* fix grad_clip naming
* cleaning up pretrained_vectors out of cfg
* further refactoring Model init's
* move Model building out of pipes
* further refactor to require a model config when creating a pipe
* small fixes
* making cfg in nn_parser more consistent
* fixing nr_class for parser
* fixing nn_parser's nO
* fix printing of loss
* architectures in own file per type, consistent naming
* convenience methods default_tagger_config and default_tok2vec_config
* let create_pipe access default config if available for that component
* default_parser_config
* move defaults to separate folder
* allow reading nlp from package or dir with argument 'name'
* architecture spacy.VocabVectors.v1 to read static vectors from file
* cleanup
* default configs for nel, textcat, morphologizer, tensorizer
* fix imports
* fixing unit tests
* fixes and clean up
* fixing defaults, nO, fix unit tests
* restore parser IO
* fix IO
* 'fix' serialization test
* add *.cfg to manifest
* fix example configs with additional arguments
* replace Morpohologizer with Tagger
* add IO bit when testing overfitting of tagger (currently failing)
* fix IO - don't initialize when reading from disk
* expand overfitting tests to also check IO goes OK
* remove dropout from HashEmbed to fix Tagger performance
* add defaults for sentrec
* update thinc
* always pass a Model instance to a Pipe
* fix piped_added statement
* remove obsolete W029
* remove obsolete errors
* restore byte checking tests (work again)
* clean up test
* further test cleanup
* convert from config to Model in create_pipe
* bring back error when component is not initialized
* cleanup
* remove calls for nlp2.begin_training
* use thinc.api in imports
* allow setting charembed's nM and nC
* fix for hardcoded nM/nC + unit test
* formatting fixes
* trigger build
* Switch to train_dataset() function in train CLI
* Fixes for pipe() methods in pipeline components
* Don't clobber `examples` variable with `as_example` in pipe() methods
* Remove unnecessary traversals of `examples`
* Update Parser.pipe() for Examples
* Add `as_examples` kwarg to `pipe()` with implementation to return
`Example`s
* Accept `Doc` or `Example` in `pipe()` with `_get_doc()` (copied from
`Pipe`)
* Fixes to Example implementation in spacy.gold
* Move `make_projective` from an attribute of Example to an argument of
`Example.get_gold_parses()`
* Head of 0 are not treated as unset
* Unset heads are set to self rather than `None` (which causes problems
while projectivizing)
* Check for `Doc` (not just not `None`) when creating GoldParses for
pre-merged example
* Don't clobber `examples` variable in `iter_gold_docs()`
* Add/modify gold tests for handling projectivity
* In JSON roundtrip compare results from `dev_dataset` rather than
`train_dataset` to avoid projectivization (and other potential
modifications)
* Add test for projective train vs. nonprojective dev versions of the
same `Doc`
* Handle ignore_misaligned as arg rather than attr
Move `ignore_misaligned` from an attribute of `Example` to an argument
to `Example.get_gold_parses()`, which makes it parallel to
`make_projective`.
Add test with old and new align that checks whether `ignore_misaligned`
errors are raised as expected (only for new align).
* Remove unused attrs from gold.pxd
Remove `ignore_misaligned` and `make_projective` from `gold.pxd`
* Restructure Example with merged sents as default
An `Example` now includes a single `TokenAnnotation` that includes all
the information from one `Doc` (=JSON `paragraph`). If required, the
individual sentences can be returned as a list of examples with
`Example.split_sents()` with no raw text available.
* Input/output a single `Example.token_annotation`
* Add `sent_starts` to `TokenAnnotation` to handle sentence boundaries
* Replace `Example.merge_sents()` with `Example.split_sents()`
* Modify components to use a single `Example.token_annotation`
* Pipeline components
* conllu2json converter
* Rework/rename `add_token_annotation()` and `add_doc_annotation()` to
`set_token_annotation()` and `set_doc_annotation()`, functions that set
rather then appending/extending.
* Rename `morphology` to `morphs` in `TokenAnnotation` and `GoldParse`
* Add getters to `TokenAnnotation` to supply default values when a given
attribute is not available
* `Example.get_gold_parses()` in `spacy.gold._make_golds()` is only
applied on single examples, so the `GoldParse` is returned saved in the
provided `Example` rather than creating a new `Example` with no other
internal annotation
* Update tests for API changes and `merge_sents()` vs. `split_sents()`
* Refer to Example.goldparse in iter_gold_docs()
Use `Example.goldparse` in `iter_gold_docs()` instead of `Example.gold`
because a `None` `GoldParse` is generated with ignore_misaligned and
generating it on-the-fly can raise an unwanted AlignmentError
* Fix make_orth_variants()
Fix bug in make_orth_variants() related to conversion from multiple to
one TokenAnnotation per Example.
* Add basic test for make_orth_variants()
* Replace try/except with conditionals
* Replace default morph value with set
* OrigAnnot class instead of gold.orig_annot list of zipped tuples
* from_orig to replace from_annot_tuples
* rename to RawAnnot
* some unit tests for GoldParse creation and internal format
* removing orig_annot and switching to lists instead of tuple
* rewriting tuples to use RawAnnot (+ debug statements, WIP)
* fix pop() changing the data
* small fixes
* pop-append fixes
* return RawAnnot for existing GoldParse to have uniform interface
* clean up imports
* fix merge_sents
* add unit test for 4402 with new structure (not working yet)
* introduce DocAnnot
* typo fixes
* add unit test for merge_sents
* rename from_orig to from_raw
* fixing unit tests
* fix nn parser
* read_annots to produce text, doc_annot pairs
* _make_golds fix
* rename golds_to_gold_annots
* small fixes
* fix encoding
* have golds_to_gold_annots use DocAnnot
* missed a spot
* merge_sents as function in DocAnnot
* allow specifying only part of the token-level annotations
* refactor with Example class + underlying dicts
* pipeline components to work with Example objects (wip)
* input checking
* fix yielding
* fix calls to update
* small fixes
* fix scorer unit test with new format
* fix kwargs order
* fixes for ud and conllu scripts
* fix reading data for conllu script
* add in proper errors (not fixed numbering yet to avoid merge conflicts)
* fixing few more small bugs
* fix EL script
* Implement new API for {Phrase}Matcher.add (backwards-compatible)
* Update docs
* Also update DependencyMatcher.add
* Update internals
* Rewrite tests to use new API
* Add basic check for common mistake
Raise error with suggestion if user likely passed in a pattern instead of a list of patterns
* Fix typo [ci skip]
* Move test
* Allow default in Lookups.get_table
* Start with blank tables in Lookups.from_bytes
* Refactor lemmatizer to hold instance of Lookups
* Get lookups table within the lemmatization methods to make sure it references the correct table (even if the table was replaced or modified, e.g. when loading a model from disk)
* Deprecate other arguments on Lemmatizer.__init__ and expect Lookups for consistency
* Remove old and unsupported Lemmatizer.load classmethod
* Refactor language-specific lemmatizers to inherit as much as possible from base class and override only what they need
* Update tests and docs
* Fix more tests
* Fix lemmatizer
* Upgrade pytest to try and fix weird CI errors
* Try pytest 4.6.5
The doc.retokenize() context manager wasn't resizing doc.tensor, leading to a mismatch between the number of tokens in the doc and the number of rows in the tensor. We fix this by deleting rows from the tensor. Merged spans are represented by the vector of their last token.
* Add test for resizing doc.tensor when merging
* Add test for resizing doc.tensor when merging. Closes#1963
* Update get_lca_matrix test for develop
* Fix retokenize if tensor unset
* Auto-format tests with black
* Add flake8 config
* Tidy up and remove unused imports
* Fix redefinitions of test functions
* Replace orths_and_spaces with words and spaces
* Fix compatibility with pytest 4.0
* xfail test for now
Test was previously overwritten by following test due to naming conflict, so failure wasn't reported
* Unfail passing test
* Only use fixture via arguments
Fixes pytest 4.0 compatibility
## Description
Related issues: #2379 (should be fixed by separating model tests)
* **total execution time down from > 300 seconds to under 60 seconds** 🎉
* removed all model-specific tests that could only really be run manually anyway – those will now live in a separate test suite in the [`spacy-models`](https://github.com/explosion/spacy-models) repository and are already integrated into our new model training infrastructure
* changed all relative imports to absolute imports to prepare for moving the test suite from `/spacy/tests` to `/tests` (it'll now always test against the installed version)
* merged old regression tests into collections, e.g. `test_issue1001-1500.py` (about 90% of the regression tests are very short anyways)
* tidied up and rewrote existing tests wherever possible
### Todo
- [ ] move tests to `/tests` and adjust CI commands accordingly
- [x] move model test suite from internal repo to `spacy-models`
- [x] ~~investigate why `pipeline/test_textcat.py` is flakey~~
- [x] review old regression tests (leftover files) and see if they can be merged, simplified or deleted
- [ ] update documentation on how to run tests
### Types of change
enhancement, tests
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
