code: def download_fever_nli_data_and_write_config(
      task_name: str, task_data_path: str, task_config_path: str
  ):
      os.makedirs(task_data_path, exist_ok=True)
      download_utils.download_and_unzip(
          "https://www.dropbox.com/s/hylbuaovqwo2zav/nli_fever.zip?dl=1",
          task_data_path,
      )
      # Since the FEVER NLI dataset doesn't have labels for the dev set, we also download the original
      # FEVER dev set and match example CIDs to obtain labels.
      orig_dev_path = os.path.join(
          task_data_path, "fever-dev-temp.jsonl"
      )
      download_utils.download_file(
          "https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_dev.jsonl",
          orig_dev_path,
      )
      id_to_label = {}
      for line in py_io.read_jsonl(orig_dev_path):
          if "id" not in line:
              logging.warning("FEVER dev dataset is missing ID.")
              continue
          if "label" not in line:
              logging.warning("FEVER dev dataset is missing label.")
              continue
          id_to_label[line["id"]] = line["label"]
      os.remove(orig_dev_path)
  
      dev_path = os.path.join(
          task_data_path, "nli_fever", "dev_fitems.jsonl"
      )
      dev_examples = []
      for line in py_io.read_jsonl(dev_path):
          if "cid" not in line:
              logging.warning(
                  "Data in {} is missing CID.".format(dev_path)
              )
              continue
          if int(line["cid"]) not in id_to_label:
              logging.warning(
                  "Could not match CID {} to dev data.".format(
                      line["cid"]
                  )
              )
              continue
          dev_example = line
          dev_example["label"] = id_to_label[int(line["cid"])]
          dev_examples.append(dev_example)
      py_io.write_jsonl(
          dev_examples, os.path.join(task_data_path, "val.jsonl")
      )
      os.remove(dev_path)
  
      for phase in ["train", "test"]:
          os.rename(
              os.path.join(
                  task_data_path, "nli_fever", f"{phase}_fitems.jsonl"
              ),
              os.path.join(task_data_path, f"{phase}.jsonl"),
          )
      shutil.rmtree(os.path.join(task_data_path, "nli_fever"))
  
      py_io.write_json(
          data={
              "task": task_name,
              "paths": {
                  "train": os.path.join(task_data_path, "train.jsonl"),
                  "val": os.path.join(task_data_path, "val.jsonl"),
                  "test": os.path.join(task_data_path, "test.jsonl"),
              },
              "name": task_name,
          },
          path=task_config_path,
      )
  
imports: import json
  import logging
  import os
  import pandas
  import re
  import shutil
  import tarfile
  from operator import itemgetter
  from collections import Counter
  import jiant.scripts.download_data.utils
  import jiant.utils.display
  import jiant.utils.python.filesystem
  import jiant.utils.python.io
  from jiant.scripts.download_data.constants import SQUAD_TASKS, DIRECT_SUPERGLUE_TASKS_TO_DATA_URLS
label_desc: Use image node_id 11 for calling a global function with example usage: download_fever_nli_data_and_write_config(task_name, task_data_path, task_config_path) without return types