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use tok as fallback tokenizer #11

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use tok as fallback tokenizer #11

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5 changes: 3 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -27,8 +27,9 @@ encoder.fit(test_corpus.split('\n'))
example = "Vizzini: He didn't fall? INCONCEIVABLE!"
print(encoder.tokenize(example))
# ['__sow', 'vi', 'z', 'zi', 'ni', '__eow', '__sow', ':', '__eow', 'he', 'didn', "'", 't', 'fall', '__sow', '?', '__eow', '__sow', 'in', 'co', 'n', 'ce', 'iv', 'ab', 'le', '__eow', '__sow', '!', '__eow']
# ['__sow', 'vi', 'z', 'zi', 'ni', '__eow', '__sow', ':', '__eow', 'he', 'did', 'not', 'fall', '__sow', '?', '__eow', '__sow', 'in', 'co', 'n', 'ce', 'iv', 'ab', 'le', '__eow', '__sow', '!', '__eow']
print(next(encoder.transform([example])))
# [26, 108, 79, 104, 72, 24, 26, 117, 24, 9, 11, 8, 12, 10, 26, 90, 24, 26, 154, 56, 37, 149, 80, 169, 84, 24, 26, 156, 24]
# [25, 102, 76, 77, 68, 24, 25, 149, 24, 13, 10, 11, 12, 25, 79, 24, 25, 135, 58, 37, 152, 81, 160, 108, 24, 25, 143, 24]
print(next(encoder.inverse_transform(encoder.transform([example]))))
# vizzini : he didn ' t fall ? inconceivable !
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@soaxelbrooke soaxelbrooke Jul 10, 2019

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So using tok would change the default tokenization?

# vizzini : he did not fall ? inconceivable !
```
4 changes: 2 additions & 2 deletions bpe/encoder.py
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Expand Up @@ -7,7 +7,7 @@
except ImportError:
pass

from nltk.tokenize import wordpunct_tokenize
from tok import word_tokenize
from tqdm import tqdm
import toolz
import json
Expand Down Expand Up @@ -39,7 +39,7 @@ def __init__(self, vocab_size=8192, pct_bpe=0.2, word_tokenizer=None,
self.pct_bpe = pct_bpe
self.word_vocab_size = max([int(vocab_size * (1 - pct_bpe)), len(self.required_tokens or [])])
self.bpe_vocab_size = vocab_size - self.word_vocab_size
self.word_tokenizer = word_tokenizer if word_tokenizer is not None else wordpunct_tokenize
self.word_tokenizer = word_tokenizer if word_tokenizer is not None else word_tokenize
self.custom_tokenizer = word_tokenizer is not None
self.word_vocab = {} # type: Dict[str, int]
self.bpe_vocab = {} # type: Dict[str, int]
Expand Down
4 changes: 2 additions & 2 deletions requirements.txt
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@@ -1,6 +1,6 @@
nltk
tok
tqdm
pytest
hypothesis
toolz
mypy
mypy