Use lru_cache for tokenization tests (#36818)
* fix * fix * fix * fix --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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@@ -30,8 +30,9 @@ class FlaubertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = FlaubertTokenizer
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test_rust_tokenizer = False
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def setUp(self):
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super().setUp()
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
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vocab = ["l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "w</w>", "r</w>", "t</w>", "i</w>", "lo", "low", "ne", "new", "er</w>", "low</w>", "lowest</w>", "new</w>", "newer</w>", "wider</w>", "<unk>"] # fmt: skip
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@@ -39,11 +40,11 @@ class FlaubertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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vocab_tokens = dict(zip(vocab, range(len(vocab))))
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merges = ["n e 300", "ne w 301", "e r</w> 302", ""]
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self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
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self.merges_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["merges_file"])
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with open(self.vocab_file, "w", encoding="utf-8") as fp:
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cls.vocab_file = os.path.join(cls.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
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cls.merges_file = os.path.join(cls.tmpdirname, VOCAB_FILES_NAMES["merges_file"])
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with open(cls.vocab_file, "w", encoding="utf-8") as fp:
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fp.write(json.dumps(vocab_tokens) + "\n")
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with open(self.merges_file, "w", encoding="utf-8") as fp:
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with open(cls.merges_file, "w", encoding="utf-8") as fp:
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fp.write("\n".join(merges))
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# Copied from transformers.tests.models.xlm.test_tokenization_xlm.XLMTokenizationTest.test_full_tokenizer
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