Spaces:
Paused
Paused
| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Team. All rights reserved. | |
| # | |
| # 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 BigBirdTokenizer, BigBirdTokenizerFast | |
| from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow | |
| from transformers.utils import cached_property | |
| from ...test_tokenization_common import TokenizerTesterMixin | |
| SPIECE_UNDERLINE = "▁" | |
| SAMPLE_VOCAB = get_tests_dir("fixtures/test_sentencepiece.model") | |
| class BigBirdTokenizationTest(TokenizerTesterMixin, unittest.TestCase): | |
| tokenizer_class = BigBirdTokenizer | |
| rust_tokenizer_class = BigBirdTokenizerFast | |
| test_rust_tokenizer = True | |
| test_sentencepiece = True | |
| def setUp(self): | |
| super().setUp() | |
| tokenizer = self.tokenizer_class(SAMPLE_VOCAB, keep_accents=True) | |
| tokenizer.save_pretrained(self.tmpdirname) | |
| def test_convert_token_and_id(self): | |
| """Test ``_convert_token_to_id`` and ``_convert_id_to_token``.""" | |
| token = "<s>" | |
| 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], "<unk>") | |
| self.assertEqual(vocab_keys[1], "<s>") | |
| 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_000) | |
| 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_full_tokenizer(self): | |
| tokenizer = BigBirdTokenizer(SAMPLE_VOCAB, keep_accents=True) | |
| tokens = tokenizer.tokenize("This is a test") | |
| self.assertListEqual(tokens, ["▁This", "▁is", "▁a", "▁t", "est"]) | |
| self.assertListEqual( | |
| tokenizer.convert_tokens_to_ids(tokens), | |
| [285, 46, 10, 170, 382], | |
| ) | |
| tokens = tokenizer.tokenize("I was born in 92000, and this is falsé.") | |
| self.assertListEqual( | |
| tokens, | |
| [ | |
| SPIECE_UNDERLINE + "I", | |
| SPIECE_UNDERLINE + "was", | |
| SPIECE_UNDERLINE + "b", | |
| "or", | |
| "n", | |
| SPIECE_UNDERLINE + "in", | |
| SPIECE_UNDERLINE + "", | |
| "9", | |
| "2", | |
| "0", | |
| "0", | |
| "0", | |
| ",", | |
| SPIECE_UNDERLINE + "and", | |
| SPIECE_UNDERLINE + "this", | |
| SPIECE_UNDERLINE + "is", | |
| SPIECE_UNDERLINE + "f", | |
| "al", | |
| "s", | |
| "é", | |
| ".", | |
| ], | |
| ) | |
| ids = tokenizer.convert_tokens_to_ids(tokens) | |
| self.assertListEqual( | |
| ids, | |
| [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4], | |
| ) | |
| back_tokens = tokenizer.convert_ids_to_tokens(ids) | |
| self.assertListEqual( | |
| back_tokens, | |
| [ | |
| SPIECE_UNDERLINE + "I", | |
| SPIECE_UNDERLINE + "was", | |
| SPIECE_UNDERLINE + "b", | |
| "or", | |
| "n", | |
| SPIECE_UNDERLINE + "in", | |
| SPIECE_UNDERLINE + "", | |
| "<unk>", | |
| "2", | |
| "0", | |
| "0", | |
| "0", | |
| ",", | |
| SPIECE_UNDERLINE + "and", | |
| SPIECE_UNDERLINE + "this", | |
| SPIECE_UNDERLINE + "is", | |
| SPIECE_UNDERLINE + "f", | |
| "al", | |
| "s", | |
| "<unk>", | |
| ".", | |
| ], | |
| ) | |
| def big_tokenizer(self): | |
| return BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base") | |
| def test_tokenization_base_easy_symbols(self): | |
| symbols = "Hello World!" | |
| original_tokenizer_encodings = [65, 18536, 2260, 101, 66] | |
| self.assertListEqual(original_tokenizer_encodings, self.big_tokenizer.encode(symbols)) | |
| def test_tokenization_base_hard_symbols(self): | |
| symbols = ( | |
| 'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will' | |
| " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth" | |
| ) | |
| # fmt: off | |
| original_tokenizer_encodings = [65, 871, 419, 358, 946, 991, 2521, 452, 358, 1357, 387, 7751, 3536, 112, 985, 456, 126, 865, 938, 5400, 5734, 458, 1368, 467, 786, 2462, 5246, 1159, 633, 865, 4519, 457, 582, 852, 2557, 427, 916, 508, 405, 34324, 497, 391, 408, 11342, 1244, 385, 100, 938, 985, 456, 574, 362, 12597, 3200, 3129, 1172, 66] # noqa: E231 | |
| # fmt: on | |
| self.assertListEqual(original_tokenizer_encodings, self.big_tokenizer.encode(symbols)) | |
| def test_torch_encode_plus_sent_to_model(self): | |
| import torch | |
| from transformers import BigBirdConfig, BigBirdModel | |
| # Build sequence | |
| first_ten_tokens = list(self.big_tokenizer.get_vocab().keys())[:10] | |
| sequence = " ".join(first_ten_tokens) | |
| encoded_sequence = self.big_tokenizer.encode_plus(sequence, return_tensors="pt", return_token_type_ids=False) | |
| batch_encoded_sequence = self.big_tokenizer.batch_encode_plus( | |
| [sequence + " " + sequence], return_tensors="pt", return_token_type_ids=False | |
| ) | |
| config = BigBirdConfig(attention_type="original_full") | |
| model = BigBirdModel(config) | |
| assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size | |
| with torch.no_grad(): | |
| model(**encoded_sequence) | |
| model(**batch_encoded_sequence) | |
| def test_special_tokens(self): | |
| """ | |
| To reproduce: | |
| $ wget https://github.com/google-research/bigbird/blob/master/bigbird/vocab/gpt2.model?raw=true | |
| $ mv gpt2.model?raw=true gpt2.model | |
| ``` | |
| import tensorflow_text as tft | |
| import tensorflow as tf | |
| vocab_model_file = "./gpt2.model" | |
| tokenizer = tft.SentencepieceTokenizer(model=tf.io.gfile.GFile(vocab_model_file, "rb").read())) | |
| ids = tokenizer.tokenize("Paris is the [MASK].") | |
| ids = tf.concat([tf.constant([65]), ids, tf.constant([66])], axis=0) | |
| detokenized = tokenizer.detokenize(ids) # should give [CLS] Paris is the [MASK].[SEP] | |
| """ | |
| tokenizer = BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base") | |
| decoded_text = tokenizer.decode(tokenizer("Paris is the [MASK].").input_ids) | |
| self.assertTrue(decoded_text == "[CLS] Paris is the[MASK].[SEP]") | |
| def test_tokenizer_integration(self): | |
| # fmt: off | |
| expected_encoding = {'input_ids': [[65, 39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114, 66], [65, 448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '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, 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, 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, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]} # noqa: E501 | |
| # fmt: on | |
| self.tokenizer_integration_test_util( | |
| expected_encoding=expected_encoding, | |
| model_name="google/bigbird-roberta-base", | |
| revision="215c99f1600e06f83acce68422f2035b2b5c3510", | |
| ) | |