Remove the non-working `--use-chars` option from the train CLI. The
implementation of the option across component types and the CLI settings
could be fixed, but the `CharacterEmbed` model does not work on GPU in
v2 so it's better to remove it.
* 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
* small fix in example imports
* throw error when train_corpus or dev_corpus is not a string
* small fix in custom logger example
* limit macro_auc to labels with 2 annotations
* fix typo
* also create parents of output_dir if need be
* update documentation of textcat scores
* refactor TextCatEnsemble
* fix tests for new AUC definition
* bump to 3.0.0a42
* update docs
* rename to spacy.TextCatEnsemble.v2
* spacy.TextCatEnsemble.v1 in legacy
* cleanup
* small fix
* update to 3.0.0rc2
* fix import that got lost in merge
* cursed IDE
* fix two typos
* 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
* add informative warning when messing up store_user_data DocBin flags
* add informative warning when messing up store_user_data DocBin flags
* cleanup test
* rename to patterns_path
* Support data augmentation in Corpus
* Note initial docs for data augmentation
* Add augmenter to quickstart
* Fix flake8
* Format
* Fix test
* Update spacy/tests/training/test_training.py
* Improve data augmentation arguments
* Update templates
* Move randomization out into caller
* Refactor
* Update spacy/training/augment.py
* Update spacy/tests/training/test_training.py
* Fix augment
* Fix test
* Add MORPH handling to Matcher
* Add `MORPH` to `Matcher` schema
* Rename `_SetMemberPredicate` to `_SetPredicate`
* Add `ISSUBSET` and `ISSUPERSET` operators to `_SetPredicate`
* Add special handling for normalization and conversion of morph
values into sets
* For other attrs, `ISSUBSET` acts like `IN` and `ISSUPERSET` only
matches for 0 or 1 values
* Update test
* Rename to IS_SUBSET and IS_SUPERSET
* NEL: read sentences and ents from reference
* fiddling with sent_start annotations
* add KB serialization test
* KB write additional file with strings.json
* score_links function to calculate NEL P/R/F
* formatting
* documentation
* Refactor Docs.is_ flags
* Add derived `Doc.has_annotation` method
* `Doc.has_annotation(attr)` returns `True` for partial annotation
* `Doc.has_annotation(attr, require_complete=True)` returns `True` for
complete annotation
* Add deprecation warnings to `is_tagged`, `is_parsed`, `is_sentenced`
and `is_nered`
* Add `Doc._get_array_attrs()`, which returns a full list of `Doc` attrs
for use with `Doc.to_array`, `Doc.to_bytes` and `Doc.from_docs`. The
list is the `DocBin` attributes list plus `SPACY` and `LENGTH`.
Notes on `Doc.has_annotation`:
* `HEAD` is converted to `DEP` because heads don't have an unset state
* Accept `IS_SENT_START` as a synonym of `SENT_START`
Additional changes:
* Add `NORM`, `ENT_ID` and `SENT_START` to default attributes for
`DocBin`
* In `Doc.from_array()` the presence of `DEP` causes `HEAD` to override
`SENT_START`
* In `Doc.from_array()` using `attrs` other than
`Doc._get_array_attrs()` (i.e., a user's custom list rather than our
default internal list) with both `HEAD` and `SENT_START` shows a warning
that `HEAD` will override `SENT_START`
* `set_children_from_heads` does not require dependency labels to set
sentence boundaries and sets `sent_start` for all non-sentence starts to
`-1`
* Fix call to set_children_form_heads
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
Add official support for the `DependencyMatcher`. Redesign the pattern
specification. Fix and extend operator implementations. Update API docs
and add usage docs.
Patterns
--------
Refactor pattern structure to:
```
{
"LEFT_ID": str,
"REL_OP": str,
"RIGHT_ID": str,
"RIGHT_ATTRS": dict,
}
```
The first node contains only `RIGHT_ID` and `RIGHT_ATTRS` and all
subsequent nodes contain all four keys.
New operators
-------------
Because of the way patterns are constructed from left to right, it's
helpful to have `follows` operators along with `precedes` operators. Add
operators for simple precedes / follows alongside immediate precedes /
follows.
* `.*`: precedes
* `;`: immediately follows
* `;*`: follows
Operator fixes
--------------
* `<` and `<<` do not include the node itself
* Fix reversed order for all operators involving linear precedence (`.`,
all sibling operators)
* Linear precedence operators do not match nodes outside the same parse
Additional fixes
----------------
* Use v3 Matcher API
* Support `get` and `remove`
* Support pickling
* rename to spacy-transformers.TransformerListener
* add some more tok2vec tests
* use select_pipes
* fix docs - annotation setter was not changed in the end
* Add AttributeRuler.score
Add scoring for TAG / POS / MORPH / LEMMA if these are present in the
assigned token attributes.
Add default score weights (that don't really make a lot of sense) so
that the scores are in the default config in some form.
* Update docs
- Accept any case for label names in ents and colors option, even if actual predicted label uses different casing
- Don't text-transform: uppercase visually, if it's important to users that the label is represented as-is in the UI
* candidate generator as separate part of EL config
* update comment
* ent instead of str as input for candidate generation
* Span instead of str: correct type indication
* fix types
* unit test to create new candidate generator
* fix replace_pipe argument passing
* move error message, general cleanup
* add vocab back to KB constructor
* provide KB as callable from Vocab arg
* rename to kb_loader, fix KB serialization as part of the EL pipe
* fix typo
* reformatting
* cleanup
* fix comment
* fix wrongly duplicated code from merge conflict
* rename dump to to_disk
* from_disk instead of load_bulk
* update test after recent removal of set_morphology in tagger
* remove old doc
* Add Lemmatizer and simplify related components
* Add `Lemmatizer` pipe with `lookup` and `rule` modes using the
`Lookups` tables.
* Reduce `Tagger` to a simple tagger that sets `Token.tag` (no pos or lemma)
* Reduce `Morphology` to only keep track of morph tags (no tag map, lemmatizer,
or morph rules)
* Remove lemmatizer from `Vocab`
* Adjust many many tests
Differences:
* No default lookup lemmas
* No special treatment of TAG in `from_array` and similar required
* Easier to modify labels in a `Tagger`
* No extra strings added from morphology / tag map
* Fix test
* Initial fix for Lemmatizer config/serialization
* Adjust init test to be more generic
* Adjust init test to force empty Lookups
* Add simple cache to rule-based lemmatizer
* Convert language-specific lemmatizers
Convert language-specific lemmatizers to component lemmatizers. Remove
previous lemmatizer class.
* Fix French and Polish lemmatizers
* Remove outdated UPOS conversions
* Update Russian lemmatizer init in tests
* Add minimal init/run tests for custom lemmatizers
* Add option to overwrite existing lemmas
* Update mode setting, lookup loading, and caching
* Make `mode` an immutable property
* Only enforce strict `load_lookups` for known supported modes
* Move caching into individual `_lemmatize` methods
* Implement strict when lang is not found in lookups
* Fix tables/lookups in make_lemmatizer
* Reallow provided lookups and allow for stricter checks
* Add lookups asset to all Lemmatizer pipe tests
* Rename lookups in lemmatizer init test
* Clean up merge
* Refactor lookup table loading
* Add helper from `load_lemmatizer_lookups` that loads required and
optional lookups tables based on settings provided by a config.
Additional slight refactor of lookups:
* Add `Lookups.set_table` to set a table from a provided `Table`
* Reorder class definitions to be able to specify type as `Table`
* Move registry assets into test methods
* Refactor lookups tables config
Use class methods within `Lemmatizer` to provide the config for
particular modes and to load the lookups from a config.
* Add pipe and score to lemmatizer
* Simplify Tagger.score
* Add missing import
* Clean up imports and auto-format
* Remove unused kwarg
* Tidy up and auto-format
* Update docstrings for Lemmatizer
Update docstrings for Lemmatizer.
Additionally modify `is_base_form` API to take `Token` instead of
individual features.
* Update docstrings
* Remove tag map values from Tagger.add_label
* Update API docs
* Fix relative link in Lemmatizer API docs
* Allow Doc.char_span to snap to token boundaries
Add a `mode` option to allow `Doc.char_span` to snap to token
boundaries. The `mode` options:
* `strict`: character offsets must match token boundaries (default, same as
before)
* `inside`: all tokens completely within the character span
* `outside`: all tokens at least partially covered by the character span
Add a new helper function `token_by_char` that returns the token
corresponding to a character position in the text. Update
`token_by_start` and `token_by_end` to use `token_by_char` for more
efficient searching.
* Remove unused import
* Rename mode to alignment_mode
Rename `mode` to `alignment_mode` with the options
`strict`/`contract`/`expand`. Any unrecognized modes are silently
converted to `strict`.
* 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
* Use cosine loss in Cloze multitask
* Fix char_embed for gpu
* Call resume_training for base model in train CLI
* Fix bilstm_depth default in pretrain command
* Implement character-based pretraining objective
* Use chars loss in ClozeMultitask
* Add method to decode predicted characters
* Fix number characters
* Rescale gradients for mlm
* Fix char embed+vectors in ml
* Fix pipes
* Fix pretrain args
* Move get_characters_loss
* Fix import
* Fix import
* Mention characters loss option in pretrain
* Remove broken 'self attention' option in pretrain
* Revert "Remove broken 'self attention' option in pretrain"
This reverts commit 56b820f6af.
* Document 'characters' objective of pretrain
* Add static method to Doc to allow merging of multiple docs.
* Add error description for the error that occurs if docs with different
vocabs (from different languages) are merged in Doc.from_docs().
* Add test for Doc.from_docs() implementation.
* Fix using numpy's concatenate in Doc.from_docs.
* Replace typing's type annotations in from_docs.
* Simply remove type annotations in from_docs.
* Add documentation for Doc.from_docs to api.
* Simplify from_docs, its test and the api doc for codebase consistency.
* Fix merging of Doc objects that end with whitespaces (Achieved by simply not setting the SPACY attribute on whitespace tokens). Remove two unnecessary imports of attributes.
* Add merging of user data from Doc objects in from_docs. Add user data test case to corresponding test. Add applicable warning messages.
* Fix incorrect setting of tokens idx by using concatenated spaces (again). Add test case to corresponding test.
* Add MORPH to attrs
* Update warnings calls
* Remove out-dated error from merge
* Rename space_delimiter to ensure_whitespace
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Add version number to DocBin
Add a version number to DocBin for future use.
* Add POS to all attributes in DocBin
* Add morph string to strings in DocBin
* Update DocBin API
* Add string for ENT_KB_ID in DocBin
Very minor fix in docs, specifically in this part:
```
matcher = PhraseMatcher(nlp.vocab)
> for doc in matcher.pipe(texts, batch_size=50):
> pass
```
`texts` suggests the input is an iterable of strings. I replaced it for `docs`.
Very minor fix in docs, specifically in this part:
```
matcher = PhraseMatcher(nlp.vocab)
> for doc in matcher.pipe(texts, batch_size=50):
> pass
```
`texts` suggests the input is an iterable of strings. I replaced it for `docs`.
* Update website models for v2.3.0
* Add docs for Chinese word segmentation
* Tighten up Chinese docs section
* Merge branch 'master' into docs/v2.3.0 [ci skip]
* Merge branch 'master' into docs/v2.3.0 [ci skip]
* Auto-format and update version
* Update matcher.md
* Update languages and sorting
* Typo in landing page
* Infobox about token_match behavior
* Add meta and basic docs for Japanese
* POS -> TAG in models table
* Add info about lookups for normalization
* Updates to API docs for v2.3
* Update adding norm exceptions for adding languages
* Add --omit-extra-lookups to CLI API docs
* Add initial draft of "What's New in v2.3"
* Add new in v2.3 tags to Chinese and Japanese sections
* Add tokenizer to migration section
* Add new in v2.3 flags to init-model
* Typo
* More what's new in v2.3
Co-authored-by: Ines Montani <ines@ines.io>
* verbose and tag_map options
* adding init_tok2vec option and only changing the tok2vec that is specified
* adding omit_extra_lookups and verifying textcat config
* wip
* pretrain bugfix
* add replace and resume options
* train_textcat fix
* raw text functionality
* improve UX when KeyError or when input data can't be parsed
* avoid unnecessary access to goldparse in TextCat pipe
* save performance information in nlp.meta
* add noise_level to config
* move nn_parser's defaults to config file
* multitask in config - doesn't work yet
* scorer offering both F and AUC options, need to be specified in config
* add textcat verification code from old train script
* small fixes to config files
* clean up
* set default config for ner/parser to allow create_pipe to work as before
* two more test fixes
* small fixes
* cleanup
* fix NER pickling + additional unit test
* create_pipe as before
