Add NFC and NFD normalization options (keeping NFKC as the default) #313
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
While NFKC is kept as the default, this gives the option to use NFC and NFD normalization options. These can't be used directly, but allow a model that has been trained with an alternative normalization to be loaded and used. Without this patch, such a model will throw an error when unpickling such a model. Such a model can be built using different normalization= parameters, as for example in PR#257.
kba
approved these changes
Aug 31, 2018
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
I'm proposing this as NFC/NFD normalization is definitely useful
for some models, and this allows users to load models which use
one of these normalizations. #257 (the proposal to use NFC by
default) didn't get enough traction to merge, but this at least allows
those of us who benefit from alternative normalization to distribute
our models to users, without having to ask them to apply a patch.
While NFKC is kept as the default, this gives the option to use NFC
and NFD normalization options. These can't be used directly, but
allow a model that has been trained with an alternative
normalization to be loaded and used. Without this patch, such a
model will throw an error when unpickling such a model.
Such a model can be built using different normalization= parameters,
as for example in #257.