code: def _download_and_parse_dataset(tmp_dir, train):
      """Downloads and prepairs the dataset to be parsed by the data_generator."""
      file_path = generator_utils.maybe_download(
          tmp_dir, _SNLI_ZIP, _SNLI_URL
      )
      zip_ref = zipfile.ZipFile(file_path, "r")
      zip_ref.extractall(tmp_dir)
      zip_ref.close()
  
      file_name = "train" if train else "dev"
      dataset_file_path = os.path.join(
          tmp_dir, _SNLI_DATA_PATH % file_name
      )
      _parse_dataset(dataset_file_path, tmp_dir, train)
  
file_path: tensor2tensor/tensor2tensor/data_generators/snli.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import zipfile
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import tokenizer
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: _download_and_parse_dataset(tmp_dir, train) without return types