add a warning in SpmConverter for sentencepiece's model using the byte fallback feature (#16629)
* update proto sentencepiece model * Revert "update proto sentencepiece model" This reverts commit b07f671747fec35773d0b3d4788b8b15aefa0229. * add check * add test * Revert "Revert "update proto sentencepiece model"" This reverts commit 46108257b8927b73627ec8f4f3eed53a95fc700d. * test for log level * test for log level 2 * warning at the warning level * clean * format * add explanation in docstring
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tests/fixtures/test_sentencepiece_with_bytefallback.model
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tests/fixtures/test_sentencepiece_with_bytefallback.model
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tests/utils/test_convert_slow_tokenizer.py
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tests/utils/test_convert_slow_tokenizer.py
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import unittest
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import warnings
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from dataclasses import dataclass
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from transformers.convert_slow_tokenizer import SpmConverter
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from transformers.testing_utils import get_tests_dir
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@dataclass
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class FakeOriginalTokenizer:
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vocab_file: str
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class ConvertSlowTokenizerTest(unittest.TestCase):
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def test_spm_converter_bytefallback_warning(self):
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spm_model_file_without_bytefallback = f"{get_tests_dir()}/fixtures/test_sentencepiece.model"
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spm_model_file_with_bytefallback = f"{get_tests_dir()}/fixtures/test_sentencepiece_with_bytefallback.model"
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original_tokenizer_without_bytefallback = FakeOriginalTokenizer(vocab_file=spm_model_file_without_bytefallback)
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with warnings.catch_warnings(record=True) as w:
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_ = SpmConverter(original_tokenizer_without_bytefallback)
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self.assertEqual(len(w), 0)
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original_tokenizer_with_bytefallback = FakeOriginalTokenizer(vocab_file=spm_model_file_with_bytefallback)
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with warnings.catch_warnings(record=True) as w:
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_ = SpmConverter(original_tokenizer_with_bytefallback)
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self.assertEqual(len(w), 1)
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self.assertIn(
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(
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"The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option"
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" which is not implemented in the fast tokenizers."
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),
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str(w[0].message),
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)
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