code: def download_mind(size="small", dest_path=None):
      """Download MIND dataset
  
      Args:
          size (str): Dataset size. One of ["small", "large"]
          dest_path (str): Download path. If path is None, it will download the dataset on a temporal path
  
      Returns:
          str, str: Path to train and validation sets.
      """
      size_options = ["small", "large", "demo"]
      if size not in size_options:
          raise ValueError(
              f"Wrong size option, available options are {size_options}"
          )
      url_train, url_valid = URL_MIND[size]
      with download_path(dest_path) as path:
          train_path = maybe_download(
              url=url_train, work_directory=path
          )
          valid_path = maybe_download(
              url=url_valid, work_directory=path
          )
      return train_path, valid_path
  
imports: import os
  import random
  import logging
  import json
  import numpy
  import re
  from tqdm import tqdm
  from nltk.tokenize import RegexpTokenizer
  from recommenders.datasets.download_utils import maybe_download, download_path, unzip_file
label_desc: Use image node_id 1 for calling a global function with example usage: download_mind(size, dest_path) and returns: train_path,  valid_path