Spaces:
Runtime error
Runtime error
| # coding=utf-8 | |
| # Copyright 2018 HuggingFace Inc. team. | |
| # | |
| # 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 unittest | |
| from transformers import CamembertTokenizer, CamembertTokenizerFast | |
| from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow | |
| from transformers.utils import is_torch_available | |
| from ...test_tokenization_common import TokenizerTesterMixin | |
| SAMPLE_VOCAB = get_tests_dir("fixtures/test_sentencepiece.model") | |
| SAMPLE_BPE_VOCAB = get_tests_dir("fixtures/test_sentencepiece_bpe.model") | |
| FRAMEWORK = "pt" if is_torch_available() else "tf" | |
| class CamembertTokenizationTest(TokenizerTesterMixin, unittest.TestCase): | |
| tokenizer_class = CamembertTokenizer | |
| rust_tokenizer_class = CamembertTokenizerFast | |
| test_rust_tokenizer = True | |
| test_sentencepiece = True | |
| def setUp(self): | |
| super().setUp() | |
| # We have a SentencePiece fixture for testing | |
| tokenizer = CamembertTokenizer(SAMPLE_VOCAB) | |
| tokenizer.save_pretrained(self.tmpdirname) | |
| def test_convert_token_and_id(self): | |
| """Test ``_convert_token_to_id`` and ``_convert_id_to_token``.""" | |
| token = "<pad>" | |
| token_id = 1 | |
| self.assertEqual(self.get_tokenizer()._convert_token_to_id(token), token_id) | |
| self.assertEqual(self.get_tokenizer()._convert_id_to_token(token_id), token) | |
| def test_get_vocab(self): | |
| vocab_keys = list(self.get_tokenizer().get_vocab().keys()) | |
| self.assertEqual(vocab_keys[0], "<s>NOTUSED") | |
| self.assertEqual(vocab_keys[1], "<pad>") | |
| self.assertEqual(vocab_keys[-1], "<mask>") | |
| self.assertEqual(len(vocab_keys), 1_004) | |
| def test_vocab_size(self): | |
| self.assertEqual(self.get_tokenizer().vocab_size, 1_005) | |
| def test_rust_and_python_bpe_tokenizers(self): | |
| tokenizer = CamembertTokenizer(SAMPLE_BPE_VOCAB) | |
| tokenizer.save_pretrained(self.tmpdirname) | |
| rust_tokenizer = CamembertTokenizerFast.from_pretrained(self.tmpdirname) | |
| sequence = "I was born in 92000, and this is falsé." | |
| ids = tokenizer.encode(sequence) | |
| rust_ids = rust_tokenizer.encode(sequence) | |
| self.assertListEqual(ids, rust_ids) | |
| ids = tokenizer.encode(sequence, add_special_tokens=False) | |
| rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False) | |
| self.assertListEqual(ids, rust_ids) | |
| # <unk> tokens are not the same for `rust` than for `slow`. | |
| # Because spm gives back raw token instead of `unk` in EncodeAsPieces | |
| # tokens = tokenizer.tokenize(sequence) | |
| tokens = tokenizer.convert_ids_to_tokens(ids) | |
| rust_tokens = rust_tokenizer.tokenize(sequence) | |
| self.assertListEqual(tokens, rust_tokens) | |
| def test_rust_and_python_full_tokenizers(self): | |
| if not self.test_rust_tokenizer: | |
| return | |
| tokenizer = self.get_tokenizer() | |
| rust_tokenizer = self.get_rust_tokenizer() | |
| sequence = "I was born in 92000, and this is falsé." | |
| tokens = tokenizer.tokenize(sequence) | |
| rust_tokens = rust_tokenizer.tokenize(sequence) | |
| self.assertListEqual(tokens, rust_tokens) | |
| ids = tokenizer.encode(sequence, add_special_tokens=False) | |
| rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False) | |
| self.assertListEqual(ids, rust_ids) | |
| rust_tokenizer = self.get_rust_tokenizer() | |
| ids = tokenizer.encode(sequence) | |
| rust_ids = rust_tokenizer.encode(sequence) | |
| self.assertListEqual(ids, rust_ids) | |
| def test_tokenizer_integration(self): | |
| # fmt: off | |
| expected_encoding = {'input_ids': [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 27575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9088, 20, 1517, 8, 22804, 18818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 10326, 24, 2267, 20, 416, 5072, 15612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 8, 930, 9, 6]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]} # noqa: E501 | |
| # fmt: on | |
| # camembert is a french model. So we also use french texts. | |
| sequences = [ | |
| "Le transformeur est un modèle d'apprentissage profond introduit en 2017, " | |
| "utilisé principalement dans le domaine du traitement automatique des langues (TAL).", | |
| "À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus " | |
| "pour gérer des données séquentielles, telles que le langage naturel, pour des tâches " | |
| "telles que la traduction et la synthèse de texte.", | |
| ] | |
| self.tokenizer_integration_test_util( | |
| expected_encoding=expected_encoding, | |
| model_name="camembert-base", | |
| revision="3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf", | |
| sequences=sequences, | |
| ) | |