code: def prepare_binaural_wsj0mix(
      experiment_name,
      datapath,
      savepath,
      n_spks=2,
      skip_prep=False,
      fs=8000,
      version="min",
  ):
      """
      Prepared binaural wsj2mix if n_spks=2 and binaural wsj3mix if n_spks=3.
  
      Arguments:
      ----------
          datapath (str) : path for the binaural-wsj0mix dataset.
          savepath (str) : path where we save the csv file.
          n_spks (int): number of speakers
          skip_prep (bool): If True, skip data preparation
      """
  
      if skip_prep:
          return
  
      if "noise" in experiment_name:
          create_binaural_wsj0mix2_noise_csv(
              datapath, savepath, fs, version
          )
      elif "reverb" in experiment_name:
          create_binaural_wsj0mix2_reverb_csv(
              datapath, savepath, fs, version
          )
      elif n_spks == 2:
          create_binaural_wsj0mix2_csv(datapath, savepath, fs, version)
      elif n_spks == 3:
          create_binaural_wsj0mix3_csv(datapath, savepath, fs, version)
      else:
          raise ValueError("Unsupported preparation mode")
  
imports: import os
  import csv
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_binaural_wsj0mix(experiment_name, datapath, savepath, n_spks, skip_prep, fs, version) without return types