code: def __init__(
      self,
      manifest_paths,
      min_duration=0.5,
      max_duration=16.0,
      pad_multiple=1024,
      sample_rate=22050,
      sup_data_dir=None,
  ):
      self.data = []
      for manifest_path in manifest_paths:
          with open(manifest_path, "r") as f:
              for line in f:
                  record = json.loads(line)
                  if (
                      record["duration"] < min_duration
                      or record["duration"] > max_duration
                  ):
                      continue
                  self.data.append(json.loads(line))
  
      self.base_data_dir = get_base_dir(
          [item["audio_filepath"] for item in self.data]
      )
      if sup_data_dir is not None:
          self.sup_data_dir = sup_data_dir
      else:
          self.sup_data_dir = os.path.join(
              self.base_data_dir, "sup_data"
          )
      if not os.path.exists(self.sup_data_dir):
          os.makedirs(self.sup_data_dir)
  
      self.pad_multiple = pad_multiple
      self.sample_rate = sample_rate
  
imports: import argparse
  import json
  import os
  import time
  from multiprocessing import Pool
  from pathlib import Path
  import hydra.utils
  import librosa
  import numpy
  import torch
  from omegaconf import open_dict
  from tqdm import tqdm
  from nemo.collections.asr.parts.preprocessing.segment import AudioSegment
  from nemo.collections.tts.models import ssl_tts
  from nemo.collections.tts.parts.utils.tts_dataset_utils import get_base_dir
  from nemo.core.classes import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new AudioDataset object from inherited base classes: Dataset with example: obj = AudioDataset(manifest_paths, min_duration, max_duration, pad_multiple, sample_rate, sup_data_dir)