code: def iterate(bs=1, start=0):
      print(f"there are {len(ci)} samples in the dataset")
      for i in range(start, len(ci), bs):
          samples, sample_lens = zip(
              *[
                  load_wav(BASEDIR / v["files"][0]["fname"])
                  for v in ci[i : i + bs]
              ]
          )
          samples = list(samples)
          # pad to same length
          max_len = max(sample_lens)
          for j in range(len(samples)):
              samples[j] = np.pad(
                  samples[j], (0, max_len - sample_lens[j]), "constant"
              )
          samples, sample_lens = np.array(samples), np.array(
              sample_lens
          )
  
          yield feature_extract(samples, sample_lens), np.array(
              [v["transcript"] for v in ci[i : i + bs]]
          )
  
imports: import json
  import pathlib
  import numpy
  import librosa
  import soundfile
label_desc: Use image node_id 3 for calling a global function with example usage: iterate(bs, start) without return types