make check failed if I rewrite the unk value about sentencepiece HOT 6 CLOSED

Is that an only test-case problem or it needs more effort?

from sentencepiece.

BOS/EOS/UNK ids are hard coded. Not sure what happens when rewriting these variables.

By the way, If you want to reserve some ids, you can train sentencepiece with --contol_symbols flag
https://github.com/google/sentencepiece/blob/master/doc/special_symbols.md
--control_symbols="<my_tag1>,<my_tag2>"

then, "<my_tag1>" and "<my_tag2>" are reserved. These vocab must be inserted outside of sentencepiece. The id of these symbols can be found in vocab file.

from sentencepiece.

Thanks for the advice. However, I'd like to reserve symbol IDs, but not names....

from sentencepiece.

Here's my fork with (bos=0, eos=1, unk=2) for who is interested in this; https://github.com/deasuke/sentencepiece

A lot of sequence processing system use pad=0 and eos=1 and has no bos; e.g. tf.reduce_sum(some_position_slice)==0 means every word in the position is PAD and tf.less(some_position_slice, 2) means "choose finished sequences"

BTW, I have a question: I have to rewrite the test case of "我輩は猫である" (see unigram_trainer_test.cc of the change deasuke@4a9f041 )
Is the algorithm dependent on (the order of) word ID ?

from sentencepiece.

This feature may be hard to implement because some IDs are hard-coded but it will be helpful when using SentencPiece with Tensor2Tensor because it uses some ids (0 and 1) for special purposes. I imagine there are other cases when downstream programs reserves some ids whose meanings are different from SentencePiece.

from sentencepiece.

Updated the code such that ids for are redefined.

% spm_train --bos_id=0 --eos_id=1 --unk_id=2 ....

Also id for padding is added, though it is disabled by default. Will update the document soon.

d102897

from sentencepiece.