Setters that take a different type than what the getter returns are still
problematic for MyPy. Replace the setter by a method, so that type inference
works everywhere.
This change adds the new `activations` attribute to `Doc`. This
attribute can be used by trainable pipes to store their activations,
probabilities, and guesses for downstream users.
As an example, this change modifies the `tagger` and `senter` pipes to
add an `store_activations` option. When this option is enabled, the
probabilities and guesses are stored in `set_annotations`.
* 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
* Fix Scorer.score_cats for missing labels
* Add test case for Scorer.score_cats missing labels
* semantic nitpick
* black formatting
* adjust test to give different results depending on multi_label setting
* fix loss function according to whether or not missing values are supported
* add note to docs
* small fixes
* make mypy happy
* Update spacy/pipeline/textcat.py
Co-authored-by: Florian Cäsar <florian.caesar@pm.me>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: svlandeg <svlandeg@github.com>
* Add overwrite settings for more components
For pipeline components where it's relevant and not already implemented,
add an explicit `overwrite` setting that controls whether
`set_annotations` overwrites existing annotation.
For the `morphologizer`, add an additional setting `extend`, which
controls whether the existing features are preserved.
* +overwrite, +extend: overwrite values of existing features, add any new
features
* +overwrite, -extend: overwrite completely, removing any existing
features
* -overwrite, +extend: keep values of existing features, add any new
features
* -overwrite, -extend: do not modify the existing value if set
In all cases an unset value will be set by `set_annotations`.
Preserve current overwrite defaults:
* True: morphologizer, entity linker
* False: tagger, sentencizer, senter
* Add backwards compat overwrite settings
* Put empty line back
Removed by accident in last commit
* Set backwards-compatible defaults in __init__
Because the `TrainablePipe` serialization methods update `cfg`, there's
no straightforward way to detect whether models serialized with a
previous version are missing the overwrite settings.
It would be possible in the sentencizer due to its separate
serialization methods, however to keep the changes parallel, this also
sets the default in `__init__`.
* Remove traces
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
* Add scorer option to components
Add an optional `scorer` parameter to all pipeline components. If a
scoring function is provided, it overrides the default scoring method
for that component.
* Add registered scorers for all components
* Add `scorers` registry
* Move all scoring methods outside of components as independent
functions and register
* Use the registered scoring methods as defaults in configs and inits
Additional:
* The scoring methods no longer have access to the full component, so
use settings from `cfg` as default scorer options to handle settings
such as `labels`, `threshold`, and `positive_label`
* The `attribute_ruler` scoring method no longer has access to the
patterns, so all scoring methods are called
* Bug fix: `spancat` scoring method is updated to set `allow_overlap` to
score overlapping spans correctly
* Update Russian lemmatizer to use direct score method
* Check type of cfg in Pipe.score
* Fix check
* Update spacy/pipeline/sentencizer.pyx
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Remove validate_examples from scoring functions
* Use Pipe.labels instead of Pipe.cfg["labels"]
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Replace negative rows with 0 in StaticVectors
Replace negative row indices with 0-vectors in `StaticVectors`.
* Increase versions related to StaticVectors
* Increase versions of all architctures and layers related to
`StaticVectors`
* Improve efficiency of 0-vector operations
Parallel `spacy-legacy` PR: https://github.com/explosion/spacy-legacy/pull/5
* Update config defaults to new versions
* Update docs
* Add util method for check
* Add new languages to list with lexeme norm tables
* Add check to all relevant components
* Add config details to warning message
Note that we're not actually inspecting the model config to see if
`NORM` is used as an attribute, so it may warn in cases where it's not
relevant.
* Handle missing reference values in scorer
Handle missing values in reference doc during scoring where it is
possible to detect an unset state for the attribute. If no reference
docs contain annotation, `None` is returned instead of a score. `spacy
evaluate` displays `-` for missing scores and the missing scores are
saved as `None`/`null` in the metrics.
Attributes without unset states:
* `token.head`: relies on `token.dep` to recognize unset values
* `doc.cats`: unable to handle missing annotation
Additional changes:
* add optional `has_annotation` check to `score_scans` to replace
`doc.sents` hack
* update `score_token_attr_per_feat` to handle missing and empty morph
representations
* fix bug in `Doc.has_annotation` for normalization of `IS_SENT_START`
vs. `SENT_START`
* Fix import
* Update return types
* rename Pipe to TrainablePipe
* split functionality between Pipe and TrainablePipe
* remove unnecessary methods from certain components
* cleanup
* hasattr(component, "pipe") should be sufficient again
* remove serialization and vocab/cfg from Pipe
* unify _ensure_examples and validate_examples
* small fixes
* hasattr checks for self.cfg and self.vocab
* make is_resizable and is_trainable properties
* serialize strings.json instead of vocab
* fix KB IO + tests
* fix typos
* more typos
* _added_strings as a set
* few more tests specifically for _added_strings field
* bump to 3.0.0a36
* ensure Language passes on valid examples for initialization
* fix tagger model initialization
* check for valid get_examples across components
* assume labels were added before begin_training
* fix senter initialization
* fix morphologizer initialization
* use methods to check arguments
* test textcat init, requires thinc>=8.0.0a31
* fix tok2vec init
* fix entity linker init
* use islice
* fix simple NER
* cleanup debug model
* fix assert statements
* fix tests
* throw error when adding a label if the output layer can't be resized anymore
* fix test
* add failing test for simple_ner
* UX improvements
* morphologizer UX
* assume begin_training gets a representative set and processes the labels
* remove assumptions for output of untrained NER model
* restore test for original purpose
* consistently use upper-case IDS in token_annotation format and for get_aligned
* remove ID from to_dict (not used in from_dict either)
* fix test
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* moving syntax folder to _parser_internals
* moving nn_parser and transition_system
* move nn_parser and transition_system out of internals folder
* moving nn_parser code into transition_system file
* rename transition_system to transition_parser
* moving parser_model and _state to ml
* move _state back to internals
* The Parser now inherits from Pipe!
* small code fixes
* removing unnecessary imports
* remove link_vectors_to_models
* transition_system to internals folder
* little bit more cleanup
* newlines
