* add v1 and v2 tests for tok2vec architectures
* textcat architectures are not "layers"
* test older textcat architectures
* test older parser architecture
* Add initial design for diff command
For now, the diffing process looks like this:
- The default config is created based from some values in the user
config (e.g. which pipeline components were used, the lang, etc.)
- The user must supply manually if it was optimized for acc/efficiency
and if pretraining was involved.
* Make diff command structure similar to siblings
* Include gpu as a user option for CLI
* Make variables more explicit
* Fix type declaration for optimize enum
* Improve docstrings for diff CLI
* Add debug-diff to website API docs
* Switch position of configs so that user config is modded
* Add markdown flag for debug diff
This commit adds a --markdown (--md) flag that allows easier
copy-pasting to Github issues. Please note that this commit is dependent
on an unreleased version of wasabi (for the time being).
For posterity, the related PR is found here: https://github.com/ines/wasabi/pull/20
* Bump version of wasabi to 0.9.1
So that we can use the add_symbols parameter.
* Apply suggestions from code review
Co-authored-by: Ines Montani <ines@ines.io>
* Update docs based on code review suggestions
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Change command name from diff -> diff-config
* Clarify when options are relevant or not
* Rerun prettier on cli.md
Co-authored-by: Ines Montani <ines@ines.io>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Added new convenience cython functions to SpanGroup to avoid unnecessary allocation/deallocation of objects
* Replaced sorting in has_overlap with C++ for efficiency. Also, added a test for has_overlap
* Added a method to efficiently merge SpanGroups
* Added __delitem__, __add__ and __iadd__. Also, allowed to pass span lists to merge function. Replaced extend() body with call to merge
* Renamed merge to concat and added missing things to documentation
* Added operator+ and operator += in the documentation
* Added a test for Doc deallocation
* Update spacy/tokens/span_group.pyx
* Updated SpanGroup tests to use new span list comparison function rather than assert_span_list_equal, eliminating the need to have a separate assert_not_equal fnction
* Fixed typos in SpanGroup documentation
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Minor changes requested by Sofie: rearranged import statements. Added new=3.2.1 tag to SpanGroup.__setitem__ documentation
* SpanGroup: moved repetitive list index check/adjustment in a separate function
* Turn off formatting that hurts readability spacy/tests/doc/test_span_group.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Remove formatting that hurts readability spacy/tests/doc/test_span_group.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Turn off formatting that hurts readability in spacy/tests/doc/test_span_group.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Support more internal methods for SpanGroup
Add support for:
* `__setitem__`
* `__delitem__`
* `__iadd__`: for `SpanGroup` or `Iterable[Span]`
* `__add__`: for `SpanGroup` only
Adapted from #9698 with the scope limited to the magic methods.
* Use v3.3 as new version in docs
* Add new tag to SpanGroup.copy in API docs
* Remove duplicate import
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Remaining suggestions and formatting
Co-authored-by: nrodnova <nrodnova@hotmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Natalia Rodnova <4512370+nrodnova@users.noreply.github.com>
* Add vector deduplication
* Add `Vocab.deduplicate_vectors()`
* Always run deduplication in `spacy init vectors`
* Clean up a few vector-related error messages and docs examples
* Always unique with numpy
* Fix types
* Add edit tree lemmatizer
Co-authored-by: Daniël de Kok <me@danieldk.eu>
* Hide edit tree lemmatizer labels
* Use relative imports
* Switch to single quotes in error message
* Type annotation fixes
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Reformat edit_tree_lemmatizer with black
* EditTreeLemmatizer.predict: take Iterable
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Validate edit trees during deserialization
This change also changes the serialized representation. Rather than
mirroring the deep C structure, we use a simple flat union of the match
and substitution node types.
* Move edit_trees to _edit_tree_internals
* Fix invalid edit tree format error message
* edit_tree_lemmatizer: remove outdated TODO comment
* Rename factory name to trainable_lemmatizer
* Ignore type instead of casting truths to List[Union[Ints1d, Floats2d, List[int], List[str]]] for thinc v8.0.14
* Switch to Tagger.v2
* Add documentation for EditTreeLemmatizer
* docs: Fix 3.2 -> 3.3 somewhere
* trainable_lemmatizer documentation fixes
* docs: EditTreeLemmatizer is in edit_tree_lemmatizer.py
Co-authored-by: Daniël de Kok <me@danieldk.eu>
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add tokenizer option to allow Matcher handling for all rules
Add tokenizer option `with_faster_rules_heuristics` that determines
whether the special cases applied by the internal `Matcher` are filtered
by whether they contain affixes or space. If `True` (default), the rules
are filtered to prioritize speed over rare edge cases. If `False`, all
rules are included in the final `Matcher`-based pass over the doc.
* Reset all caches when reloading special cases
* Revert "Reset all caches when reloading special cases"
This reverts commit 4ef6bd171d.
* Initialize max_length properly
* Add new tag to API docs
* Rename to faster heuristics
* Fix docstring for EntityRenderer
* Add warning in displacy if doc.spans are empty
* Implement parse_spans converter
One notable change here is that the default spans_key is sc, and
it's set by the user through the options.
* Implement SpanRenderer
Here, I implemented a SpanRenderer that looks similar to the
EntityRenderer except for some templates. The spans_key, by default, is
set to sc, but can be configured in the options (see parse_spans). The
way I rendered these spans is per-token, i.e., I first check if each
token (1) belongs to a given span type and (2) a starting token of a
given span type. Once I have this information, I render them into the
markup.
* Fix mypy issues on typing
* Add tests for displacy spans support
* Update colors from RGB to hex
Co-authored-by: Ines Montani <ines@ines.io>
* Remove unnecessary CSS properties
* Add documentation for website
* Remove unnecesasry scripts
* Update wording on the documentation
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Put typing dependency on top of file
* Put back z-index so that spans overlap properly
* Make warning more explicit for spans_key
Co-authored-by: Ines Montani <ines@ines.io>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* 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
* Add save_candidates attribute
* Change spancat api
* Add unit test
* reimplement method to produce a list of doc
* Add method to docs
* Add new version tag
* Add intended use to docstring
* prettier formatting
* Partial fix of entity linker batching
* Add import
* Better name
* Add `use_gold_ents` option, docs
* Change to v2, create stub v1, update docs etc.
* Fix error type
Honestly no idea what the right type to use here is.
ConfigValidationError seems wrong. Maybe a NotImplementedError?
* Make mypy happy
* Add hacky fix for init issue
* Add legacy pipeline entity linker
* Fix references to class name
* Add __init__.py for legacy
* Attempted fix for loss issue
* Remove placeholder V1
* formatting
* slightly more interesting train data
* Handle batches with no usable examples
This adds a test for batches that have docs but not entities, and a
check in the component that detects such cases and skips the update step
as thought the batch were empty.
* Remove todo about data verification
Check for empty data was moved further up so this should be OK now - the
case in question shouldn't be possible.
* Fix gradient calculation
The model doesn't know which entities are not in the kb, so it generates
embeddings for the context of all of them.
However, the loss does know which entities aren't in the kb, and it
ignores them, as there's no sensible gradient.
This has the issue that the gradient will not be calculated for some of
the input embeddings, which causes a dimension mismatch in backprop.
That should have caused a clear error, but with numpyops it was causing
nans to happen, which is another problem that should be addressed
separately.
This commit changes the loss to give a zero gradient for entities not in
the kb.
* add failing test for v1 EL legacy architecture
* Add nasty but simple working check for legacy arch
* Clarify why init hack works the way it does
* Clarify use_gold_ents use case
* Fix use gold ents related handling
* Add tests for no gold ents and fix other tests
* Use aligned ents function (not working)
This doesn't actually work because the "aligned" ents are gold-only. But
if I have a different function that returns the intersection, *then*
this will work as desired.
* Use proper matching ent check
This changes the process when gold ents are not used so that the
intersection of ents in the pred and gold is used.
* Move get_matching_ents to Example
* Use model attribute to check for legacy arch
* Rename flag
* bump spacy-legacy to lower 3.0.9
Co-authored-by: svlandeg <svlandeg@github.com>
* remove duplicate line
* add sent start/end token attributes to the docs
* let has_annotation work with IS_SENT_END
* elif instead of if
* add has_annotation test for sent attributes
* fix typo
* remove duplicate is_sent_start entry in docs
* Clarify Span.ents documentation
Ref: #10135
Retain current behaviour. Span.ents will only include entities within
said span. You can't get tokens outside of the original span.
* Reword docstrings
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update API docs in the website
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* added new field
* added exception for IOb strings
* minor refinement to schema
* removed field
* fixed typo
* imported numeriacla val
* changed the code bit
* cosmetics
* added test for matcher
* set ents of moc docs
* added invalid pattern
* minor update to documentation
* blacked matcher
* added pattern validation
* add IOB vals to schema
* changed into test
* mypy compat
* cleaned left over
* added compat import
* changed type
* added compat import
* changed literal a bit
* went back to old
* made explicit type
* Update spacy/schemas.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spacy/schemas.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spacy/schemas.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Add link to pattern file info in EntityRuler.initialize docs
* Update website/docs/api/entityruler.md
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Use Vectors.shape rather than Vectors.data.shape
* Use Vectors.size rather than Vectors.data.size
* Add Vectors.to_ops to move data between different ops
* Add documentation for Vector.to_ops
* 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>
* added ruler coe
* added error for none existing pattern
* changed error to warning
* changed error to warning
* added basic tests
* fixed place
* added test files
* went back to error
* went back to pattern error
* minor change to docs
* changed style
* changed doc
* changed error slightly
* added remove to phrasem api
* error key already existed
* phrase matcher match code to api
* blacked tests
* moved comments before expr
* corrected error no
* Update website/docs/api/entityruler.md
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update website/docs/api/entityruler.md
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Added sents property to Span class that returns a generator of sentences the Span belongs to
* Added description to Span.sents property
* Update test_span to clarify the difference between span.sent and span.sents
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update spacy/tests/doc/test_span.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Fix documentation typos in spacy/tokens/span.pyx
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update Span.sents doc string in spacy/tokens/span.pyx
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Parametrized test_span_spans
* Corrected Span.sents to check for span-level hook first. Also, made Span.sent respect doc-level sents hook if no span-level hook is provided
* Corrected Span ocumentation copy/paste issue
* Put back accidentally deleted lines
* Fixed formatting in span.pyx
* Moved check for SENT_START annotation after user hooks in Span.sents
* add version where the property was introduced
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add support for kb_id to be displayed via displacy.serve. The current support is only limited to the manual option in displacy.render
* Commit to check pre-commit hooks are run.
* Update spacy/displacy/__init__.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Changes as per suggestions on the PR.
* Update website/docs/api/top-level.md
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update website/docs/api/top-level.md
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* tag option as new from 3.2.1 onwards
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
* Added ENT_ID and ENT_KB_ID into the list of the attributes that Matcher matches on
* Added ENT_ID and ENT_KB_ID to TEST_PATTERNS in test_pattern_validation.py. Disabled tests that I added before
* Update website/docs/api/matcher.md
* Format
* Remove skipped tests
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Add note on batch contract
Using listeners requires batches to be consistent. This is obvious if
you understand how the listener works, but it wasn't clearly stated in
the Docs, and was subtle enough that the EntityLinker missed it.
There is probably a clearer way to explain what the actual requirement
is, but I figure this is a good start.
* Rewrite to clarify role of caching
* Clarify how to fill in init_tok2vec after pretraining
* Ignore init_tok2vec arg in pretraining
* Update docs, config setting
* Remove obsolete note about not filling init_tok2vec early
This seems to have also caught some lines that needed cleanup.
* Clarify error when words are of wrong type
See #9437
* Update docs
* Use try/except
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Add section for spacy.cli.train.train
* Add link from training page to train function
* Ensure path in train helper
* Update docs
Co-authored-by: Ines Montani <ines@ines.io>
* Add micro PRF for morph scoring
For pipelines where morph features are added by more than one component
and a reference training corpus may not contain all features, a micro
PRF score is more flexible than a simple accuracy score. An example is
the reading and inflection features added by the Japanese tokenizer.
* Use `morph_micro_f` as the default morph score for Japanese
morphologizers.
* Update docstring
* Fix typo in docstring
* Update Scorer API docs
* Fix results type
* Organize score list by attribute prefix
