import tensorflow as tf

                          "r").extractall(tmp_dir)

        if dataset[1][0] == "tmx":
          cleaning_requested = "tmx" in datatypes_to_clean
          tmx_filename = os.path.join(tmp_dir, dataset[1][1])
          if tmx_filename.endswith(".gz"):
            with gzip.open(tmx_filename, "rb") as tmx_file:
              _tmx_to_source_target(tmx_file, lang1_resfile, lang2_resfile,
                                    do_cleaning=cleaning_requested)
          else:
            with tf.gfile.Open(tmx_filename) as tmx_file:
              _tmx_to_source_target(tmx_file, lang1_resfile, lang2_resfile,
                                    do_cleaning=cleaning_requested)

        elif dataset[1][0] == "tsv":
          _, src_column, trg_column, glob_pattern = dataset[1]
          filenames = tf.gfile.Glob(os.path.join(tmp_dir, glob_pattern))
          if not filenames:
            # Capture *.tgz and *.tar.gz too.
            mode = "r:gz" if compressed_filepath.endswith("gz") else "r"
