* 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>
* Require that all SpanGroup spans are from the current doc
The restriction on only adding spans from the current doc were already
implemented for all operations except for `SpanGroup.__init__`.
Initialize copied spans for `SpanGroup.copy` with `Doc.char_span` in
order to validate the character offsets and to make it possible to copy
spans between documents with differing tokenization. Currently there is
no validation that the document texts are identical, but the span char
offsets must be valid spans in the target doc, which prevents you from
ending up with completely invalid spans.
* Undo change in test_beam_overfitting_IO
* Address upcoming numpy v1.25 deprecations in test suite
* Temporarily test most recent numpy prerelease in CI
* Revert "Temporarily test most recent numpy prerelease in CI"
This reverts commit d75a66e55e.
* Add scorer option to return per-component scores
Add `per_component` option to `Language.evaluate` and `Scorer.score` to
return scores keyed by `tokenizer` (hard-coded) or by component name.
Add option to `evaluate` CLI to score by component. Per-component scores
can only be saved to JSON.
* Update help text and messages
This reverts commit 6f314f99c4.
We are reverting this until we can support this normalization more
consistently across vectors, training corpora, and lemmatizer data.
* Use Latin normalization for Serbian attrs
Use Latin normalization for Serbian `NORM`, `PREFIX`, and `SUFFIX`.
* Update NORMs in tokenizer exceptions and related tests
* Add tests for all custom lex attrs
* Remove unused imports
* Add spans in spacy benchmark
The current implementation of spaCy benchmark accuracy / spacy evaluate
doesn't include the "spans" type, so calling the command doesn't render
the HTML displaCy file needed.
This PR attempts to fix that by creating a new parameter for "spans"
and calling the appropriate displaCy value.
* Reformat file with black
* Add tests for evaluate
* Fix spans -> span for displacy style
* Update test to check render instead
* Update source so mypy passes
* Add parser information to avoid warnings
* Add distillation initialization and loop
* Fix up configuration keys
* Add docstring
* Type annotations
* init_nlp_distill -> init_nlp_student
* Do not resolve dot name distill corpus in initialization
(Since we don't use it.)
* student: do not request use of optimizer in student pipe
We apply finish up the updates once in the training loop instead.
Also add the necessary logic to `Language.distill` to mirror
`Language.update`.
* Correctly determine sort key in subdivide_batch
* Fix _distill_loop docstring wrt. stopping condition
* _distill_loop: fix distill_data docstring
Make similar changes in train_while_improving, since it also had
incorrect types and missing type annotations.
* Move `set_{gpu_allocator,seed}_from_config` to spacy.util
* Update Language.update docs for the sgd argument
* Type annotation
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
---------
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Add noun chunking to la syntax iterators
* Expand list of numeral, ordinal words
* Expand abbreviations in la tokenizer_exceptions
* Add example sents
* Update spacy/lang/la/syntax_iterators.py
Reorganize la syntax iterators
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Minor updates based on review
* fix call
---------
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add default to MorphAnalysis.get
Similar to `dict`, allow a `default` option for `MorphAnalysis.get` for
the user to provide a default return value if the field is not found.
The default return value remains `[]`, which is not the same as
`dict.get`, but is already established as this method's default return
value with the return type `List[str]`. However the new `default` option
does not enforce that the user-provided default is actually `List[str]`.
* Restore test case
* Enforce that Span.start/end(_char) remain valid and in sync
Allowing span attributes to be writable starting in v3 has made it
possible for the internal `Span.start/end/start_char/end_char` to get
out-of-sync or have invalid values.
This checks that the values are valid and syncs the token and char
offsets if any attributes are modified directly. It does not yet handle
the case where the underlying doc is modified.
* Format
* Avoid `TrainablePipe.finish_update` getting called twice during training
PR #12136 fixed an issue where the tok2vec pipe was updated before
gradient were accumulated. However, it introduced a new bug that cause
`finish_update` to be called twice when using the training loop. This
causes a fairly large slowdown.
The `Language.update` method accepts the `sgd` argument for passing an
optimizer. This argument has three possible values:
- `Optimizer`: use the given optimizer to finish pipe updates.
- `None`: use a default optimizer to finish pipe updates.
- `False`: do not finish pipe updates.
However, the latter option was not documented and not valid with the
existing type of `sgd`. I assumed that this was a remnant of earlier
spaCy versions and removed handling of `False`.
However, with that change, we are passing `None` to `Language.update`.
As a result, we were calling `finish_update` in both `Language.update`
and in the training loop after all subbatches are processed.
This change restores proper handling/use of `False`. Moreover, the role
of `False` is now documented and added to the type to avoid future
accidents.
* Fix typo
* Document defaults for `Language.update`
* 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>
* Clean up Vocab constructor
* Change effective type of `strings` from `Iterable[str]` to `Optional[StringStore]`
* Don't automatically add strings to vocab
* Change default values to `None`
* Remove `**deprecated_kwargs`
* Format
* [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>
* Handle deprecation of pkg_resources
* Replace `pkg_resources` with `importlib_metadata` for `spacy info
--url`
* Remove requirements check from `spacy project` given the lack of
alternatives
* Fix installed model URL method and CI test
* Fix types/handling, simplify catch-all return
* Move imports instead of disabling requirements check
* Format
* Reenable test with ignored deprecation warning
* Fix except
* Fix return
* 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.
* Add immediate left/right child/parent dependency relations
* Add tests for new REL_OPs: `>+`, `>-`, `<+`, and `<-`.
---------
Co-authored-by: Tan Long <tanloong@foxmail.com>
* add unittest for explosion#12311
* create punctuation.py for swedish
* removed : from infixes in swedish punctuation.py
* allow : as infix if succeeding char is uppercase
* 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>
* `Language.update`: ensure that tok2vec gets updated
The components in a pipeline can be updated independently. However,
tok2vec implementations are an exception to this, since they depend on
listeners for their gradients. The update method of a tok2vec
implementation computes the tok2vec forward and passes this along with a
backprop function to the listeners. This backprop function accumulates
gradients for all the listeners. There are two ways in which the
accumulated gradients can be used to update the tok2vec weights:
1. Call the `finish_update` method of tok2vec *after* the `update`
method is called on all of the pipes that use a tok2vec listener.
2. Pass an optimizer to the `update` method of tok2vec. In this
case, tok2vec will give the last listener a special backprop
function that calls `finish_update` on the tok2vec.
Unfortunately, `Language.update` did neither of these. Instead, it
immediately called `finish_update` on every pipe after `update`. As a
result, the tok2vec weights are updated when no gradients have been
accumulated from listeners yet. And the gradients of the listeners are
only used in the next call to `Language.update` (when `finish_update` is
called on tok2vec again).
This change fixes this issue by passing the optimizer to the `update`
method of trainable pipes, leading to use of the second strategy
outlined above.
The main updating loop in `Language.update` is also simplified by using
the `TrainableComponent` protocol consistently.
* Train loop: `sgd` is `Optional[Optimizer]`, do not pass false
* Language.update: call pipe finish_update after all pipe updates
This does correct and fast updates if multiple components update the
same parameters.
* Add comment why we moved `finish_update` to a separate loop
* change logging call for spacy.LookupsDataLoader.v1
* substitutions in language and _util
* various more substitutions
* add string formatting guidelines to contribution guidelines
* 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
