* Move coref scoring code to scorer.py
Includes some renames to make names less generic.
* Refactor coval code to remove ternary expressions
* Black formatting
* Add header
* Make scorers into registered scorers
* Small test fixes
* Skip coref tests when torch not present
Coref can't be loaded without Torch, so nothing works.
* Fix remaining type issues
Some of this just involves ignoring types in thorny areas. Two main
issues:
1. Some things have weird types due to indirection/ argskwargs
2. xp2torch return type seems to have changed at some point
* Update spacy/scorer.py
Co-authored-by: kadarakos <kadar.akos@gmail.com>
* Small changes from review
* Be specific about the ValueError
* Type fix
Co-authored-by: kadarakos <kadar.akos@gmail.com>
* Make changes to typing
* Correction
* Format with black
* Corrections based on review
* Bumped Thinc dependency version
* Bumped blis requirement
* Correction for older Python versions
* Update spacy/ml/models/textcat.py
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
* Corrections based on review feedback
* Readd deleted docstring line
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
Torch is required for the coref/spanpred models but shouldn't be
required for spaCy in general.
The one tricky part of this is that one function in coref_util relied on
torch, but that file was imported in several places. Since the function
was only used in one place I moved it there.
* 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
The span predictor component is initialized but not used at all now.
Plan is to work on it after the word level clustering part is trainable
end-to-end.
This absolutely does not work. First step here is getting over most of
the code in roughly the files we want it in. After the code has been
pulled over it can be restructured to match spaCy and cleaned up.
