )
          + 0.5
      ) / 5
  
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 1 for calling a global function with example usage: pesq_eval(pred_wav, target_wav) and returns: unknown