code: def test_huggingface_wordpiece_tokenizer_v08():
      """Test for huggingface tokenizer >=0.8"""
      with tempfile.TemporaryDirectory() as dir_path:
          model_path = os.path.join(
              dir_path, "hf_wordpiece_new_0.8.model"
          )
          download(
              url=get_repo_url()
              + "tokenizer_test_models/hf_wordpiece_new_0.8/hf_wordpiece.model",
              path=model_path,
              sha1_hash="66ccadf6e5e354ff9604e4a82f107a2ac873abd5",
          )
          vocab_path = os.path.join(
              dir_path, "hf_wordpiece_new_0.8.vocab"
          )
          download(
              url=get_repo_url()
              + "tokenizer_test_models/hf_wordpiece_new_0.8/hf_wordpiece.vocab",
              path=vocab_path,
              sha1_hash="dd6fdf4bbc74eaa8806d12cb3d38a4d9a306aea8",
          )
          tokenizer = HuggingFaceTokenizer(model_path, vocab_path)
          gt_tokenized = [
              [
                  "Hel",
                  "##lo",
                  ",",
                  "y",
                  "[UNK]",
                  "all",
                  "!",
                  "How",
                  "are",
                  "you",
                  "[UNK]",
                  "[UNK]",
                  "[UNK]",
                  "[UNK]",
                  "?",
              ],
              [
                  "Gl",
                  "##u",
                  "##on",
                  "##N",
                  "##L",
                  "##P",
                  "is",
                  "great",
                  "[UNK]",
                  "[UNK]",
                  "[UNK]",
                  "!",
                  "!",
                  "!",
              ],
              [
                  "Gl",
                  "##u",
                  "##on",
                  "##N",
                  "##L",
                  "##P",
                  "-",
                  "Am",
                  "##az",
                  "##on",
                  "-",
                  "Ha",
                  "##ibi",
                  "##n",
                  "-",
                  "Leon",
                  "##ard",
                  "-",
                  "She",
                  "##n",
                  "##g",
                  "-",
                  "Sh",
                  "##ua",
                  "##i",
                  "-",
                  "X",
                  "##ing",
                  "##j",
                  "##ian",
                  ".",
                  ".",
                  ".",
                  ".",
                  ".",
                  "/",
                  ":",
                  "!",
                  "@",
                  "#",
                  "[UNK]",
                  "ab",
                  "##c",
                  "[UNK]",
              ],
          ]
          gt_offsets = [
              [
                  (0, 3),
                  (3, 5),
                  (5, 6),
                  (7, 8),
                  (8, 9),
                  (9, 12),
                  (12, 13),
                  (14, 17),
                  (18, 21),
                  (22, 25),
                  (26, 27),
                  (28, 29),
                  (30, 31),
                  (32, 33),
                  (34, 35),
              ],
              [
                  (0, 2),
                  (2, 3),
                  (3, 5),
                  (5, 6),
                  (6, 7),
                  (7, 8),
                  (9, 11),
                  (12, 17),
                  (17, 18),
                  (18, 19),
                  (19, 20),
                  (20, 21),
                  (21, 22),
                  (22, 23),
              ],
              [
                  (0, 2),
                  (2, 3),
                  (3, 5),
                  (5, 6),
                  (6, 7),
                  (7, 8),
                  (8, 9),
                  (9, 11),
                  (11, 13),
                  (13, 15),
                  (15, 16),
                  (16, 18),
                  (18, 21),
                  (21, 22),
                  (22, 23),
                  (23, 27),
                  (27, 30),
                  (30, 31),
                  (31, 34),
                  (34, 35),
                  (35, 36),
                  (36, 37),
                  (37, 39),
                  (39, 41),
                  (41, 42),
                  (42, 43),
                  (43, 44),
                  (44, 47),
                  (47, 48),
                  (48, 51),
                  (51, 52),
                  (52, 53),
                  (53, 54),
                  (54, 55),
                  (55, 56),
                  (56, 57),
                  (57, 58),
                  (58, 59),
                  (59, 60),
                  (60, 61),
                  (62, 63),
                  (63, 65),
                  (65, 66),
                  (66, 67),
              ],
          ]
          gt_decode = [
              "Hello, y all! How are you?",
              "GluonNLP is great!!!",
              "GluonNLP - Amazon - Haibin - Leonard - Sheng - Shuai - Xingjian..... / "
              ":! @ # abc",
          ]
          verify_encode_token(
              tokenizer, SUBWORD_TEST_SAMPLES, gt_tokenized
          )
          verify_pickleble(tokenizer, HuggingFaceTokenizer)
          verify_encode_token_with_offsets(
              tokenizer, SUBWORD_TEST_SAMPLES, gt_offsets
          )
          verify_decode_hf(tokenizer, SUBWORD_TEST_SAMPLES, gt_decode)
  
imports: import pytest
  import random
  import collections
  import pickle
  from uuid import uuid4
  import os
  import unicodedata
  import tempfile
  from pkg_resources import parse_version
  import gluonnlp
  from gluonnlp.data.tokenizers import WhitespaceTokenizer, MosesTokenizer, JiebaTokenizer, SpacyTokenizer, SubwordNMTTokenizer, YTTMTokenizer, SentencepieceTokenizer, HuggingFaceBPETokenizer, HuggingFaceByteBPETokenizer, HuggingFaceWordPieceTokenizer, HuggingFaceTokenizer
  from gluonnlp.base import get_repo_url
  from gluonnlp.data import Vocab, load_vocab
  from gluonnlp.utils.misc import download
  from gluonnlp.models.t5 import T5Tokenizer
label_desc: Use image node_id 22 for calling a global function with example usage: test_huggingface_wordpiece_tokenizer_v08() without return types