spaCy/spacy/tests/training
Daniël de Kok e5debc68e4
Tagger: use unnormalized probabilities for inference (#10197)
* Tagger: use unnormalized probabilities for inference

Using unnormalized softmax avoids use of the relatively expensive exp function,
which can significantly speed up non-transformer models (e.g. I got a speedup
of 27% on a German tagging + parsing pipeline).

* Add spacy.Tagger.v2 with configurable normalization

Normalization of probabilities is disabled by default to improve
performance.

* Update documentation, models, and tests to spacy.Tagger.v2

* Move Tagger.v1 to spacy-legacy

* docs/architectures: run prettier

* Unnormalized softmax is now a Softmax_v2 option

* Require thinc 8.0.14 and spacy-legacy 3.0.9
2022-03-15 14:15:31 +01:00
..
__init__.py move tests to correct subdir 2020-09-15 21:40:38 +02:00
test_augmenters.py Add whitespace and combined augmenters (#10170) 2022-02-17 15:54:09 +01:00
test_new_example.py Allow Example to align whitespace annotation (#10189) 2022-02-03 17:01:53 +01:00
test_pretraining.py Tagger: use unnormalized probabilities for inference (#10197) 2022-03-15 14:15:31 +01:00
test_readers.py Address random results in slow readers tests (#9544) 2021-10-26 16:53:10 +02:00
test_rehearse.py Auto-format code with black (#10377) 2022-02-25 10:00:21 +01:00
test_training.py Tagger: use unnormalized probabilities for inference (#10197) 2022-03-15 14:15:31 +01:00