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| # coding=utf-8 | |
| # Copyright 2019 HuggingFace Inc. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import os | |
| import sys | |
| import tempfile | |
| import unittest | |
| import unittest.mock as mock | |
| from pathlib import Path | |
| from huggingface_hub import HfFolder, delete_repo | |
| from huggingface_hub.file_download import http_get | |
| from requests.exceptions import HTTPError | |
| from transformers import ( | |
| AlbertTokenizer, | |
| AutoTokenizer, | |
| BertTokenizer, | |
| BertTokenizerFast, | |
| GPT2TokenizerFast, | |
| is_tokenizers_available, | |
| ) | |
| from transformers.testing_utils import TOKEN, USER, is_staging_test, require_tokenizers | |
| from transformers.tokenization_utils import Trie | |
| sys.path.append(str(Path(__file__).parent.parent / "utils")) | |
| from test_module.custom_tokenization import CustomTokenizer # noqa E402 | |
| if is_tokenizers_available(): | |
| from test_module.custom_tokenization_fast import CustomTokenizerFast | |
| class TokenizerUtilTester(unittest.TestCase): | |
| def test_cached_files_are_used_when_internet_is_down(self): | |
| # A mock response for an HTTP head request to emulate server down | |
| response_mock = mock.Mock() | |
| response_mock.status_code = 500 | |
| response_mock.headers = {} | |
| response_mock.raise_for_status.side_effect = HTTPError | |
| response_mock.json.return_value = {} | |
| # Download this model to make sure it's in the cache. | |
| _ = BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert") | |
| # Under the mock environment we get a 500 error when trying to reach the tokenizer. | |
| with mock.patch("requests.Session.request", return_value=response_mock) as mock_head: | |
| _ = BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert") | |
| # This check we did call the fake head request | |
| mock_head.assert_called() | |
| def test_cached_files_are_used_when_internet_is_down_missing_files(self): | |
| # A mock response for an HTTP head request to emulate server down | |
| response_mock = mock.Mock() | |
| response_mock.status_code = 500 | |
| response_mock.headers = {} | |
| response_mock.raise_for_status.side_effect = HTTPError | |
| response_mock.json.return_value = {} | |
| # Download this model to make sure it's in the cache. | |
| _ = GPT2TokenizerFast.from_pretrained("gpt2") | |
| # Under the mock environment we get a 500 error when trying to reach the tokenizer. | |
| with mock.patch("requests.Session.request", return_value=response_mock) as mock_head: | |
| _ = GPT2TokenizerFast.from_pretrained("gpt2") | |
| # This check we did call the fake head request | |
| mock_head.assert_called() | |
| def test_legacy_load_from_one_file(self): | |
| # This test is for deprecated behavior and can be removed in v5 | |
| try: | |
| tmp_file = tempfile.mktemp() | |
| with open(tmp_file, "wb") as f: | |
| http_get("https://huggingface.co/albert-base-v1/resolve/main/spiece.model", f) | |
| _ = AlbertTokenizer.from_pretrained(tmp_file) | |
| finally: | |
| os.remove(tmp_file) | |
| # Supporting this legacy load introduced a weird bug where the tokenizer would load local files if they are in | |
| # the current folder and have the right name. | |
| if os.path.isfile("tokenizer.json"): | |
| # We skip the test if the user has a `tokenizer.json` in this folder to avoid deleting it. | |
| return | |
| try: | |
| with open("tokenizer.json", "wb") as f: | |
| http_get("https://huggingface.co/hf-internal-testing/tiny-random-bert/blob/main/tokenizer.json", f) | |
| tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2") | |
| # The tiny random BERT has a vocab size of 1024, tiny gpt2 as a vocab size of 1000 | |
| self.assertEqual(tokenizer.vocab_size, 1000) | |
| # Tokenizer should depend on the remote checkpoint, not the local tokenizer.json file. | |
| finally: | |
| os.remove("tokenizer.json") | |
| def test_legacy_load_from_url(self): | |
| # This test is for deprecated behavior and can be removed in v5 | |
| _ = AlbertTokenizer.from_pretrained("https://huggingface.co/albert-base-v1/resolve/main/spiece.model") | |
| class TokenizerPushToHubTester(unittest.TestCase): | |
| vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "bla", "blou"] | |
| def setUpClass(cls): | |
| cls._token = TOKEN | |
| HfFolder.save_token(TOKEN) | |
| def tearDownClass(cls): | |
| try: | |
| delete_repo(token=cls._token, repo_id="test-tokenizer") | |
| except HTTPError: | |
| pass | |
| try: | |
| delete_repo(token=cls._token, repo_id="valid_org/test-tokenizer-org") | |
| except HTTPError: | |
| pass | |
| try: | |
| delete_repo(token=cls._token, repo_id="test-dynamic-tokenizer") | |
| except HTTPError: | |
| pass | |
| def test_push_to_hub(self): | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| vocab_file = os.path.join(tmp_dir, "vocab.txt") | |
| with open(vocab_file, "w", encoding="utf-8") as vocab_writer: | |
| vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens])) | |
| tokenizer = BertTokenizer(vocab_file) | |
| tokenizer.push_to_hub("test-tokenizer", use_auth_token=self._token) | |
| new_tokenizer = BertTokenizer.from_pretrained(f"{USER}/test-tokenizer") | |
| self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab) | |
| # Reset repo | |
| delete_repo(token=self._token, repo_id="test-tokenizer") | |
| # Push to hub via save_pretrained | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| tokenizer.save_pretrained(tmp_dir, repo_id="test-tokenizer", push_to_hub=True, use_auth_token=self._token) | |
| new_tokenizer = BertTokenizer.from_pretrained(f"{USER}/test-tokenizer") | |
| self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab) | |
| def test_push_to_hub_in_organization(self): | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| vocab_file = os.path.join(tmp_dir, "vocab.txt") | |
| with open(vocab_file, "w", encoding="utf-8") as vocab_writer: | |
| vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens])) | |
| tokenizer = BertTokenizer(vocab_file) | |
| tokenizer.push_to_hub("valid_org/test-tokenizer-org", use_auth_token=self._token) | |
| new_tokenizer = BertTokenizer.from_pretrained("valid_org/test-tokenizer-org") | |
| self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab) | |
| # Reset repo | |
| delete_repo(token=self._token, repo_id="valid_org/test-tokenizer-org") | |
| # Push to hub via save_pretrained | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| tokenizer.save_pretrained( | |
| tmp_dir, repo_id="valid_org/test-tokenizer-org", push_to_hub=True, use_auth_token=self._token | |
| ) | |
| new_tokenizer = BertTokenizer.from_pretrained("valid_org/test-tokenizer-org") | |
| self.assertDictEqual(new_tokenizer.vocab, tokenizer.vocab) | |
| def test_push_to_hub_dynamic_tokenizer(self): | |
| CustomTokenizer.register_for_auto_class() | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| vocab_file = os.path.join(tmp_dir, "vocab.txt") | |
| with open(vocab_file, "w", encoding="utf-8") as vocab_writer: | |
| vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens])) | |
| tokenizer = CustomTokenizer(vocab_file) | |
| # No fast custom tokenizer | |
| tokenizer.push_to_hub("test-dynamic-tokenizer", use_auth_token=self._token) | |
| tokenizer = AutoTokenizer.from_pretrained(f"{USER}/test-dynamic-tokenizer", trust_remote_code=True) | |
| # Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module | |
| self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizer") | |
| # Fast and slow custom tokenizer | |
| CustomTokenizerFast.register_for_auto_class() | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| vocab_file = os.path.join(tmp_dir, "vocab.txt") | |
| with open(vocab_file, "w", encoding="utf-8") as vocab_writer: | |
| vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens])) | |
| bert_tokenizer = BertTokenizerFast.from_pretrained(tmp_dir) | |
| bert_tokenizer.save_pretrained(tmp_dir) | |
| tokenizer = CustomTokenizerFast.from_pretrained(tmp_dir) | |
| tokenizer.push_to_hub("test-dynamic-tokenizer", use_auth_token=self._token) | |
| tokenizer = AutoTokenizer.from_pretrained(f"{USER}/test-dynamic-tokenizer", trust_remote_code=True) | |
| # Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module | |
| self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizerFast") | |
| tokenizer = AutoTokenizer.from_pretrained( | |
| f"{USER}/test-dynamic-tokenizer", use_fast=False, trust_remote_code=True | |
| ) | |
| # Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module | |
| self.assertEqual(tokenizer.__class__.__name__, "CustomTokenizer") | |
| class TrieTest(unittest.TestCase): | |
| def test_trie(self): | |
| trie = Trie() | |
| trie.add("Hello 友達") | |
| self.assertEqual(trie.data, {"H": {"e": {"l": {"l": {"o": {" ": {"友": {"達": {"": 1}}}}}}}}}) | |
| trie.add("Hello") | |
| trie.data | |
| self.assertEqual(trie.data, {"H": {"e": {"l": {"l": {"o": {"": 1, " ": {"友": {"達": {"": 1}}}}}}}}}) | |
| def test_trie_split(self): | |
| trie = Trie() | |
| self.assertEqual(trie.split("[CLS] This is a extra_id_100"), ["[CLS] This is a extra_id_100"]) | |
| trie.add("[CLS]") | |
| trie.add("extra_id_1") | |
| trie.add("extra_id_100") | |
| self.assertEqual(trie.split("[CLS] This is a extra_id_100"), ["[CLS]", " This is a ", "extra_id_100"]) | |
| def test_trie_single(self): | |
| trie = Trie() | |
| trie.add("A") | |
| self.assertEqual(trie.split("ABC"), ["A", "BC"]) | |
| self.assertEqual(trie.split("BCA"), ["BC", "A"]) | |
| def test_trie_final(self): | |
| trie = Trie() | |
| trie.add("TOKEN]") | |
| trie.add("[SPECIAL_TOKEN]") | |
| self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"), ["This is something ", "[SPECIAL_TOKEN]"]) | |
| def test_trie_subtokens(self): | |
| trie = Trie() | |
| trie.add("A") | |
| trie.add("P") | |
| trie.add("[SPECIAL_TOKEN]") | |
| self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"), ["This is something ", "[SPECIAL_TOKEN]"]) | |
| def test_trie_suffix_tokens(self): | |
| trie = Trie() | |
| trie.add("AB") | |
| trie.add("B") | |
| trie.add("C") | |
| self.assertEqual(trie.split("ABC"), ["AB", "C"]) | |
| def test_trie_skip(self): | |
| trie = Trie() | |
| trie.add("ABC") | |
| trie.add("B") | |
| trie.add("CD") | |
| self.assertEqual(trie.split("ABCD"), ["ABC", "D"]) | |
| def test_cut_text_hardening(self): | |
| # Even if the offsets are wrong, we necessarily output correct string | |
| # parts. | |
| trie = Trie() | |
| parts = trie.cut_text("ABC", [0, 0, 2, 1, 2, 3]) | |
| self.assertEqual(parts, ["AB", "C"]) | |