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Copy object instead of passing the reference
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@ -326,7 +326,7 @@ class PreTrainedTokenizer(object):
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cls.pretrained_init_configuration
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and pretrained_model_name_or_path in cls.pretrained_init_configuration
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):
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init_configuration = cls.pretrained_init_configuration[pretrained_model_name_or_path]
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init_configuration = cls.pretrained_init_configuration[pretrained_model_name_or_path].copy()
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else:
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# Get the vocabulary from local files
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logger.info(
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@ -495,3 +495,16 @@ class TokenizerTesterMixin:
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assert [token_type_padding_idx] * padding_size + token_type_ids == padded_token_type_ids
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assert [0] * padding_size + attention_mask == padded_attention_mask
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assert [1] * padding_size + special_tokens_mask == padded_special_tokens_mask
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def test_separate_tokenizers(self):
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# This tests that tokenizers don't impact others. Unfortunately the case where it fails is when
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# we're loading an S3 configuration from a pre-trained identifier, and we have no way of testing those today.
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tokenizer = self.get_tokenizer(random_argument=True)
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print(tokenizer.init_kwargs)
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assert tokenizer.init_kwargs['random_argument'] is True
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new_tokenizer = self.get_tokenizer(random_argument=False)
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print(tokenizer.init_kwargs)
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print(new_tokenizer.init_kwargs)
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assert tokenizer.init_kwargs['random_argument'] is True
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assert new_tokenizer.init_kwargs['random_argument'] is False
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