code: def prepare_wsjmix(
      datapath,
      savepath,
      n_spks=2,
      skip_prep=False,
      librimix_addnoise=False,
      fs=8000,
  ):
      """
      Prepared wsj2mix if n_spks=2 and wsj3mix if n_spks=3.
  
      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 "wsj" in datapath:
          if n_spks == 2:
              assert (
                  "2speakers" in datapath
              ), "Inconsistent number of speakers and datapath"
              create_wsj_csv(datapath, savepath)
          elif n_spks == 3:
              assert (
                  "3speakers" in datapath
              ), "Inconsistent number of speakers and datapath"
              create_wsj_csv_3spks(datapath, savepath)
          else:
              raise ValueError("Unsupported Number of Speakers")
      else:
          print("Creating a csv file for a custom dataset")
          create_custom_dataset(datapath, savepath)
  
imports: import os
  import csv
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_wsjmix(datapath, savepath, n_spks, skip_prep, librimix_addnoise, fs) without return types