code: def load_matt_mahoney_text8_dataset(path="data"):
      """Load Matt Mahoney's dataset.
  
      Download a text file from Matt Mahoney's website
      if not present, and make sure it's the right size.
      Extract the first file enclosed in a zip file as a list of words.
      This dataset can be used for Word Embedding.
  
      Parameters
      ----------
      path : str
          The path that the data is downloaded to, defaults is ``data/mm_test8/``.
  
      Returns
      --------
      list of str
          The raw text data e.g. [.... 'their', 'families', 'who', 'were', 'expelled', 'from', 'jerusalem', ...]
  
      Examples
      --------
      >>> words = tl.files.load_matt_mahoney_text8_dataset()
      >>> print('Data size', len(words))
  
      """
      path = os.path.join(path, "mm_test8")
      logging.info(
          "Load or Download matt_mahoney_text8 Dataset> {}".format(path)
      )
  
      filename = "text8.zip"
      url = "http://mattmahoney.net/dc/"
      maybe_download_and_extract(
          filename, path, url, expected_bytes=31344016
      )
  
      with zipfile.ZipFile(os.path.join(path, filename)) as f:
          word_list = f.read(f.namelist()[0]).split()
          for idx, _ in enumerate(word_list):
              word_list[idx] = word_list[idx].decode()
      return word_list
  
imports: import os
  import zipfile
  from tensorlayer import logging
  from tensorlayer.files.utils import maybe_download_and_extract
label_desc: Use image node_id 1 for calling a global function with example usage: load_matt_mahoney_text8_dataset(path) and returns: word_list