code: def get_dataset_filelist(a):
      with open(a.input_training_file, "r", encoding="utf-8") as fi:
          training_files = [
              os.path.join(a.input_wavs_dir, x.split("|")[0] + ".wav")
              for x in fi.read().split("\n")
              if len(x) > 0
          ]
  
      with open(a.input_validation_file, "r", encoding="utf-8") as fi:
          validation_files = [
              os.path.join(a.input_wavs_dir, x.split("|")[0] + ".wav")
              for x in fi.read().split("\n")
              if len(x) > 0
          ]
      return training_files, validation_files
  
imports: import math
  import os
  import random
  import torch
  import torch.utils.data
  import numpy
  from librosa.util import normalize
  from scipy.io.wavfile import read
  from librosa.filters import mel
label_desc: Use image node_id 9 for calling a global function with example usage: get_dataset_filelist(a) and returns: training_files,  validation_files