code: def prepare_librimix(
      datapath,
      savepath,
      n_spks=2,
      skip_prep=False,
      librimix_addnoise=False,
      fs=8000,
  ):
      """
  
      Prepare .csv files for librimix
  
      Arguments:
      ----------
          datapath (str) : path for the wsj0-mix dataset.
          savepath (str) : path where we save the csv file.
          n_spks (int): number of speakers
          skip_prep (bool): If True, skip data preparation
          librimix_addnoise: If True, add whamnoise to librimix datasets
      """
  
      if skip_prep:
          return
  
      if "Libri" in datapath:
          # Libri 2/3Mix datasets
          if n_spks == 2:
              assert (
                  "Libri2Mix" in datapath
              ), "Inconsistent number of speakers and datapath"
              create_libri2mix_csv(
                  datapath, savepath, addnoise=librimix_addnoise
              )
          elif n_spks == 3:
              assert (
                  "Libri3Mix" in datapath
              ), "Inconsistent number of speakers and datapath"
              create_libri3mix_csv(
                  datapath, savepath, addnoise=librimix_addnoise
              )
          else:
              raise ValueError("Unsupported Number of Speakers")
      else:
          raise ValueError("Unsupported Dataset")
  
imports: import os
  import csv
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_librimix(datapath, savepath, n_spks, skip_prep, librimix_addnoise, fs) without return types