class_docstr: GAN Dataset searchs for all the wav files under root path
  and converts them to acoustic features on the fly and returns
  random segments of (audio, feature) couples.
code: def create_feature_cache(self):
      self.manager = Manager()
      self.cache = self.manager.list()
      self.cache += [None for _ in range(len(self.item_list))]
  
file_path: TTS/TTS/vocoder/datasets/gan_dataset.py
imports: import os
  import glob
  import torch
  import random
  import numpy
  from torch.utils.data import Dataset
  from multiprocessing import Manager
label_desc: Use image node_id 2 for calling the GANDataset obj's underlying member method code with example usage: obj.create_feature_cache() without return types