code: def main(args):
      if args.data_dir is None:
          args.data_dir = args.benchmark
      args.cache_path = os.path.join(args.cache_path, args.benchmark)
      print(
          'Downloading {} to "{}". Selected tasks = {}'.format(
              args.benchmark, args.data_dir, args.tasks
          )
      )
      os.makedirs(args.cache_path, exist_ok=True)
      os.makedirs(args.data_dir, exist_ok=True)
      tasks = get_tasks(args.benchmark, args.tasks)
      if args.benchmark == "glue":
          TASK2PATH = GLUE_TASK2PATH
          TASK2READER = GLUE_READERS
      elif args.benchmark == "superglue":
          TASK2PATH = SUPERGLUE_TASK2PATH
          TASK2READER = SUPERGLUE_READER
      else:
          raise NotImplementedError
      for task in tasks:
          print("Processing {}...".format(task))
          if task == "diagnostic" or "diagnostic" in task:
              if args.benchmark == "glue":
                  reader = TASK2READER[task]
                  base_dir = os.path.join(
                      args.data_dir, "rte_diagnostic"
                  )
                  os.makedirs(base_dir, exist_ok=True)
                  download(
                      TASK2PATH["diagnostic"][0],
                      path=os.path.join(base_dir, "diagnostic.tsv"),
                      sha1_hash=_URL_FILE_STATS[
                          TASK2PATH["diagnostic"][0]
                      ],
                  )
                  download(
                      TASK2PATH["diagnostic"][1],
                      path=os.path.join(
                          base_dir, "diagnostic-full.tsv"
                      ),
                      sha1_hash=_URL_FILE_STATS[
                          TASK2PATH["diagnostic"][1]
                      ],
                  )
                  df = reader(base_dir)
                  df.to_parquet(
                      os.path.join(base_dir, "diagnostic-full.parquet")
                  )
              else:
                  for key, name in [
                      ("broadcoverage-diagnostic", "AX-b"),
                      ("winogender-diagnostic", "AX-g"),
                  ]:
                      data_file = os.path.join(
                          args.cache_path, "{}.zip".format(key)
                      )
                      url = TASK2PATH[key]
                      reader = TASK2READER[key]
                      download(
                          url, data_file, sha1_hash=_URL_FILE_STATS[url]
                      )
                      with zipfile.ZipFile(data_file) as zipdata:
                          zipdata.extractall(args.data_dir)
                      df = reader(os.path.join(args.data_dir, name))
                      df.to_parquet(
                          os.path.join(
                              args.data_dir,
                              name,
                              "{}.parquet".format(name),
                          )
                      )
          elif task == "mrpc":
              reader = TASK2READER[task]
              format_mrpc(args.data_dir)
              df_dict, meta_data = reader(
                  os.path.join(args.data_dir, "mrpc")
              )
              for key, df in df_dict.items():
                  if key == "val":
                      key = "dev"
                  df.to_parquet(
                      os.path.join(
                          args.data_dir,
                          "mrpc",
                          "{}.parquet".format(key),
                      )
                  )
              with open(
                  os.path.join(args.data_dir, "mrpc", "metadata.json"),
                  "w",
              ) as f:
                  json.dump(meta_data, f)
          else:
              # Download data
              data_file = os.path.join(
                  args.cache_path, "{}.zip".format(task)
              )
              url = TASK2PATH[task]
              reader = TASK2READER[task]
              download(url, data_file, sha1_hash=_URL_FILE_STATS[url])
              base_dir = os.path.join(args.data_dir, task)
              if os.path.exists(base_dir):
                  print("Found!")
                  continue
              zip_dir_name = None
              with zipfile.ZipFile(data_file) as zipdata:
                  if zip_dir_name is None:
                      zip_dir_name = os.path.dirname(
                          zipdata.infolist()[0].filename
                      )
                  zipdata.extractall(args.data_dir)
              shutil.move(
                  os.path.join(args.data_dir, zip_dir_name), base_dir
              )
              df_dict, meta_data = reader(base_dir)
              for key, df in df_dict.items():
                  if key == "val":
                      key = "dev"
                  df.to_parquet(
                      os.path.join(base_dir, "{}.parquet".format(key))
                  )
              if meta_data is not None:
                  with open(
                      os.path.join(base_dir, "metadata.json"), "w"
                  ) as f:
                      json.dump(meta_data, f)
          print("\tCompleted!")
  
imports: import os
  import shutil
  import argparse
  import zipfile
  import json
  import pandas
  import pyarrow
  import pyarrow.json
  from autogluon_contrib_nlp.utils.misc import download, load_checksum_stats
  from autogluon_contrib_nlp.base import get_data_home_dir
  from autogluon_contrib_nlp.data.tokenizers import WhitespaceTokenizer
label_desc: Use image node_id 27 for calling a global function with example usage: main(args) without return types