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* 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 |
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| .. | ||
| __init__.py | ||
| test_analysis.py | ||
| test_annotates_on_update.py | ||
| test_attributeruler.py | ||
| test_entity_linker.py | ||
| test_entity_ruler.py | ||
| test_functions.py | ||
| test_initialize.py | ||
| test_lemmatizer.py | ||
| test_models.py | ||
| test_morphologizer.py | ||
| test_pipe_factories.py | ||
| test_pipe_methods.py | ||
| test_sentencizer.py | ||
| test_senter.py | ||
| test_spancat.py | ||
| test_tagger.py | ||
| test_textcat.py | ||
| test_tok2vec.py | ||