* Update numpy build constraints for numpy 1.25
Starting in numpy 1.25 (see
https://github.com/numpy/numpy/releases/tag/v1.25.0), the numpy C API is
backwards-compatible by default.
For python 3.9+, we should be able to drop the specific numpy build
requirements and use `numpy>=1.25`, which is currently
backwards-compatible to `numpy>=1.19`.
In the future, the python <3.9 requirements could be dropped and the
lower numpy pin could correspond to the oldest supported version for the
current lower python pin.
* Turn off fail-fast
* Revert "Turn off fail-fast"
This reverts commit 4306f516bc.
* Update for python 3.6
* Fix typo
* Setting up weasel branch (#12456)
* remove project-specific functionality
* remove project-specific tests
* remove project-specific schemas
* remove project-specific information in about
* remove project-specific functions in util.py
* remove project-specific error strings
* remove project-specific CLI commands
* black formatting
* restore some functions that are used beyond projects
* remove project imports
* remove imports
* remove remote_storage tests
* remove one more project unit test
* update for PR 12394
* remove get_hash and get_checksum
* remove upload_ and download_file methods
* remove ensure_pathy
* revert clumsy fingers
* reinstate E970
* feat: use weasel as spacy project command (#12473)
* feat: use weasel as spacy project command
* build: use constrained requirement for weasel
* feat: add weasel to the library requirements
* build: update weasel to new version
* build: use specific weasel tag
* build: use weasel-0.1.0rc1 from PyPI
* fix: remove weasel from requirements.txt
* fix: requirements.txt and setup.cfg need to reflect each other
* feat: remove legacy spacy project code
* bump version
* further merge fixes
* isort
---------
Co-authored-by: Basile Dura <bdura@users.noreply.github.com>
* Change GPU efficient textcat to use CNN, not BOW
If you generate a config with a textcat component using GPU
(transformers), the defaut option (efficiency) uses a BOW architecture,
which does not use tok2vec features. While that can make sense as part
of a larger pipeline, in the case of just a transformer and a textcat,
that means the transformer is doing a lot of work for no purpose.
This changes it so that the CNN architecture is used instead. It could
also be changed to be the same as the accuracy config, which uses the
ensemble architecture.
* Add the transformer when using a textcat with GPU
* Switch ubuntu-latest to ubuntu-20.04 in main tests (#11928)
* Switch ubuntu-latest to ubuntu-20.04 in main tests
* Only use 20.04 for 3.6
* Require thinc v8.1.7
* Require thinc v8.1.8
* Break up longer expression
---------
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Extend to wasabi v1.1
* Temporarily run mypy and tests with newest wasabi
* Temporarily skip check requirements test
* Revert "Temporarily skip check requirements test"
This reverts commit 44f4ce20a8.
* Revert "Temporarily run mypy and tests with newest wasabi"
This reverts commit e677a2257c.
* Support local filesystem remotes for projects
* Fix support for local filesystem remotes for projects
* Use `FluidPath` instead of `Pathy` to support both filesystem and
remote paths
* Create missing parent directories if required for local filesystem
* Add a more general `_file_exists` method to support both `Pathy`,
`Path`, and `smart_open`-compatible URLs
* Add explicit `smart_open` dependency starting with support for
`compression` flag
* Update `pathy` dependency to exclude older versions that aren't
compatible with required `smart_open` version
* Update docs to refer to `Pathy` instead of `smart_open` for project
remotes (technically you can still push to any `smart_open`-compatible
path but you can't pull from them)
* Add tests for local filesystem remotes
* Update pathy for general BlobStat sorting
* Add import
* Remove _file_exists since only Pathy remotes are supported
* Format CLI docs
* Clean up merge
* Update cupy extras:
* Extend to v11
* Add `cupy-cuda11x` and `cupy-wheel`
* Update quickstart to use `cupy-wheel` for CUDA 10.2+
* Rename cuda-wheel to cuda-autodetect, remove repeated CUDA in menu
* Add cuda116 and cuda117 extras
* Revert "remove `cuda116` extra from install widget (#11012)"
This reverts commit e7b498fb1f.
* Add cuda117 to quickstart
* Use thinc-apple-ops>=0.1.0.dev0 with `apple` extras
Also test with thinc-apple-ops that is at least 0.1.0.dev0.
* Check thinc-apple-ops on macOS with Python 3.10
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Use `pip install --pre` for installing thinc-apple-ops in CI
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Parser: use C saxpy/sgemm provided by the Ops implementation
This is a backport of https://github.com/explosion/spaCy/pull/10747
from the parser refactor branch. It eliminates the explicit calls
to BLIS, instead using the saxpy/sgemm provided by the Ops
implementation.
This allows us to use Accelerate in the parser on M1 Macs (with
an updated thinc-apple-ops).
Performance of the de_core_news_lg pipe:
BLIS 0.7.0, no thinc-apple-ops: 6385 WPS
BLIS 0.7.0, thinc-apple-ops: 36455 WPS
BLIS 0.9.0, no thinc-apple-ops: 19188 WPS
BLIS 0.9.0, thinc-apple-ops: 36682 WPS
This PR, thinc-apple-ops: 38726 WPS
Performance of the de_core_news_lg pipe (only tok2vec -> parser):
BLIS 0.7.0, no thinc-apple-ops: 13907 WPS
BLIS 0.7.0, thinc-apple-ops: 73172 WPS
BLIS 0.9.0, no thinc-apple-ops: 41576 WPS
BLIS 0.9.0, thinc-apple-ops: 72569 WPS
This PR, thinc-apple-ops: 87061 WPS
* Require thinc >=8.1.0,<8.2.0
* Lower thinc lowerbound to 8.1.0.dev0
* Use best CPU ops for CBLAS when the parser model is on the GPU
* Fix another unguarded cblas() call
* Fix: use ops as a shorthand for self.model.ops
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Make changes to typing
* Correction
* Format with black
* Corrections based on review
* Bumped Thinc dependency version
* Bumped blis requirement
* Correction for older Python versions
* Update spacy/ml/models/textcat.py
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
* Corrections based on review feedback
* Readd deleted docstring line
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
* Add initial design for diff command
For now, the diffing process looks like this:
- The default config is created based from some values in the user
config (e.g. which pipeline components were used, the lang, etc.)
- The user must supply manually if it was optimized for acc/efficiency
and if pretraining was involved.
* Make diff command structure similar to siblings
* Include gpu as a user option for CLI
* Make variables more explicit
* Fix type declaration for optimize enum
* Improve docstrings for diff CLI
* Add debug-diff to website API docs
* Switch position of configs so that user config is modded
* Add markdown flag for debug diff
This commit adds a --markdown (--md) flag that allows easier
copy-pasting to Github issues. Please note that this commit is dependent
on an unreleased version of wasabi (for the time being).
For posterity, the related PR is found here: https://github.com/ines/wasabi/pull/20
* Bump version of wasabi to 0.9.1
So that we can use the add_symbols parameter.
* Apply suggestions from code review
Co-authored-by: Ines Montani <ines@ines.io>
* Update docs based on code review suggestions
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Change command name from diff -> diff-config
* Clarify when options are relevant or not
* Rerun prettier on cli.md
Co-authored-by: Ines Montani <ines@ines.io>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Tagger: use unnormalized probabilities for inference
Using unnormalized softmax avoids use of the relatively expensive exp function,
which can significantly speed up non-transformer models (e.g. I got a speedup
of 27% on a German tagging + parsing pipeline).
* Add spacy.Tagger.v2 with configurable normalization
Normalization of probabilities is disabled by default to improve
performance.
* Update documentation, models, and tests to spacy.Tagger.v2
* Move Tagger.v1 to spacy-legacy
* docs/architectures: run prettier
* Unnormalized softmax is now a Softmax_v2 option
* Require thinc 8.0.14 and spacy-legacy 3.0.9
* Partial fix of entity linker batching
* Add import
* Better name
* Add `use_gold_ents` option, docs
* Change to v2, create stub v1, update docs etc.
* Fix error type
Honestly no idea what the right type to use here is.
ConfigValidationError seems wrong. Maybe a NotImplementedError?
* Make mypy happy
* Add hacky fix for init issue
* Add legacy pipeline entity linker
* Fix references to class name
* Add __init__.py for legacy
* Attempted fix for loss issue
* Remove placeholder V1
* formatting
* slightly more interesting train data
* Handle batches with no usable examples
This adds a test for batches that have docs but not entities, and a
check in the component that detects such cases and skips the update step
as thought the batch were empty.
* Remove todo about data verification
Check for empty data was moved further up so this should be OK now - the
case in question shouldn't be possible.
* Fix gradient calculation
The model doesn't know which entities are not in the kb, so it generates
embeddings for the context of all of them.
However, the loss does know which entities aren't in the kb, and it
ignores them, as there's no sensible gradient.
This has the issue that the gradient will not be calculated for some of
the input embeddings, which causes a dimension mismatch in backprop.
That should have caused a clear error, but with numpyops it was causing
nans to happen, which is another problem that should be addressed
separately.
This commit changes the loss to give a zero gradient for entities not in
the kb.
* add failing test for v1 EL legacy architecture
* Add nasty but simple working check for legacy arch
* Clarify why init hack works the way it does
* Clarify use_gold_ents use case
* Fix use gold ents related handling
* Add tests for no gold ents and fix other tests
* Use aligned ents function (not working)
This doesn't actually work because the "aligned" ents are gold-only. But
if I have a different function that returns the intersection, *then*
this will work as desired.
* Use proper matching ent check
This changes the process when gold ents are not used so that the
intersection of ents in the pred and gold is used.
* Move get_matching_ents to Example
* Use model attribute to check for legacy arch
* Rename flag
* bump spacy-legacy to lower 3.0.9
Co-authored-by: svlandeg <svlandeg@github.com>
By @polm, redone from #9917 after incorrect (reverted) rebase.
`sudachipy>=0.5.2` is needed for newer dictionaries. `sudachipy<0.6.0`
is kept for users who might still prefer the older version, in
particular to be able to compile it without rust.
* Edited Slovenian stop words list (#9707)
* Noun chunks for Italian (#9662)
* added it vocab
* copied portuguese
* added possessive determiner
* added conjed Nps
* added nmoded Nps
* test misc
* more examples
* fixed typo
* fixed parenth
* fixed comma
* comma fix
* added syntax iters
* fix some index problems
* fixed index
* corrected heads for test case
* fixed tets case
* fixed determiner gender
* cleaned left over
* added example with apostophe
* French NP review (#9667)
* adapted from pt
* added basic tests
* added fr vocab
* fixed noun chunks
* more examples
* typo fix
* changed naming
* changed the naming
* typo fix
* Add Japanese kana characters to default exceptions (fix#9693) (#9742)
This includes the main kana, or phonetic characters, used in Japanese.
There are some supplemental kana blocks in Unicode outside the BMP that
could also be included, but because their actual use is rare I omitted
them for now, but maybe they should be added. The omitted blocks are:
- Kana Supplement
- Kana Extended (A and B)
- Small Kana Extension
* Remove NER words from stop words in Norwegian (#9820)
Default stop words in Norwegian bokmål (nb) in Spacy contain important entities, e.g. France, Germany, Russia, Sweden and USA, police district, important units of time, e.g. months and days of the week, and organisations.
Nobody expects their presence among the default stop words. There is a danger of users complying with the general recommendation of filtering out stop words, while being unaware of filtering out important entities from their data.
See explanation in https://github.com/explosion/spaCy/issues/3052#issuecomment-986756711 and comment https://github.com/explosion/spaCy/issues/3052#issuecomment-986951831
* Bump sudachipy version
* Update sudachipy versions
* Bump versions
Bumping to the most recent dictionary just to keep thing current.
Bumping sudachipy to 5.2 because older versions don't support recent
dictionaries.
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Richard Hudson <richard@explosion.ai>
Co-authored-by: Duygu Altinok <duygu@explosion.ai>
Co-authored-by: Haakon Meland Eriksen <haakon.eriksen@far.no>
