Commit Graph

21 Commits

Author SHA1 Message Date
Adriane Boyd
b278f31ee6
Document scorers in registry and components from #8766 (#8929)
* Document scorers in registry and components from #8766

* Update spacy/pipeline/lemmatizer.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update website/docs/api/dependencyparser.md

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Reformat

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2021-08-12 12:50:03 +02:00
Adriane Boyd
f99d6d5e39
Refactor scoring methods to use registered functions (#8766)
* 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>
2021-08-10 15:13:39 +02:00
Adriane Boyd
10c930cc96
Re-refactor Sentencizer with Pipe API (#7176)
Reapply the refactoring (#4721) so that `Sentencizer` uses the faster
`predict` and `set_annotations` for both `__call__` and `pipe`.
2021-02-26 09:48:14 +01:00
Ines Montani
d0c3775712 Replace links to nightly docs [ci skip] 2021-01-30 20:09:38 +11:00
Sofie Van Landeghem
837a4f53c2
Error handling in nlp.pipe (#6817)
* add error handler for pipe methods

* add unit tests

* remove pipe method that are the same as their base class

* have Language keep track of a default error handler

* cleanup

* formatting

* small refactor

* add documentation
2021-01-29 08:51:21 +08:00
Adriane Boyd
a4b32b9552
Handle missing reference values in scorer (#6286)
* 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
2020-11-03 15:47:18 +01:00
Sofie Van Landeghem
d093d6343b
TrainablePipe (#6213)
* 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
2020-10-08 21:33:49 +02:00
Ines Montani
f171903139 Clean up sgd and pipeline -> nlp 2020-09-29 12:20:26 +02:00
Ines Montani
42f0e4c946 Clean up 2020-09-29 12:14:08 +02:00
Ines Montani
ff9a63bfbd begin_training -> initialize 2020-09-28 21:35:09 +02:00
Ines Montani
ae51f580c1 Fix handling of score_weights 2020-09-24 10:27:33 +02:00
Sofie Van Landeghem
8e7557656f
Renaming gold & annotation_setter (#6042)
* version bump to 3.0.0a16

* rename "gold" folder to "training"

* rename 'annotation_setter' to 'set_extra_annotations'

* formatting
2020-09-09 10:31:03 +02:00
Ines Montani
ab1bb421ed Update docs links in codebase 2020-09-04 12:58:50 +02:00
Ines Montani
950832f087
Tidy up pipes (#5906)
* Tidy up pipes

* Fix init, defaults and raise custom errors

* Update docs

* Update docs [ci skip]

* Apply suggestions from code review

Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>

* Tidy up error handling and validation, fix consistency

* Simplify get_examples check

* Remove unused import [ci skip]

Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-08-11 23:29:31 +02:00
Sofie Van Landeghem
ca491722ad
The Parser is now a Pipe (2) (#5844)
* 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
2020-07-30 23:30:54 +02:00
Ines Montani
b0f57a0cac Update docs and consistency 2020-07-29 15:14:07 +02:00
Ines Montani
894e20c466 Merge branch 'develop' into feature/component-scores 2020-07-27 18:14:39 +02:00
Ines Montani
d8b519c23c API docs, docstrings and argument consistency 2020-07-27 18:11:45 +02:00
Adriane Boyd
8bb0507777 Add and update score methods and score weights
Add and update `score` methods, provided `scores`, and default weights
`default_score_weights` for pipeline components.

* `scores` provides all top-level keys returned by `score` (merely informative, similar to `assigns`).
* `default_score_weights` provides the default weights for a default config.
* The keys from `default_score_weights` determine which values will be
shown in the `spacy train` output, so keys with weight `0.0` will be
displayed but not counted toward the overall score.
2020-07-27 14:44:53 +02:00
Adriane Boyd
2bcceb80c4
Refactor the Scorer to improve flexibility (#5731)
* Refactor the Scorer to improve flexibility

Refactor the `Scorer` to improve flexibility for arbitrary pipeline
components.

* Individual pipeline components provide their own `evaluate` methods
that score a list of `Example`s and return a dictionary of scores
* `Scorer` is initialized either:
  * with a provided pipeline containing components to be scored
  * with a default pipeline containing the built-in statistical
    components (senter, tagger, morphologizer, parser, ner)
* `Scorer.score` evaluates a list of `Example`s and returns a dictionary
of scores referring to the scores provided by the components in the
pipeline

Significant differences:

* `tags_acc` is renamed to `tag_acc` to be consistent with `token_acc`
and the new `morph_acc`, `pos_acc`, and `lemma_acc`
* Scoring is no longer cumulative: `Scorer.score` scores a list of
examples rather than a single example and does not retain any state
about previously scored examples
* PRF values in the returned scores are no longer multiplied by 100

* Add kwargs to Morphologizer.evaluate

* Create generalized scoring methods in Scorer

* Generalized static scoring methods are added to `Scorer`
  * Methods require an attribute (either on Token or Doc) that is
used to key the returned scores

Naming differences:

* `uas`, `las`, and `las_per_type` in the scores dict are renamed to
`dep_uas`, `dep_las`, and `dep_las_per_type`

Scoring differences:

* `Doc.sents` is now scored as spans rather than on sentence-initial
token positions so that `Doc.sents` and `Doc.ents` can be scored with
the same method (this lowers scores since a single incorrect sentence
start results in two incorrect spans)

* Simplify / extend hasattr check for eval method

* Add hasattr check to tokenizer scoring
* Simplify to hasattr check for component scoring

* Reset Example alignment if docs are set

Reset the Example alignment if either doc is set in case the
tokenization has changed.

* Add PRF tokenization scoring for tokens as spans

Add PRF scores for tokens as character spans. The scores are:

* token_acc: # correct tokens / # gold tokens
* token_p/r/f: PRF for (token.idx, token.idx + len(token))

* Add docstring to Scorer.score_tokenization

* Rename component.evaluate() to component.score()

* Update Scorer API docs

* Update scoring for positive_label in textcat

* Fix TextCategorizer.score kwargs

* Update Language.evaluate docs

* Update score names in default config
2020-07-25 12:53:02 +02:00
Ines Montani
43b960c01b
Refactor pipeline components, config and language data (#5759)
* Update with WIP

* Update with WIP

* Update with pipeline serialization

* Update types and pipe factories

* Add deep merge, tidy up and add tests

* Fix pipe creation from config

* Don't validate default configs on load

* Update spacy/language.py

Co-authored-by: Ines Montani <ines@ines.io>

* Adjust factory/component meta error

* Clean up factory args and remove defaults

* Add test for failing empty dict defaults

* Update pipeline handling and methods

* provide KB as registry function instead of as object

* small change in test to make functionality more clear

* update example script for EL configuration

* Fix typo

* Simplify test

* Simplify test

* splitting pipes.pyx into separate files

* moving default configs to each component file

* fix batch_size type

* removing default values from component constructors where possible (TODO: test 4725)

* skip instead of xfail

* Add test for config -> nlp with multiple instances

* pipeline.pipes -> pipeline.pipe

* Tidy up, document, remove kwargs

* small cleanup/generalization for Tok2VecListener

* use DEFAULT_UPSTREAM field

* revert to avoid circular imports

* Fix tests

* Replace deprecated arg

* Make model dirs require config

* fix pickling of keyword-only arguments in constructor

* WIP: clean up and integrate full config

* Add helper to handle function args more reliably

Now also includes keyword-only args

* Fix config composition and serialization

* Improve config debugging and add visual diff

* Remove unused defaults and fix type

* Remove pipeline and factories from meta

* Update spacy/default_config.cfg

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update spacy/default_config.cfg

* small UX edits

* avoid printing stack trace for debug CLI commands

* Add support for language-specific factories

* specify the section of the config which holds the model to debug

* WIP: add Language.from_config

* Update with language data refactor WIP

* Auto-format

* Add backwards-compat handling for Language.factories

* Update morphologizer.pyx

* Fix morphologizer

* Update and simplify lemmatizers

* Fix Japanese tests

* Port over tagger changes

* Fix Chinese and tests

* Update to latest Thinc

* WIP: xfail first Russian lemmatizer test

* Fix component-specific overrides

* fix nO for output layers in debug_model

* Fix default value

* Fix tests and don't pass objects in config

* Fix deep merging

* Fix lemma lookup data registry

Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed)

* Add types

* Add Vocab.from_config

* Fix typo

* Fix tests

* Make config copying more elegant

* Fix pipe analysis

* Fix lemmatizers and is_base_form

* WIP: move language defaults to config

* Fix morphology type

* Fix vocab

* Remove comment

* Update to latest Thinc

* Add morph rules to config

* Tidy up

* Remove set_morphology option from tagger factory

* Hack use_gpu

* Move [pipeline] to top-level block and make [nlp.pipeline] list

Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them

* Fix use_gpu and resume in CLI

* Auto-format

* Remove resume from config

* Fix formatting and error

* [pipeline] -> [components]

* Fix types

* Fix tagger test: requires set_morphology?

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-07-22 13:42:59 +02:00