* add multi-label textcat to menu
* add infobox on textcat API
* add info to v3 migration guide
* small edits
* further fixes in doc strings
* add infobox to textcat architectures
* add textcat_multilabel to overview of built-in components
* spelling
* fix unrelated warn msg
* Add textcat_multilabel to quickstart [ci skip]
* remove separate documentation page for multilabel_textcategorizer
* small edits
* positive label clarification
* avoid duplicating information in self.cfg and fix textcat.score
* fix multilabel textcat too
* revert threshold to storage in cfg
* revert threshold stuff for multi-textcat
Co-authored-by: Ines Montani <ines@ines.io>
* Fix aborted/skipped augmentation for `spacy.orth_variants.v1` if
lowercasing was enabled for an example
* Simplify `spacy.orth_variants.v1` for `Example` vs. `GoldParse`
* Preserve reference tokenization in `spacy.lower_case.v1`
* initialize NLP with train corpus
* add more pretraining tests
* more tests
* function to fetch tok2vec layer for pretraining
* clarify parameter name
* test different objectives
* formatting
* fix check for static vectors when using vectors objective
* clarify docs
* logger statement
* fix init_tok2vec and proc.initialize order
* test training after pretraining
* add init_config tests for pretraining
* pop pretraining block to avoid config validation errors
* custom errors
* Fix `is_cython_func` for imported code loaded under `python_code`
module name
* Add `make_named_tempfile` context manager to test utils to test
loading of imported code
* Add test for validation of `initialize` params in custom module
* Add test for #7035
* Update test for issue 7056
* Fix test
* Fix transitions method used in testing
* Fix state eol detection when rebuffer
* Clean up redundant fix
* Add regression test
* Run PhraseMatcher on Spans
* Add test for PhraseMatcher on Spans and Docs
* Add SCA
* Add test with 3 matches in Doc, 1 match in Span
* Update docs
* Use doc.length for find_matches in tokenizer
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
```python
def test_vocab_lexeme_add_flag_auto_id(en_vocab):
is_len4 = en_vocab.add_flag(lambda string: len(string) == 4)
assert en_vocab["1999"].check_flag(is_len4) is True
assert en_vocab["1999"].check_flag(IS_DIGIT) is True
assert en_vocab["199"].check_flag(is_len4) is False
> assert en_vocab["199"].check_flag(IS_DIGIT) is True
E assert False is True
E + where False = <built-in method check_flag of spacy.lexeme.Lexeme object at 0x7fa155c36840>(3)
E + where <built-in method check_flag of spacy.lexeme.Lexeme object at 0x7fa155c36840> = <spacy.lexeme.Lexeme object at 0x7fa155c36840>.check_flag
spacy/tests/vocab_vectors/test_lexeme.py:49: AssertionError
```
> `pytest==6.1.1`
>
> `numpy==1.19.2`
>
> `Python version: 3.8.3`
To reproduce the error, run `pytest --random-order-bucket=global --random-order-seed=170158 -v spacy/tests`
If `test_vocab_lexeme_add_flag_auto_id` is run after `test_vocab_lexeme_add_flag_provided_id`, it fails.
It seems like `test_vocab_lexeme_add_flag_provided_id` uses the `IS_DIGIT` bit for testing purposes but does not reset the bit.
This solution seems to work but, if anyone has a better fix, please let me know and I will integrate it.
Instead of silently using only the first token in each matched span:
* Forbid `OP: ?/*/+` through `DependencyMatcher` validation
* As a fail-safe, add warning if a token match that's not exactly one
token long is found by a token pattern.
* 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
* Initial Spanish lemmatizer
* Handle merged verb+pron(s) multi-word tokens
* Use VERB for AUX rule lookup
* Add morph to lemma cache key
* Fix aux lookups, minor refactoring
* Improve verb+pron handling
* Move verb+pron handling into its own method
* Check for exceptions (primarily for se)
* Collect pronouns in the same (not reversed) order
* Only add modified possible lemmas
* Fix `spacy.util.minibatch` when the size iterator is finished (#6745)
* Skip 0-length matches (#6759)
Add hack to prevent matcher from returning 0-length matches.
* support IS_SENT_START in PhraseMatcher (#6771)
* support IS_SENT_START in PhraseMatcher
* add unit test and friendlier error
* use IDS.get instead
* ensure span.text works for an empty span (#6772)
* Remove unicode_literals
Co-authored-by: Santiago Castro <bryant@montevideo.com.uy>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* raise NotImplementedError when noun_chunks iterator is not implemented
* bring back, fix and document span.noun_chunks
* formatting
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* Add long_token_splitter component
Add a `long_token_splitter` component for use with transformer
pipelines. This component splits up long tokens like URLs into smaller
tokens. This is particularly relevant for pretrained pipelines with
`strided_spans`, since the user can't change the length of the span
`window` and may not wish to preprocess the input texts.
The `long_token_splitter` splits tokens that are at least
`long_token_length` tokens long into smaller tokens of `split_length`
size.
Notes:
* Since this is intended for use as the first component in a pipeline,
the token splitter does not try to preserve any token annotation.
* API docs to come when the API is stable.
* Adjust API, add test
* Fix name in factory
* Handle unset token.morph in Morphologizer
Handle unset `token.morph` in `Morphologizer.initialize` and
`Morphologizer.get_loss`. If both `token.morph` and `token.pos` are
unset, treat the annotation as missing rather than empty.
* Add token.has_morph()
* Override language defaults for null token and URL match
When the serialized `token_match` or `url_match` is `None`, override the
language defaults to preserve `None` on deserialization.
* Fix fixtures in tests
* Draft out initial Spans data structure
* Initial span group commit
* Basic span group support on Doc
* Basic test for span group
* Compile span_group.pyx
* Draft addition of SpanGroup to DocBin
* Add deserialization for SpanGroup
* Add tests for serializing SpanGroup
* Fix serialization of SpanGroup
* Add EdgeC and GraphC structs
* Add draft Graph data structure
* Compile graph
* More work on Graph
* Update GraphC
* Upd graph
* Fix walk functions
* Let Graph take nodes and edges on construction
* Fix walking and getting
* Add graph tests
* Fix import
* Add module with the SpanGroups dict thingy
* Update test
* Rename 'span_groups' attribute
* Try to fix c++11 compilation
* Fix test
* Update DocBin
* Try to fix compilation
* Try to fix graph
* Improve SpanGroup docstrings
* Add doc.spans to documentation
* Fix serialization
* Tidy up and add docs
* Update docs [ci skip]
* Add SpanGroup.has_overlap
* WIP updated Graph API
* Start testing new Graph API
* Update Graph tests
* Update Graph
* Add docstring
Co-authored-by: Ines Montani <ines@ines.io>
Add `initialize.before_init` and `initialize.after_init` callbacks to
the config. The `initialize.before_init` callback is a place to
implement one-time tokenizer customizations that are then saved with the
model.
* fix TorchBiLSTMEncoder documentation
* ensure the types of the encoding Tok2vec layers are correct
* update references from v1 to v2 for the new architectures
* add syntax iterators for danish
* add test noun chunks for danish syntax iterators
* add contributor agreement
* update da syntax iterators to remove nested chunks
* add tests for da noun chunks
* Fix test
* add missing import
* fix example
* Prevent overlapping noun chunks
Prevent overlapping noun chunks by tracking the end index of the
previous noun chunk span.
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* clean up of ner tests
* beam_parser tests
* implement get_beam_parses and scored_parses for the dep parser
* we don't have to add the parse if there are no arcs
* small fixes and formatting
* bring test_issue4313 up-to-date, currently fails
* formatting
* add get_beam_parses method back
* add scored_ents function
* delete tag map
Instead of unsetting lemmas on retokenized tokens, set the default
lemmas to:
* merge: concatenate any existing lemmas with `SPACY` preserved
* split: use the new `ORTH` values if lemmas were previously set,
otherwise leave unset
* multi-label textcat component
* formatting
* fix comment
* cleanup
* fix from #6481
* random edit to push the tests
* add explicit error when textcat is called with multi-label gold data
* fix error nr
* small fix
* Fix memory issues in Language.evaluate
Reset annotation in predicted docs before evaluating and store all data
in `examples`.
* Minor refactor to docs generator init
* Fix generator expression
* Fix final generator check
* Refactor pipeline loop
* Handle examples generator in Language.evaluate
* Add test with generator
* Use make_doc
* Add Amharic to space
* clean up
* Add some PRON_LEMMA
* add Tigrinya support
* remove text_noun_chunks
* Tigrinya Support
* added some more details for ti
* fix unit test
* add amharic char range
* changes from review
* amharic and tigrinya share same unicode block
* get rid of _amharic/_tigrinya in char_classes
Co-authored-by: Josiah Solomon <jsolomon@meteorcomm.com>
