code: def prepare_dataset_from_URL(
      URL, dest_folder, ext, csv_file, max_length=None
  ):
      """Downloads a dataset containing recordings (e.g., noise sequences)
      from the provided URL and prepares the necessary CSV files for use by the noise augmenter.
  
      Arguments
      ---------
      URL: str
          The URL of the dataset to download.
      dest_folder : str
          The local folder where the noisy dataset will be downloaded.
      ext: str
          File extensions to search for within the downloaded dataset.
      csv_file : str
          The path to store the prepared noise CSV file.
      max_length : float
          The maximum length in seconds.
          Recordings longer than this will be automatically cut into pieces.
      """
  
      # Download and unpack if necessary
      data_file = os.path.join(dest_folder, "data.zip")
  
      if not os.path.isdir(dest_folder):
          download_file(URL, data_file, unpack=True)
      else:
          download_file(URL, data_file)
  
      # Prepare noise csv if necessary
      if not os.path.isfile(csv_file):
          filelist = get_all_files(dest_folder, match_and=["." + ext])
          prepare_csv(filelist, csv_file, max_length)
  
file_path: speechbrain/speechbrain/augment/preparation.py
imports: import os
  import logging
  import torchaudio
  from speechbrain.utils.data_utils import download_file
  from speechbrain.utils.data_utils import get_all_files
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_dataset_from_URL(URL, dest_folder, ext, csv_file, max_length) without return types