* 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>
* 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
* 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
* standardize predicate key format
* single key function
* Make optional args in key function keyword-only
---------
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Fix FUZZY operator definition
The default length of the FUZZY operator is 2 and not 3.
* adjust edit distance in matcher usage docs too
---------
Co-authored-by: svlandeg <svlandeg@github.com>
* 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
* 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>
* 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
* Init
* fix tests
* Update spacy/errors.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Fix test_blank_languages
* Rename xx to mul in docs
* Format _util with black
* prettier formatting
---------
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Language.distill: copy both reference and predicted
In distillation we also modify the teacher docs (e.g. in tok2vec
components), so we need to copy both the reference and predicted doc.
Problem caught by @shadeMe
* Make new `_copy_examples` args kwonly
