def load_matt_mahoney_text8_dataset(path='<STR_LIT:data>'):
path = os.path.join(path, '<STR_LIT>')<EOL>logging.info("<STR_LIT>".format(path))<EOL>filename = '<STR_LIT>'<EOL>url = '<STR_LIT>'<EOL>maybe_download_and_extract(filename, path, url, expected_bytes=<NUM_LIT>)<EOL>with zipfile.ZipFile(os.path.join(path, filename)) as f:<EOL><INDENT>word_list = f.read(f.namelist()[<NUM_LIT:0>]).split()<EOL>for idx, _ in enumerate(word_list):<EOL><INDENT>word_list[idx] = word_list[idx].decode()<EOL><DEDENT><DEDENT>return word_list<EOL>
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))