36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
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 = get_tests_dir("fixtures/test_sentencepiece.model")
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spm_model_file_with_bytefallback = 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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"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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str(w[0].message),
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)
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