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This commit is contained in:
56
tests/models/albert/test_tokenization_albert.py
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56
tests/models/albert/test_tokenization_albert.py
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# Copyright 2019 Hugging Face inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from transformers import AlbertTokenizer
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from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers
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from transformers.tokenization_utils_sentencepiece import SentencePieceExtractor
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from ...test_tokenization_common import TokenizerTesterMixin
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SAMPLE_VOCAB = get_tests_dir("fixtures/spiece.model")
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@require_sentencepiece
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@require_tokenizers
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class AlbertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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from_pretrained_id = "albert/albert-base-v1"
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tokenizer_class = AlbertTokenizer
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# Integration test data - expected outputs for the default input string
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integration_expected_tokens = ['▁this', '▁is', '▁a', '▁test', '▁', '😊', '▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁false', '.', '▁', '生活的真谛是', '▁hi', '▁hello', '▁hi', '▁hello', '▁hello', '▁', '<', 's', '>', '▁hi', '<', 's', '>', 'there', '▁the', '▁following', '▁string', '▁should', '▁be', '▁properly', '▁encoded', ':', '▁hello', '.', '▁but', '▁i', 'rd', '▁and', '▁', 'ป', '▁i', 'rd', '▁', 'ด', '▁hey', '▁how', '▁are', '▁you', '▁doing'] # fmt: skip
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integration_expected_token_ids = [48, 25, 21, 1289, 13, 1, 31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 4997, 9, 13, 1, 4148, 10975, 4148, 10975, 10975, 13, 1, 18, 1, 4148, 1, 18, 1, 1887, 14, 249, 3724, 378, 44, 7428, 13665, 45, 10975, 9, 47, 31, 897, 17, 13, 1, 31, 897, 13, 1, 8409, 184, 50, 42, 845] # fmt: skip
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integration_expected_decoded_text = "this is a test <unk> i was born in 92000, and this is false. <unk> hi hello hi hello hello <unk>s<unk> hi<unk>s<unk>there the following string should be properly encoded: hello. but ird and <unk> ird <unk> hey how are you doing"
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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from_pretrained_id = "albert/albert-base-v1"
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tokenizer = AlbertTokenizer.from_pretrained(from_pretrained_id)
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tokenizer.pad_token = tokenizer.eos_token
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tokenizer.save_pretrained(cls.tmpdirname)
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# Build backend for slow tokenizer from the fast tokenizer's SentencePiece model
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vocab_file = getattr(tokenizer, "vocab_file", None)
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extractor = SentencePieceExtractor(vocab_file)
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vocab_ids, vocab_scores, merges = extractor.extract()
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tokenizer_from_vocab = AlbertTokenizer(vocab=vocab_scores, merges=merges)
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tokenizer_from_vocab.pad_token = tokenizer_from_vocab.eos_token
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cls.tokenizers = [tokenizer, tokenizer_from_vocab]
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