* Regression test for issue 6207
* Fix issue 6207
* Sign contributor agreement
* Minor adjustments to test
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* added tr_vocab to config
* basic test
* added syntax iterator to Turkish lang class
* first version for Turkish syntax iter, without flat
* added simple tests with nmod, amod, det
* more tests to amod and nmod
* separated noun chunks and parser test
* rearrangement after nchunk parser separation
* added recursive NPs
* tests with complicated recursive NPs
* tests with conjed NPs
* additional tests for conj NP
* small modification for shaving off conj from NP
* added tests with flat
* more tests with flat
* added examples with flats conjed
* added inner func for flat trick
* corrected parse
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* 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
* added tr_vocab to config
* basic test
* added syntax iterator to Turkish lang class
* first version for Turkish syntax iter, without flat
* added simple tests with nmod, amod, det
* more tests to amod and nmod
* separated noun chunks and parser test
* rearrangement after nchunk parser separation
* added recursive NPs
* tests with complicated recursive NPs
* tests with conjed NPs
* additional tests for conj NP
* small modification for shaving off conj from NP
* added tests with flat
* more tests with flat
* added examples with flats conjed
* added inner func for flat trick
* corrected parse
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Hindi: Adds tests for lexical attributes (norm and like_num)
* Signs and sdds the contributor agreement
* Add ordinal numbers to be tagged as like_num
* Adds alternate pronunciation for 31 and 39
* Regression test for issue 6207
* Fix issue 6207
* Sign contributor agreement
* Minor adjustments to test
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Update arguments to MultiHashEmbed layer so that the attributes can be
controlled. A kind of tricky scheme is used to allow optional
specification of the rows. I think it's an okay balance between
flexibility and convenience.
* 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
* Refactor Token morph setting
* Remove `Token.morph_`
* Add `Token.set_morph()`
* `0` resets `token.c.morph` to unset
* Any other values are passed to `Morphology.add`
* Add token.morph setter to set from MorphAnalysis
* 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
* Allow `pkuseg_model` to be set to `None` on initialization
* Don't save config within tokenizer
* Force convert pkuseg_model to use pickle protocol 4 by reencoding with
`pickle5` on serialization
* Update pkuseg serialization 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
* Add option to disable Matcher errors
* Add option to disable Matcher errors when a doc doesn't contain a
particular type of annotation
Minor additional change:
* Update `AttributeRuler.load_from_morph_rules` to allow direct `MORPH`
values
* Rename suppress_errors to allow_missing
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* Refactor annotation checks in Matcher and PhraseMatcher
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* 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
Similar to how vectors are handled, move the vocab lookups to be loaded
at the start of training rather than when the vocab is initialized,
since the vocab doesn't have access to the full config when it's
created.
The option moves from `nlp.load_vocab_data` to `training.lookups`.
Typically these tables will come from `spacy-lookups-data`, but any
`Lookups` object can be provided.
The loading from `spacy-lookups-data` is now strict, so configs for each
language should specify the exact tables required. This also makes it
easier to control whether the larger clusters and probs tables are
included.
To load `lexeme_norm` from `spacy-lookups-data`:
```
[training.lookups]
@misc = "spacy.LoadLookupsData.v1"
lang = ${nlp.lang}
tables = ["lexeme_norm"]
```
In order to make it easier to construct `Doc` objects as training data,
modify how missing and blocked entity tokens are set to prioritize
setting `O` and missing entity tokens for training purposes over setting
blocked entity tokens.
* `Doc.ents` setter sets tokens outside entity spans to `O` regardless
of the current state of each token
* For `Doc.ents`, setting a span with a missing label sets the `ent_iob`
to missing instead of blocked
* `Doc.block_ents(spans)` marks spans as hard `O` for use with the
`EntityRecognizer`
* 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>
* Clean up spacy.tokens
* Update `set_children_from_heads`:
* Don't check `dep` when setting lr_* or sentence starts
* Set all non-sentence starts to `False`
* Use `set_children_from_heads` in `Token.head` setter
* Reduce similar/duplicate code (admittedly adds a bit of overhead)
* Update sentence starts consistently
* Remove unused `Doc.set_parse`
* Minor changes:
* Declare cython variables (to avoid cython warnings)
* Clean up imports
* Modify set_children_from_heads to set token range
Modify `set_children_from_heads` so that it adjust tokens within a
specified range rather then the whole document.
Modify the `Token.head` setter to adjust only the tokens affected by the
new head assignment.
For languages without provided models and with lemmatizer rules in
`spacy-lookups-data`, make the rule-based lemmatizer the default:
Bengali, Persian, Norwegian, Swedish
