* Add `training.before_update` callback
This callback can be used to implement training paradigms like gradual (un)freezing of components (e.g: the Transformer) after a certain number of training steps to mitigate catastrophic forgetting during fine-tuning.
* Fix type annotation, default config value
* Generalize arguments passed to the callback
* Update schema
* Pass `epoch` to callback, rename `current_step` to `step`
* Add test
* Simplify test
* Replace config string with `spacy.blank`
* Apply suggestions from code review
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Cleanup imports
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Check textcat values for validity
* Fix error numbers
* Clean up vals reference
* Check category value validity through training
The _validate_categories is called in update, which for multilabel is
inherited from the single label component.
* Formatting
* Add equality definition for vectors
This re-uses the check from sourcing components.
* Use the equality check
* Format
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Fix typos, add couple of new abbreviations, remove nonbreaking spaces
* Remove space from abbreviation
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update warning, add tests for project requirements check
* Make warning more general for differences between PEP 508 and pip
* Add tests for _check_requirements
* Parameterize test
* Add fallback in requirements check, only check once
* Rename to skip_requirements_check
* Update spacy/cli/project/run.py
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
* Fix default parameters for load functions
Some load functions used SimpleFrozenList() directly instead of the
_DEFAULT_EMPTY_PIPES parameter. That mostly worked as intended, but
the changes in #11459 check for equality using identity, not value, so a
warning is incorrectly raised sometimes, as in #11706.
This change just has all the load functions use the singleton value
instead.
* Add test that there are no warnings on module-based load
This will succeed due to changes in this branch, but local tests with
the latest release failed as intended.
* Try reverting commit and see if CI changes
There is an error in CI that is probably unrelated.
Revert "Fix default parameters for load functions"
This reverts commit dc46b35687.
* Revert "Try reverting commit and see if CI changes"
This reverts commit 2514ed07ef.
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Use `build` instead of `python setup.py sdist`
* Remove in-place build with `setup.py`
* Remove `gpu` parameter and GPU tests
* Keep `architecture` and `num_build_jobs` in azure steps with CI
defaults
* Fix use of `num_build_jobs` parameters
* Remove now-unused `prefix` parameter
* Test imports and CLI before installing test requirements
* Remove `*.egg-info` directory in addition to source directory for an
warning-free `import spacy`
* Switch `thinc-apple-ops` test to python 3.11 (as most recent python
that is tested across platforms)
* Update textcat scorer threshold behavior
For `textcat` (with exclusive classes) the scorer should always use a
threshold of 0.0 because there should be one predicted label per doc and
the numeric score for that particular label should not matter.
* Rename to test_textcat_multilabel_threshold
* Remove all uses of threshold for multi_label=False
* Update Scorer.score_cats API docs
* Add tests for score_cats with thresholds
* Update textcat API docs
* Fix types
* Convert threshold back to float
* Fix threshold type in docstring
* Improve formatting in Scorer API docs
* Handle docs with no entities
If a whole batch contains no entities it won't make it to the model, but
it's possible for individual Docs to have no entities. Before this
commit, those Docs would cause an error when attempting to concatenate
arrays because the dimensions didn't match.
It turns out the process of preparing the Ragged at the end of the span
maker forward was a little different from list2ragged, which just uses
the flatten function directly. Letting list2ragged do the conversion
avoids the dimension issue.
This did not come up before because in NEL demo projects it's typical
for data with no entities to be discarded before it reaches the NEL
component.
This includes a simple direct test that shows the issue and checks it's
resolved. It doesn't check if there are any downstream changes, so a
more complete test could be added. A full run was tested by adding an
example with no entities to the Emerson sample project.
* Add a blank instance to default training data in tests
Rather than adding a specific test, since not failing on instances with
no entities is basic functionality, it makes sense to add it to the
default set.
* Fix without modifying architecture
If the architecture is modified this would have to be a new version, but
this change isn't big enough to merit that.
