* fix type annotation in docs
* only restore entities after loss calculation
* restore entities of sample in initialization
* rename overfitting function
* fix EL scorer
* Relax test
* fix formatting
* Update spacy/pipeline/entity_linker.py
Co-authored-by: Raphael Mitsch <r.mitsch@outlook.com>
* rename to _ensure_ents
* further rename
* allow for scorer to be None
---------
Co-authored-by: Raphael Mitsch <r.mitsch@outlook.com>
* Add TextCatReduce.v1
This is a textcat classifier that pools the vectors generated by a
tok2vec implementation and then applies a classifier to the pooled
representation. Three reductions are supported for pooling: first, max,
and mean. When multiple reductions are enabled, the reductions are
concatenated before providing them to the classification layer.
This model is a generalization of the TextCatCNN model, which only
supports mean reductions and is a bit of a misnomer, because it can also
be used with transformers. This change also reimplements TextCatCNN.v2
using the new TextCatReduce.v1 layer.
* Doc fixes
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Fully specify `TextCatCNN` <-> `TextCatReduce` equivalence
* Move TextCatCNN docs to legacy, in prep for moving to spacy-legacy
* Add back a test for TextCatCNN.v2
* Replace TextCatCNN in pipe configurations and templates
* Add an infobox to the `TextCatReduce` section with an `TextCatCNN` anchor
* Add last reduction (`use_reduce_last`)
* Remove non-working TextCatCNN Netlify redirect
* Revert layer changes for the quickstart
* Revert one more quickstart change
* Remove unused import
* Fix docstring
* Fix setting name in error message
---------
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update `TextCatBOW` to use the fixed `SparseLinear` layer
A while ago, we fixed the `SparseLinear` layer to use all available
parameters: https://github.com/explosion/thinc/pull/754
This change updates `TextCatBOW` to `v3` which uses the new
`SparseLinear_v2` layer. This results in a sizeable improvement on a
text categorization task that was tested.
While at it, this `spacy.TextCatBOW.v3` also adds the `length_exponent`
option to make it possible to change the hidden size. Ideally, we'd just
have an option called `length`. But the way that `TextCatBOW` uses
hashes results in a non-uniform distribution of parameters when the
length is not a power of two.
* Replace TexCatBOW `length_exponent` parameter by `length`
We now round up the length to the next power of two if it isn't
a power of two.
* Remove some tests for TextCatBOW.v2
* Fix missing import
* Recommend lookups tables from URLs or other loaders
Shift away from the `lookups` extra (which isn't removed, just no longer
mentioned) and recommend loading data from the `spacy-lookups-data` repo
or other sources rather than the `spacy-lookups-data` package.
If the tables can't be loaded from the `lookups` registry in the
lemmatizer, show how to specify the tables in `[initialize]` rather than
recommending the `spacy-lookups-data` package.
* Add tests for some rule-based lemmatizers
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---------
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
When the default `max_length` is not set and there are longer training
documents, it can be difficult to train and evaluate the span finder due
to memory limits and the time it takes to evaluate a huge number of
predicted spans.
* Use isort with Black profile
* isort all the things
* Fix import cycles as a result of import sorting
* Add DOCBIN_ALL_ATTRS type definition
* Add isort to requirements
* Remove isort from build dependencies check
* Typo
* span finder integrated into spacy from experimental
* black
* isort
* black
* default spankey constant
* black
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* rename
* rename
* max_length and min_length as Optional[int] and strict checking
* black
* mypy fix for integer type infinity
* revert line order
* implement all comparison operators for inf int
* avoid two for loops over all docs by not precomputing
* interleave thresholding with span creation
* black
* revert to not interleaving (relized its faster)
* black
* Update spacy/errors.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* update dosctring
* enforce that the gold and predicted documents have the same text
* new error for ensuring reference and predicted texts are the same
* remove todo
* adjust test
* black
* handle misaligned tokenization
* return correct variable
* failing overfit test
* only use a single spans_key like in spancat
* black
* remove debug lines
* typo
* remove comment
* remove near duplicate reduntant method
* use the 'spans_key' variable name everywhere
* Update spacy/pipeline/span_finder.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* flaky test fix suggestion, hand set bias terms
* only test suggester and test result exhaustively
* make it clear that the span_finder_suggester is more general (not specific to span_finder)
* Update spacy/tests/pipeline/test_span_finder.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Apply suggestions from code review
* remove question comment
* move preset_spans_suggester test to spancat tests
* Add docs and unify default configs for spancat and span finder
* Add `allow_overlap=True` to span finder scorer
* Fix offset bug in set_annotations
* Ignore labels in span finder scorer
* Format
* Add span_finder to quickstart template
* Move settings to self.cfg, store min/max unset as None
* Remove debugging
* Update docstrings and docs
* Update spacy/pipeline/span_finder.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Fix imports
---------
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Convert Candidate from Cython to Python class.
* Format.
* Fix .entity_ typo in _add_activations() usage.
* Change type for mentions to look up entity candidates for to SpanGroup from Iterable[Span].
* Update docs.
* Update spacy/kb/candidate.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update doc string of BaseCandidate.__init__().
* Update spacy/kb/candidate.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Rename Candidate to InMemoryCandidate, BaseCandidate to Candidate.
* Adjust Candidate to support and mandate numerical entity IDs.
* Format.
* Fix docstring and docs.
* Update website/docs/api/kb.mdx
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Rename alias -> mention.
* Refactor Candidate attribute names. Update docs and tests accordingly.
* Refacor Candidate attributes and their usage.
* Format.
* Fix mypy error.
* Update error code in line with v4 convention.
* Reverse erroneous changes during merge.
* Update return type in EL tests.
* Re-add Candidate to setup.py.
* Format updated docs.
---------
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* [wip] Update
* [wip] Update
* Add initial port
* [wip] Update
* Fix all imports
* Add spancat_exclusive to pipeline
* [WIP] Update
* [ci skip] Add breakpoint for debugging
* Use spacy.SpanCategorizer.v1 as default archi
* Update spacy/pipeline/spancat_exclusive.py
Co-authored-by: kadarakos <kadar.akos@gmail.com>
* [ci skip] Small updates
* Use Softmax v2 directly from thinc
* Cache the label map
* Fix mypy errors
However, I ignored line 370 because it opened up a bunch of type errors
that might be trickier to solve and might lead to a more complicated
codebase.
* avoid multiplication with 1.0
Co-authored-by: kadarakos <kadar.akos@gmail.com>
* Update spacy/pipeline/spancat_exclusive.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update component versions to v2
* Add scorer to docstring
* Add _n_labels property to SpanCategorizer
Instead of using len(self.labels) in initialize() I am using a private
property self._n_labels. This achieves implementation parity and allows
me to delete the whole initialize() method for spancat_exclusive (since
it's now the same with spancat).
* Inherit from SpanCat instead of TrainablePipe
This commit changes the inheritance structure of Exclusive_Spancat,
now it's inheriting from SpanCategorizer than TrainablePipe. This
allows me to remove duplicate methods that are already present in
the parent function.
* Revert documentation link to spancat
* Fix init call for exclusive spancat
* Update spacy/pipeline/spancat_exclusive.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Import Suggester from spancat
* Include zero_init.v1 for spancat
* Implement _allow_extra_label to use _n_labels
To ensure that spancat / spancat_exclusive cannot be resized after
initialization, I inherited the _allow_extra_label() method from
spacy/pipeline/trainable_pipe.pyx and used self._n_labels instead
of len(self.labels) for checking.
I think that changing it locally is a better solution rather than
forcing each class that inherits TrainablePipe to use the self._n_labels
attribute.
Also note that I turned-off black formatting in this block of code
because it reads better without the overhang.
* Extend existing tests to spancat_exclusive
In this commit, I extended the existing tests for spancat to include
spancat_exclusive. I parametrized the test functions with 'name'
(similar var name with textcat and textcat_multilabel) for each
applicable test.
TODO: Add overfitting tests for spancat_exclusive
* Update documentation for spancat
* Turn on formatting for allow_extra_label
* Remove initializers in default config
* Use DEFAULT_EXCL_SPANCAT_MODEL
I also renamed spancat_exclusive_default_config into
spancat_excl_default_config because black does some not pretty
formatting changes.
* Update documentation
Update grammar and usage
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Clarify docstring for Exclusive_SpanCategorizer
* Remove mypy ignore and typecast labels to list
* Fix documentation API
* Use a single variable for tests
* Update defaults for number of rows
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Put back initializers in spancat config
Whenever I remove model.scorer.init_w and model.scorer.init_b,
I encounter an error in the test:
SystemError: <method '__getitem__' of 'dict' objects> returned a result
with an error set.
My Thinc version is 8.1.5, but I can't seem to check what's causing the
error.
* Update spancat_exclusive docstring
* Remove init_W and init_B parameters
This commit is expected to fail until the new Thinc release.
* Require thinc>=8.1.6 for serializable Softmax defaults
* Handle zero suggestions to make tests pass
I'm not sure if this is the most elegant solution. But what should
happen is that the _make_span_group function MUST return an empty
SpanGroup if there are no suggestions.
The error happens when the 'scores' variable is empty. We cannot
get the 'predicted' and other downstream vars.
* Better approach for handling zero suggestions
* Update website/docs/api/spancategorizer.md
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spancategorizer headers
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add default value in negative_weight in docs
* Add default value in allow_overlap in docs
* Update how spancat_exclusive is constructed
In this commit, I added the following:
- Put the default values of negative_weight and allow_overlap
in the default_config dictionary.
- Rename make_spancat -> make_exclusive_spancat
* Run prettier on spancategorizer.mdx
* Change exactly one -> at most one
* Add suggester documentation in Exclusive_SpanCategorizer
* Add suggester to spancat docstrings
* merge multilabel and singlelabel spancat
* rename spancat_exclusive to singlelable
* wire up different make_spangroups for single and multilabel
* black
* black
* add docstrings
* more docstring and fix negative_label
* don't rely on default arguments
* black
* remove spancat exclusive
* replace single_label with add_negative_label and adjust inference
* mypy
* logical bug in configuration check
* add spans.attrs[scores]
* single label make_spangroup test
* bugfix
* black
* tests for make_span_group with negative labels
* refactor make_span_group
* black
* Update spacy/tests/pipeline/test_spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* remove duplicate declaration
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* raise error instead of just print
* make label mapper private
* update docs
* run prettier
* Update website/docs/api/spancategorizer.mdx
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update website/docs/api/spancategorizer.mdx
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* don't keep recomputing self._label_map for each span
* typo in docs
* Intervals to private and document 'name' param
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update spacy/pipeline/spancat.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* add Tag to new features
* replace tags
* revert
* revert
* revert
* revert
* Update website/docs/api/spancategorizer.mdx
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update website/docs/api/spancategorizer.mdx
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* prettier
* Fix merge
* Update website/docs/api/spancategorizer.mdx
* remove references to 'single_label'
* remove old paragraph
* Add spancat_singlelabel to config template
* Format
* Extend init config tests
---------
Co-authored-by: kadarakos <kadar.akos@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Make empty_kb() configurable.
* Format.
* Update docs.
* Be more specific in KB serialization test.
* Update KB serialization tests. Update docs.
* Remove doc update for batched candidate generation.
* Fix serialization of subclassed KB in tests.
* Format.
* Update docstring.
* Update docstring.
* Switch from pickle to json for custom field serialization.
* Improve the correctness of _parse_patch
* If there are no more actions, do not attempt to make further
transitions, even if not all states are final.
* Assert that the number of actions for a step is the same as
the number of states.
* Reimplement distillation with oracle cut size
The code for distillation with an oracle cut size was not reimplemented
after the parser refactor. We did not notice, because we did not have
tests for this functionality. This change brings back the functionality
and adds this to the parser tests.
* Rename states2actions to _states_to_actions for consistency
* Test distillation max cuts in NER
* Mark parser/NER tests as slow
* Typo
* Fix invariant in _states_diff_to_actions
* Rename _init_batch -> _init_batch_from_teacher
* Ninja edit the ninja edit
* Check that we raise an exception when we pass the incorrect number or actions
* Remove unnecessary get
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Write out condition more explicitly
---------
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Remove backwards-compatible overwrite from Entity Linker
This also adds a docstring about overwrite, since it wasn't present.
* Fix docstring
* Remove backward compat settings in Morphologizer
This also needed a docstring added.
For this component it's less clear what the right overwrite settings
are.
* Remove backward compat from sentencizer
This was simple
* Remove backward compat from senter
Another simple one
* Remove backward compat setting from tagger
* Add docstrings
* Update spacy/pipeline/morphologizer.pyx
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update docs
---------
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Move Entity Linker v1 component to spacy-legacy
This is a follow up to #11889 that moves the component instead of
removing it.
In general, we never import from spacy-legacy in spaCy proper. However,
to use this component, that kind of import will be necessary. I was able
to test this without issues, but is this current import strategy
acceptable? Or should we put the component in a registry?
* Use spacy-legacy pr for CI
This will need to be reverted before merging.
* Add temporary step to log installed spacy-legacy version
* Modify requirements.txt to trigger tests
* Add comment to Python to trigger tests
* TODO REVERT This is a commit with logic changes to trigger tests
* Remove pipe from YAML
Works locally, but possibly this is causing a quoting error or
something.
* Revert "TODO REVERT This is a commit with logic changes to trigger tests"
This reverts commit 689fae71f3.
* Revert "Add comment to Python to trigger tests"
This reverts commit 11840fc598.
* Add more logging
* Try installing directly in workflow
* Try explicitly uninstalling spacy-legacy first
* Cat requirements.txt to confirm contents
In the branch, the thinc version spec is `thinc>=8.1.0,<8.2.0`. But in
the logs, it's clear that a development release of 9.0 is being
installed. It's not clear why that would happen.
* Log requirements at start of build
* TODO REVERT Change thinc spec
Want to see what happens to the installed thinc spec with this change.
* Update thinc requirements
This makes it the same as it was before the merge, >=8.1.0,<8.2.0.
* Use same thinc version as v4 branch
* TODO REVERT Mark dependency check as xfail
spacy-legacy is specified as a git checkout in requirements.txt while
this PR is in progress, which makes the consistency check here fail.
* Remove debugging output / install step
* Revert "Remove debugging output / install step"
This reverts commit 923ea7448b.
* Clean up debugging output
The manual install step with the URL fragment seems to have caused
issues on Windows due to the = in the URL being misinterpreted. On the
other hand, removing it seems to mean the git version of spacy-legacy
isn't actually installed.
This PR removes the URL fragment but keeps the direct command-line
install. Additionally, since it looks like this job is configured to use
the default shell (and not bash), it removes a comment that upsets the
Windows cmd shell.
* Revert "TODO REVERT Mark dependency check as xfail"
This reverts commit d4863ec156.
* Fix requirements.txt, increasing spacy-legacy version
* Raise spacy legacy version in setup.cfg
* Remove azure build workarounds
* make spacy-legacy version explicit in error message
* Remove debugging line
* Suggestions from code review
* Add `Language.distill`
This method is the distillation counterpart of `Language.update`. It
takes a teacher `Language` instance and distills the student pipes on
the teacher pipes.
* Apply suggestions from code review
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Clarify that how Example is used in distillation
* Update transition parser distill docstring for examples argument
* Pass optimizer to `TrainablePipe.distill`
* Annotate pipe before update
As discussed internally, we want to let a pipe annotate before doing an
update with gold/silver data. Otherwise, the output may be (too)
informed by the gold/silver data.
* Rename `component_map` to `student_to_teacher`
* Better synopsis in `Language.distill` docstring
* `name` -> `student_name`
* Fix labels type in docstring
* Mark distill test as slow
* Fix `student_to_teacher` type in docs
---------
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
