fix both failing RoCBert tests (#20469)
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@@ -710,4 +710,4 @@ class RoCBertModelIntegrationTest(unittest.TestCase):
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# convert to tokens is: ['[CLS]', '巴', '*', '黎', '是', '法', '国', '的', '首', '都', '[SEP]']
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# convert to tokens is: ['[CLS]', '巴', '*', '黎', '是', '法', '国', '的', '首', '都', '[SEP]']
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expected_output = torch.tensor([[101, 2349, 115, 7944, 3221, 3791, 1744, 4638, 7674, 6963, 102]])
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expected_output = torch.tensor([[101, 2349, 115, 7944, 3221, 3791, 1744, 4638, 7674, 6963, 102]])
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self.assertEqual(output_ids, expected_output)
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assert torch.allclose(output_ids, expected_output)
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@@ -299,8 +299,8 @@ class BertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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encoded_sentence = tokenizer.build_inputs_with_special_tokens(text)
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encoded_sentence = tokenizer.build_inputs_with_special_tokens(text)
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encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
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encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
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assert encoded_sentence == [101] + text + [102]
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assert encoded_sentence == [1] + text + [2]
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assert encoded_pair == [101] + text + [102] + text_2 + [102]
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assert encoded_pair == [1] + text + [2] + text_2 + [2]
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def test_prepare_for_model(self):
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def test_prepare_for_model(self):
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tokenizers = self.get_tokenizers(do_lower_case=False)
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tokenizers = self.get_tokenizers(do_lower_case=False)
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