mirror of https://github.com/explosion/spaCy.git
e5debc68e4
* 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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| .. | ||
| models | ||
| __init__.py | ||
| _character_embed.py | ||
| _precomputable_affine.py | ||
| callbacks.py | ||
| extract_ngrams.py | ||
| extract_spans.py | ||
| featureextractor.py | ||
| parser_model.pxd | ||
| parser_model.pyx | ||
| staticvectors.py | ||
| tb_framework.py | ||