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Simplify unk token (#12582)

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* Base test

* More test

* Fix mistake

* Add a docstring change

* Add doc ignore

* Simplify logic for unk token in Unigram tokenizers

* Remove changes from otehr branch
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Sylvain Gugger 2021-07-09 09:02:34 -04:00 committed by GitHub
parent deecdd4939
commit 0cc2dc2456
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1 changed files with 2 additions and 11 deletions
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13
src/transformers/tokenization_utils_fast.py
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@ -662,22 +662,13 @@ class PreTrainedTokenizerFast(PreTrainedTokenizerBase):
and tokenizer_json["model"]["end_of_word_suffix"] is not None
):
kwargs["end_of_word_suffix"] = tokenizer_json["model"]["end_of_word_suffix"]
if tokenizer_json["model"]["type"] == "Unigram" and unk_token is not None:
kwargs["unk_token"] = unk_token
trainer_class = MODEL_TO_TRAINER_MAPPING[tokenizer_json["model"]["type"]]
trainer = trainer_class(vocab_size=vocab_size, special_tokens=special_tokens, **kwargs)
tokenizer.train_from_iterator(text_iterator, trainer=trainer)
if unk_token is not None:
# For Unigram tokenizers we need to set back the unk id of the model (bug in Tokenizers?)
trained_tokenizer_json = json.loads(tokenizer.to_str())
vocab = trained_tokenizer_json["model"]["vocab"]
unk_id = 0
while unk_id < len(vocab) and vocab[unk_id][0] != unk_token:
unk_id += 1
if unk_id < len(vocab):
trained_tokenizer_json["model"]["unk_id"] = unk_id
tokenizer = TokenizerFast.from_str(json.dumps(trained_tokenizer_json))
if post_processor is not None:
trained_tokenizer_json = json.loads(tokenizer.to_str())
# Almost done, we just have to adjust the token IDs in the post processor