code: def codes2wav(self, codes, speaker_ids=[0, 4], pred_dur=False):
      if isinstance(codes, dict):
          codes = list(codes.values())
      assert len(codes) == 2
      wav1 = self.code2wav(codes[0], speaker_ids[0], pred_dur)
      wav2 = self.code2wav(codes[1], speaker_ids[1], pred_dur)
      wav = np.stack([wav1, wav2])
      return wav
  
file_path: fairseq/examples/textless_nlp/dgslm/dgslm_utils.py
imports: import numpy
  import torch
  import json
  from fairseq import utils
  from fairseq.models.text_to_speech.vocoder import CodeHiFiGANVocoder
  from examples.textless_nlp.gslm.speech2unit.pretrained.hubert_feature_reader import HubertFeatureReader
  from examples.hubert.simple_kmeans.dump_km_label import ApplyKmeans
label_desc: Use image node_id 3 for calling the HifiganVocoder obj's underlying member method code with example usage: obj.codes2wav(codes, speaker_ids, pred_dur) and returns: wav