code: def prepare_wham_whamr_csv(
      datapath, savepath, skip_prep=False, fs=8000, task="separation"
  ):
      """
      Prepares the csv files for wham or whamr dataset
  
      Arguments:
      ----------
          datapath (str) : path for the wsj0-mix dataset.
          savepath (str) : path where we save the csv file.
          skip_prep (bool): If True, skip data preparation
      """
  
      if skip_prep:
          return
  
      if "wham_original" in datapath:
          # if we want to train a model on the original wham dataset
          create_wham_whamr_csv(
              datapath,
              savepath,
              fs,
              savename="whamorg_",
              add_reverb=False,
              task=task,
          )
      elif "whamr" in datapath:
          # if we want to train a model on the whamr dataset
          create_wham_whamr_csv(
              datapath, savepath, fs, add_reverb=True, task=task
          )
      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_wham_whamr_csv(datapath, savepath, skip_prep, fs, task) without return types