* 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>
* Add the configuration schema for distillation
This also adds the default configuration and some tests. The schema will
be used by the training loop and `distill` subcommand.
* Format
* Change distillation shortopt to -d
* Fix descripion of max_epochs
* Rename distillation flag to -dt
* Rename `pipe_map` to `student_to_teacher`
* Add `Language.distill`
This method is the distillation counterpart of `Language.update`. It
takes a teacher `Language` instance and distills the student pipes on
the teacher pipes.
* Apply suggestions from code review
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Clarify that how Example is used in distillation
* Update transition parser distill docstring for examples argument
* Pass optimizer to `TrainablePipe.distill`
* Annotate pipe before update
As discussed internally, we want to let a pipe annotate before doing an
update with gold/silver data. Otherwise, the output may be (too)
informed by the gold/silver data.
* Rename `component_map` to `student_to_teacher`
* Better synopsis in `Language.distill` docstring
* `name` -> `student_name`
* Fix labels type in docstring
* Mark distill test as slow
* Fix `student_to_teacher` type in docs
---------
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Normalize whitespace in evaluate CLI output test
Depending on terminal settings, lines may be padded to the screen width
so the comparison is too strict with only the command string replacement.
* Move to test util method
* Change to normalization method
* Add span_id to Span.char_span, update Doc/Span.char_span docs
`Span.char_span(id=)` should be removed in the future.
* Also use Union[int, str] in Doc docstring
* WIP
* rm ipython embeds
* rm total
* WIP
* cleanup
* cleanup + reword
* rm component function
* remove migration support form
* fix reference dataset for dev data
* additional fixes
- set approach to identifying unique trees
- adjust line length on messages
- add logic for detecting docs without annotations
* use 0 instead of none for no annotation
* partial annotation support
* initial tests for _compile_gold lemma attributes
Using the example data from the edit tree lemmatizer tests for:
- lemmatizer_trees
- partial_lemma_annotations
- n_low_cardinality_lemmas
- no_lemma_annotations
* adds output test for cli app
* switch msg level
* rm unclear uniqueness check
* Revert "rm unclear uniqueness check"
This reverts commit 6ea2b3524b.
* remove good message on uniqueness
* formatting
* use en_vocab fixture
* clarify data set source in messages
* remove unnecessary import
Co-authored-by: svlandeg <svlandeg@github.com>
* Add `spacy.PlainTextCorpusReader.v1`
This is a corpus reader that reads plain text corpora with the following
format:
- UTF-8 encoding
- One line per document.
- Blank lines are ignored.
It is useful for applications where we deal with very large corpora,
such as distillation, and don't want to deal with the space overhead of
serialized formats. Additionally, many large corpora already use such
a text format, keeping the necessary preprocessing to a minimum.
* Update spacy/training/corpus.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* docs: add version to `PlainTextCorpus`
* Add docstring to registry function
* Add plain text corpus tests
* Only strip newline/carriage return
* Add return type _string_to_tmp_file helper
* Use a temporary directory in place of file name
Different OS auto delete/sharing semantics are just wonky.
* This will be new in 3.5.1 (rather than 4)
* Test improvements from code review
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Refactor _scores2guesses
* Handle arrays on GPU
* Convert argmax result to raw integer
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Use NumpyOps() to copy data to CPU
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Changes based on review comments
* Use different _scores2guesses depending on tree_k
* Add tests for corner cases
* Add empty line for consistency
* Improve naming
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
* Improve naming
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
* Fix batching regression
Some time ago, the spaCy v4 branch switched to the new Thinc v9
schedule. However, this introduced an error in how batching is handed.
In the PR, the batchers were changed to keep track of their step,
so that the step can be passed to the schedule. However, the issue
is that the training loop repeatedly calls the batching functions
(rather than using an infinite generator/iterator). So, the step and
therefore the schedule would be reset each epoch. Before the schedule
switch we didn't have this issue, because the old schedules were
stateful.
This PR fixes this issue by reverting the batching functions to use
a (stateful) generator. Their registry functions do accept a `Schedule`
and we convert `Schedule`s to generators.
* Update batcher docs
* Docstring fixes
* Make minibatch take iterables again as well
* Bump thinc requirement to 9.0.0.dev2
* Use type declaration
* Convert another comment into a proper type declaration
* Try to fix doc.copy
* Set dev version
* Make vocab always own lexemes
* Change version
* Add SpanGroups.copy method
* Fix set_annotations during Parser.update
* Fix dict proxy copy
* Upd version
* Fix copying SpanGroups
* Fix set_annotations in parser.update
* Fix parser set_annotations during update
* Revert "Fix parser set_annotations during update"
This reverts commit eb138c89ed.
* Revert "Fix set_annotations in parser.update"
This reverts commit c6df0eafd0.
* Fix set_annotations during parser update
* Inc version
* Handle final states in get_oracle_sequence
* Inc version
* Try to fix parser training
* Inc version
* Fix
* Inc version
* Fix parser oracle
* Inc version
* Inc version
* Fix transition has_gold
* Inc version
* Try to use real histories, not oracle
* Inc version
* Upd parser
* Inc version
* WIP on rewrite parser
* WIP refactor parser
* New progress on parser model refactor
* Prepare to remove parser_model.pyx
* Convert parser from cdef class
* Delete spacy.ml.parser_model
* Delete _precomputable_affine module
* Wire up tb_framework to new parser model
* Wire up parser model
* Uncython ner.pyx and dep_parser.pyx
* Uncython
* Work on parser model
* Support unseen_classes in parser model
* Support unseen classes in parser
* Cleaner handling of unseen classes
* Work through tests
* Keep working through errors
* Keep working through errors
* Work on parser. 15 tests failing
* Xfail beam stuff. 9 failures
* More xfail. 7 failures
* Xfail. 6 failures
* cleanup
* formatting
* fixes
* pass nO through
* Fix empty doc in update
* Hackishly fix resizing. 3 failures
* Fix redundant test. 2 failures
* Add reference version
* black formatting
* Get tests passing with reference implementation
* Fix missing prints
* Add missing file
* Improve indexing on reference implementation
* Get non-reference forward func working
* Start rigging beam back up
* removing redundant tests, cf #8106
* black formatting
* temporarily xfailing issue 4314
* make flake8 happy again
* mypy fixes
* ensure labels are added upon predict
* cleanup remnants from merge conflicts
* Improve unseen label masking
Two changes to speed up masking by ~10%:
- Use a bool array rather than an array of float32.
- Let the mask indicate whether a label was seen, rather than
unseen. The mask is most frequently used to index scores for
seen labels. However, since the mask marked unseen labels,
this required computing an intermittent flipped mask.
* Write moves costs directly into numpy array (#10163)
This avoids elementwise indexing and the allocation of an additional
array.
Gives a ~15% speed improvement when using batch_by_sequence with size
32.
* Temporarily disable ner and rehearse tests
Until rehearse is implemented again in the refactored parser.
* Fix loss serialization issue (#10600)
* Fix loss serialization issue
Serialization of a model fails with:
TypeError: array(738.3855, dtype=float32) is not JSON serializable
Fix this using float conversion.
* Disable CI steps that require spacy.TransitionBasedParser.v2
After finishing the refactor, TransitionBasedParser.v2 should be
provided for backwards compat.
* Add back support for beam parsing to the refactored parser (#10633)
* Add back support for beam parsing
Beam parsing was already implemented as part of the `BeamBatch` class.
This change makes its counterpart `GreedyBatch`. Both classes are hooked
up in `TransitionModel`, selecting `GreedyBatch` when the beam size is
one, or `BeamBatch` otherwise.
* Use kwarg for beam width
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Avoid implicit default for beam_width and beam_density
* Parser.{beam,greedy}_parse: ensure labels are added
* Remove 'deprecated' comments
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Parser `StateC` optimizations (#10746)
* `StateC`: Optimizations
Avoid GIL acquisition in `__init__`
Increase default buffer capacities on init
Reduce C++ exception overhead
* Fix typo
* Replace `set::count` with `set::find`
* Add exception attribute to c'tor
* Remove unused import
* Use a power-of-two value for initial capacity
Use default-insert to init `_heads` and `_unshiftable`
* Merge `cdef` variable declarations and assignments
* Vectorize `example.get_aligned_parses` (#10789)
* `example`: Vectorize `get_aligned_parse`
Rename `numpy` import
* Convert aligned array to lists before returning
* Revert import renaming
* Elide slice arguments when selecting the entire range
* Tagger/morphologizer alignment performance optimizations (#10798)
* `example`: Unwrap `numpy` scalar arrays before passing them to `StringStore.__getitem__`
* `AlignmentArray`: Use native list as staging buffer for offset calculation
* `example`: Vectorize `get_aligned`
* Hoist inner functions out of `get_aligned`
* Replace inline `if..else` clause in assignment statement
* `AlignmentArray`: Use raw indexing into offset and data `numpy` arrays
* `example`: Replace array unique value check with `groupby`
* `example`: Correctly exclude tokens with no alignment in `_get_aligned_vectorized`
Simplify `_get_aligned_non_vectorized`
* `util`: Update `all_equal` docstring
* Explicitly use `int32_t*`
* Restore C CPU inference in the refactored parser (#10747)
* Bring back the C parsing model
The C parsing model is used for CPU inference and is still faster for
CPU inference than the forward pass of the Thinc model.
* Use C sgemm provided by the Ops implementation
* Make tb_framework module Cython, merge in C forward implementation
* TransitionModel: raise in backprop returned from forward_cpu
* Re-enable greedy parse test
* Return transition scores when forward_cpu is used
* Apply suggestions from code review
Import `Model` from `thinc.api`
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Use relative imports in tb_framework
* Don't assume a default for beam_width
* We don't have a direct dependency on BLIS anymore
* Rename forwards to _forward_{fallback,greedy_cpu}
* Require thinc >=8.1.0,<8.2.0
* tb_framework: clean up imports
* Fix return type of _get_seen_mask
* Move up _forward_greedy_cpu
* Style fixes.
* Lower thinc lowerbound to 8.1.0.dev0
* Formatting fix
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Reimplement parser rehearsal function (#10878)
* Reimplement parser rehearsal function
Before the parser refactor, rehearsal was driven by a loop in the
`rehearse` method itself. For each parsing step, the loops would:
1. Get the predictions of the teacher.
2. Get the predictions and backprop function of the student.
3. Compute the loss and backprop into the student.
4. Move the teacher and student forward with the predictions of
the student.
In the refactored parser, we cannot perform search stepwise rehearsal
anymore, since the model now predicts all parsing steps at once.
Therefore, rehearsal is performed in the following steps:
1. Get the predictions of all parsing steps from the student, along
with its backprop function.
2. Get the predictions from the teacher, but use the predictions of
the student to advance the parser while doing so.
3. Compute the loss and backprop into the student.
To support the second step a new method, `advance_with_actions` is
added to `GreedyBatch`, which performs the provided parsing steps.
* tb_framework: wrap upper_W and upper_b in Linear
Thinc's Optimizer cannot handle resizing of existing parameters. Until
it does, we work around this by wrapping the weights/biases of the upper
layer of the parser model in Linear. When the upper layer is resized, we
copy over the existing parameters into a new Linear instance. This does
not trigger an error in Optimizer, because it sees the resized layer as
a new set of parameters.
* Add test for TransitionSystem.apply_actions
* Better FIXME marker
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
* Fixes from Madeesh
* Apply suggestions from Sofie
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Remove useless assignment
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Rename some identifiers in the parser refactor (#10935)
* Rename _parseC to _parse_batch
* tb_framework: prefix many auxiliary functions with underscore
To clearly state the intent that they are private.
* Rename `lower` to `hidden`, `upper` to `output`
* Parser slow test fixup
We don't have TransitionBasedParser.{v1,v2} until we bring it back as a
legacy option.
* Remove last vestiges of PrecomputableAffine
This does not exist anymore as a separate layer.
* ner: re-enable sentence boundary checks
* Re-enable test that works now.
* test_ner: make loss test more strict again
* Remove commented line
* Re-enable some more beam parser tests
* Remove unused _forward_reference function
* Update for CBlas changes in Thinc 8.1.0.dev2
Bump thinc dependency to 8.1.0.dev3.
* Remove references to spacy.TransitionBasedParser.{v1,v2}
Since they will not be offered starting with spaCy v4.
* `tb_framework`: Replace references to `thinc.backends.linalg` with `CBlas`
* dont use get_array_module (#11056) (#11293)
Co-authored-by: kadarakos <kadar.akos@gmail.com>
* Move `thinc.extra.search` to `spacy.pipeline._parser_internals` (#11317)
* `search`: Move from `thinc.extra.search`
Fix NPE in `Beam.__dealloc__`
* `pytest`: Add support for executing Cython tests
Move `search` tests from thinc and patch them to run with `pytest`
* `mypy` fix
* Update comment
* `conftest`: Expose `register_cython_tests`
* Remove unused import
* Move `argmax` impls to new `_parser_utils` Cython module (#11410)
* Parser does not have to be a cdef class anymore
This also fixes validation of the initialization schema.
* Add back spacy.TransitionBasedParser.v2
* Fix a rename that was missed in #10878.
So that rehearsal tests pass.
* Remove module from setup.py that got added during the merge
* Bring back support for `update_with_oracle_cut_size` (#12086)
* Bring back support for `update_with_oracle_cut_size`
This option was available in the pre-refactor parser, but was never
implemented in the refactored parser. This option cuts transition
sequences that are longer than `update_with_oracle_cut` size into
separate sequences that have at most `update_with_oracle_cut`
transitions. The oracle (gold standard) transition sequence is used to
determine the cuts and the initial states for the additional sequences.
Applying this cut makes the batches more homogeneous in the transition
sequence lengths, making forward passes (and as a consequence training)
much faster.
Training time 1000 steps on de_core_news_lg:
- Before this change: 149s
- After this change: 68s
- Pre-refactor parser: 81s
* Fix a rename that was missed in #10878.
So that rehearsal tests pass.
* Apply suggestions from @shadeMe
* Use chained conditional
* Test with update_with_oracle_cut_size={0, 1, 5, 100}
And fix a git that occurs with a cut size of 1.
* Fix up some merge fall out
* Update parser distillation for the refactor
In the old parser, we'd iterate over the transitions in the distill
function and compute the loss/gradients on the go. In the refactored
parser, we first let the student model parse the inputs. Then we'll let
the teacher compute the transition probabilities of the states in the
student's transition sequence. We can then compute the gradients of the
student given the teacher.
* Add back spacy.TransitionBasedParser.v1 references
- Accordion in the architecture docs.
- Test in test_parse, but disabled until we have a spacy-legacy release.
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
Co-authored-by: svlandeg <svlandeg@github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: kadarakos <kadar.akos@gmail.com>
* Add `TrainablePipe.{distill,get_teacher_student_loss}`
This change adds two methods:
- `TrainablePipe::distill` which performs a training step of a
student pipe on a teacher pipe, giving a batch of `Doc`s.
- `TrainablePipe::get_teacher_student_loss` computes the loss
of a student relative to the teacher.
The `distill` or `get_teacher_student_loss` methods are also implemented
in the tagger, edit tree lemmatizer, and parser pipes, to enable
distillation in those pipes and as an example for other pipes.
* Fix stray `Beam` import
* Fix incorrect import
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* TrainablePipe.distill: use `Iterable[Example]`
* Add Pipe.is_distillable method
* Add `validate_distillation_examples`
This first calls `validate_examples` and then checks that the
student/teacher tokens are the same.
* Update distill documentation
* Add distill documentation for all pipes that support distillation
* Fix incorrect identifier
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add comment to explain `is_distillable`
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add a `spacy evaluate speed` subcommand
This subcommand reports the mean batch performance of a model on a data set with
a 95% confidence interval. For reliability, it first performs some warmup
rounds. Then it will measure performance on batches with randomly shuffled
documents.
To avoid having too many spaCy commands, `speed` is a subcommand of `evaluate`
and accuracy evaluation is moved to its own `evaluate accuracy` subcommand.
* Fix import cycle
* Restore `spacy evaluate`, make `spacy benchmark speed` an alias
* Add documentation for `spacy benchmark`
* CREATES -> PRINTS
* WPS -> words/s
* Disable formatting of benchmark speed arguments
* Fail with an error message when trying to speed bench empty corpus
* Make it clearer that `benchmark accuracy` is a replacement for `evaluate`
* Fix docstring webpage reference
* tests: check `evaluate` output against `benchmark accuracy`
In the v3 scorer refactoring, `token_acc` was implemented incorrectly.
It should use `precision` instead of `fscore` for the measure of
correctly aligned tokens / number of predicted tokens.
Fix the docs to reflect that the measure uses the number of predicted
tokens rather than the number of gold tokens.
* enable fuzzy matching
* add fuzzy param to EntityMatcher
* include rapidfuzz_capi
not yet used
* fix type
* add FUZZY predicate
* add fuzzy attribute list
* fix type properly
* tidying
* remove unnecessary dependency
* handle fuzzy sets
* simplify fuzzy sets
* case fix
* switch to FUZZYn predicates
use Levenshtein distance.
remove fuzzy param.
remove rapidfuzz_capi.
* revert changes added for fuzzy param
* switch to polyleven
(Python package)
* enable fuzzy matching
* add fuzzy param to EntityMatcher
* include rapidfuzz_capi
not yet used
* fix type
* add FUZZY predicate
* add fuzzy attribute list
* fix type properly
* tidying
* remove unnecessary dependency
* handle fuzzy sets
* simplify fuzzy sets
* case fix
* switch to FUZZYn predicates
use Levenshtein distance.
remove fuzzy param.
remove rapidfuzz_capi.
* revert changes added for fuzzy param
* switch to polyleven
(Python package)
* fuzzy match only on oov tokens
* remove polyleven
* exclude whitespace tokens
* don't allow more edits than characters
* fix min distance
* reinstate FUZZY operator
with length-based distance function
* handle sets inside regex operator
* remove is_oov check
* attempt build fix
no mypy failure locally
* re-attempt build fix
* don't overwrite fuzzy param value
* move fuzzy_match
to its own Python module to allow patching
* move fuzzy_match back inside Matcher
simplify logic and add tests
* Format tests
* Parametrize fuzzyn tests
* Parametrize and merge fuzzy+set tests
* Format
* Move fuzzy_match to a standalone method
* Change regex kwarg type to bool
* Add types for fuzzy_match
- Refactor variable names
- Add test for symmetrical behavior
* Parametrize fuzzyn+set tests
* Minor refactoring for fuzz/fuzzy
* Make fuzzy_match a Matcher kwarg
* Update type for _default_fuzzy_match
* don't overwrite function param
* Rename to fuzzy_compare
* Update fuzzy_compare default argument declarations
* allow fuzzy_compare override from EntityRuler
* define new Matcher keyword arg
* fix type definition
* Implement fuzzy_compare config option for EntityRuler and SpanRuler
* Rename _default_fuzzy_compare to fuzzy_compare, remove from reexported objects
* Use simpler fuzzy_compare algorithm
* Update types
* Increase minimum to 2 in fuzzy_compare to allow one transposition
* Fix predicate keys and matching for SetPredicate with FUZZY and REGEX
* Add FUZZY6..9
* Add initial docs
* Increase default fuzzy to rounded 30% of pattern length
* Update docs for fuzzy_compare in components
* Update EntityRuler and SpanRuler API docs
* Rename EntityRuler and SpanRuler setting to matcher_fuzzy_compare
To having naming similar to `phrase_matcher_attr`, rename
`fuzzy_compare` setting for `EntityRuler` and `SpanRuler` to
`matcher_fuzzy_compare. Organize next to `phrase_matcher_attr` in docs.
* Fix schema aliases
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Fix typo
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add FUZZY6-9 operators and update tests
* Parameterize test over greedy
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Fix type for fuzzy_compare to remove Optional
* Rename to spacy.levenshtein_compare.v1, move to spacy.matcher.levenshtein
* Update docs following levenshtein_compare renaming
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* check port in use and add itself
* check port in use and add itself
* Auto switch to nearest available port.
* Use bind to check port instead of connect_ex.
* Reformat.
* Add auto_select_port argument.
* update docs for displacy.serve
* Update spacy/errors.py
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
* Update website/docs/api/top-level.md
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
* Update spacy/errors.py
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
* Add test using multiprocessing
* fix argument name
* Increase sleep times
Want to rule this out as a cause of test failure
* Don't terminate a process that isn't alive
* Refactor port finding logic
This moves all the port logic into its own util function, which can be
tested without having to background a server directly.
* Use with for the server
This ensures the server is closed correctly.
* Pass in the host when checking port availability
* Shorten argument name
* Update error codes following merge
* Add types for arguments, specify docstrings.
* Add typing for arguments with default value.
* Update docstring to match spaCy format.
* Update docstring to match spaCy format.
* Fix docs
Arg name changed from `auto_select_port` to just `auto_select`.
* Revert "Fix docs"
This reverts commit 356966fe84.
Co-authored-by: zhiiw <1302593554@qq.com>
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
Co-authored-by: Raphael Mitsch <r.mitsch@outlook.com>
* add test for running evaluate on an nlp pipeline with two distinct textcat components
* cleanup
* merge dicts instead of overwrite
* don't add more labels to the given set
* Revert "merge dicts instead of overwrite"
This reverts commit 89bee0ed77.
* Switch tests to separate scorer keys rather than merged dicts
* Revert unrelated edits
* Switch textcat scorers to v2
* formatting
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* fix processing of "auto" in walk_directory
* add check for None
* move AUTO check to convert and fix verification of args
* add specific CLI test with CliRunner
* cleanup
* more cleanup
* update docstring
* Init
* Fix return type for mypy
* adjust types and improve setting new attributes
* Add underscore changes to json conversion
* Add test and underscore changes to from_docs
* add underscore changes and test to span.to_doc
* update return values
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add types to function
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* adjust formatting
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* shorten return type
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* add helper function to improve readability
* Improve code and add comments
* rerun azure tests
* Fix tests for json conversion
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Convert all individual values explicitly to uint64 for array-based doc representations
* Temporarily test with latest numpy v1.24.0rc
* Remove unnecessary conversion from attr_t
* Reduce number of individual casts
* Convert specifically from int32 to uint64
* Revert "Temporarily test with latest numpy v1.24.0rc"
This reverts commit eb0e3c5006.
* Also use int32 in tests
Strings in replacement nodes where not added to the `StringStore`
when `EditTreeLemmatizer` was initialized from a set of labels. The
corresponding test did not capture this because it added the strings
through the examples that were passed to the initialization.
This change fixes both this bug in the initialization as the 'shadowing'
of the bug in the test.
* 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
* pymorph2 issues #11620, #11626, #11625:
- #11620: pymorphy2_lookup
- #11626: handle multiple forms pointing to the same normal form + handling empty POS tag
- #11625: matching DET that are labelled as PRON by pymorhp2
* Move lemmatizer algorithm changes back into RussianLemmatizer
* Fix uk pymorphy3_lookup mode init
* Move and update tests for ru/uk lookup lemmatizer modes
* Fix typo
* Remove traces of previous behavior for uninflected POS
* Refactor to private generic-looking pymorphy methods
* Remove xfailed uk lemmatizer cases
* Update spacy/lang/ru/lemmatizer.py
Co-authored-by: Richard Hudson <richard@explosion.ai>
Co-authored-by: Dmytro S Lituiev <d.lituiev@gmail.com>
Co-authored-by: Richard Hudson <richard@explosion.ai>
* 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>
* remove sentiment attribute
* remove sentiment from docs
* add test for backwards compatibility
* replace from_disk with from_bytes
* Fix docs and format file
* Fix formatting
* 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>
* 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
* 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.
* Replace EntityRuler with SpanRuler implementation
Remove `EntityRuler` and rename the `SpanRuler`-based
`future_entity_ruler` to `entity_ruler`.
Main changes:
* It is no longer possible to load patterns on init as with
`EntityRuler(patterns=)`.
* The older serialization formats (`patterns.jsonl`) are no longer
supported and the related tests are removed.
* The config settings are only stored in the config, not in the
serialized component (in particular the `phrase_matcher_attr` and
overwrite settings).
* Add migration guide to EntityRuler API docs
* docs update
* Minor edit
Co-authored-by: svlandeg <svlandeg@github.com>
* Remove imports marked as v2 leftovers
There are a few functions that were in `spacy.util` in v2, but were
moved to Thinc. In v3 these were imported in `spacy.util` so that code
could be used unchanged, but the comment over them indicates they should
always be imported from Thinc. This commit removes those imports.
It doesn't look like any DeprecationWarning was ever thrown for using
these, but it is probably fine to remove them anyway with a major
version. It is not clear that they were widely used.
* Import fix_random_seed correctly
This seems to be the only place in spaCy that was using the old import.
* Fix multiple extensions and character offset
* Rename token_start/end to start/end
* Refactor Doc.from_json based on review
* Iterate over user_data items
* Only add non-empty underscore entries
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* `strings`: Remove unused `hash32_utf8` function
* `strings`: Make `hash_utf8` and `decode_Utf8Str` private
* `strings`: Reorganize private functions
* 'strings': Raise error when non-string/-int types are passed to functions that don't accept them
* `strings`: Add `items()` method, add type hints, remove unused methods, restrict inputs to specific types, reorganize methods
* `Morphology`: Use `StringStore.items()` to enumerate features when pickling
* `test_stringstore`: Update pre-Python 3 tests
* Update `StringStore` docs
* Fix `get_string_id` imports
* Replace redundant test with tests for type checking
* Rename `_retrieve_interned_str`, remove `.get` default arg
* Add `get_string_id` to `strings.pyi`
Remove `mypy` ignore directives from imports of the above
* `strings.pyi`: Replace functions that consume `Union`-typed params with overloads
* `strings.pyi`: Revert some function signatures
* Update `SYMBOLS_BY_INT` lookups and error codes post-merge
* Revert clobbered change introduced in a previous merge
* Remove unnecessary type hint
* Invert tuple order in `StringStore.items()`
* Add test for `StringStore.items()`
* Revert "`Morphology`: Use `StringStore.items()` to enumerate features when pickling"
This reverts commit 1af9510ceb.
* Rename `keys` and `key_map`
* Add `keys()` and `values()`
* Add comment about the inverted key-value semantics in the API
* Fix type hints
* Implement `keys()`, `values()`, `items()` without generators
* Fix type hints, remove unnecessary boxing
* Update docs
* Simplify `keys/values/items()` impl
* `mypy` fix
* Fix error message, doc fixes
* Change enable/disable behavior so that arguments take precedence over config options. Extend error message on conflict. Add warning message in case of overwriting config option with arguments.
* Fix tests in test_serialize_pipeline.py to reflect changes to handling of enable/disable.
* Fix type issue.
* Move comment.
* Move comment.
* Issue UserWarning instead of printing wasabi message. Adjust test.
* Added pytest.warns(UserWarning) for expected warning to fix tests.
* Update warning message.
* Move type handling out of fetch_pipes_status().
* Add global variable for default value. Use id() to determine whether used values are default value.
* Fix default value for disable.
* Rename DEFAULT_PIPE_STATUS to _DEFAULT_EMPTY_PIPES.
* add punctuation to grc
Add support for special editorial punctuation that is common in ancient Greek texts. Ancient Greek texts, as found in digital and print form, have been largely edited by scholars. Restorations and improvements are normally marked with special characters that need to be handled properly by the tokenizer.
* add unit tests
* simplify regex
* move generic quotes to char classes
* rename unit test
* fix regex
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: svlandeg <svlandeg@github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Preserve both `-` and `O` annotation in augmenters rather than relying
on `Example.to_dict`'s default support for one option outside of labeled
entity spans.
This is intended as a temporary workaround for augmenters for v3.4.x.
The behavior of `Example` and related IOB utils could be improved in the
general case for v3.5.
* Remove side effects from Doc.__init__()
* Changes based on review comment
* Readd test
* Change interface of Doc.__init__()
* Simplify test
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update doc.md
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Store activations in Doc when `store_activations` is enabled
This change adds the new `activations` attribute to `Doc`. This
attribute can be used by trainable pipes to store their activations,
probabilities, and guesses for downstream users.
As an example, this change modifies the `tagger` and `senter` pipes to
add an `store_activations` option. When this option is enabled, the
probabilities and guesses are stored in `set_annotations`.
* Change type of `store_activations` to `Union[bool, List[str]]`
When the value is:
- A bool: all activations are stored when set to `True`.
- A List[str]: the activations named in the list are stored
* Formatting fixes in Tagger
* Support store_activations in spancat and morphologizer
* Make Doc.activations type visible to MyPy
* textcat/textcat_multilabel: add store_activations option
* trainable_lemmatizer/entity_linker: add store_activations option
* parser/ner: do not currently support returning activations
* Extend tagger and senter tests
So that they, like the other tests, also check that we get no
activations if no activations were requested.
* Document `Doc.activations` and `store_activations` in the relevant pipes
* Start errors/warnings at higher numbers to avoid merge conflicts
Between the master and v4 branches.
* Add `store_activations` to docstrings.
* Replace store_activations setter by set_store_activations method
Setters that take a different type than what the getter returns are still
problematic for MyPy. Replace the setter by a method, so that type inference
works everywhere.
* Use dict comprehension suggested by @svlandeg
* Revert "Use dict comprehension suggested by @svlandeg"
This reverts commit 6e7b958f70.
* EntityLinker: add type annotations to _add_activations
* _store_activations: make kwarg-only, remove doc_scores_lens arg
* set_annotations: add type annotations
* Apply suggestions from code review
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* TextCat.predict: return dict
* Make the `TrainablePipe.store_activations` property a bool
This means that we can also bring back `store_activations` setter.
* Remove `TrainablePipe.activations`
We do not need to enumerate the activations anymore since `store_activations` is
`bool`.
* Add type annotations for activations in predict/set_annotations
* Rename `TrainablePipe.store_activations` to `save_activations`
* Error E1400 is not used anymore
This error was used when activations were still `Union[bool, List[str]]`.
* Change wording in API docs after store -> save change
* docs: tag (save_)activations as new in spaCy 4.0
* Fix copied line in morphologizer activations test
* Don't train in any test_save_activations test
* Rename activations
- "probs" -> "probabilities"
- "guesses" -> "label_ids", except in the edit tree lemmatizer, where
"guesses" -> "tree_ids".
* Remove unused W400 warning.
This warning was used when we still allowed the user to specify
which activations to save.
* Formatting fixes
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Replace "kb_ids" by a constant
* spancat: replace a cast by an assertion
* Fix EOF spacing
* Fix comments in test_save_activations tests
* Do not set RNG seed in activation saving tests
* Revert "spancat: replace a cast by an assertion"
This reverts commit 0bd5730d16.
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* replicate bug with tok2vec in annotating components
* add overfitting test with a frozen tok2vec
* remove broadcast from predict and check doc.tensor instead
* remove broadcast
* proper error
* slight rephrase of documentation
* Add a dry run flag to download
* Remove --dry-run, add --url option to `spacy info` instead
* Make mypy happy
* Print only the URL, so it's easier to use in scripts
* Don't add the egg hash unless downloading an sdist
* Update spacy/cli/info.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Add two implementations of requirements
* Clean up requirements sample slightly
This should make mypy happy
* Update URL help string
* Remove requirements option
* Add url option to docs
* Add URL to spacy info model output, when available
* Add types-setuptools to testing reqs
* Add types-setuptools to requirements
* Add "compatible", expand docstring
* Update spacy/cli/info.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Run prettier on CLI docs
* Update docs
Add a sidebar about finding download URLs, with some examples of the new
command.
* Add download URLs to table on model page
* Apply suggestions from code review
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Updates from review
* download url -> download link
* Update docs
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* `Matcher`: Better type checking of values in `SetPredicate`
`SetPredicate`: Emit warning and return `False` on unexpected value types
* Rename `value_type_mismatch` variable
* Inline warning
* Remove unexpected type warning from `_SetPredicate`
* Ensure that `str` values are not interpreted as sequences
Check elements of sequence values for convertibility to `str` or `int`
* Add more `INTERSECT` and `IN` test cases
* Test for inputs with multiple characters
* Return `False` early instead of using a boolean flag
* Remove superfluous `int` check, parentheses
* Apply suggestions from code review
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Appy suggestions from code review
* Clarify test comment
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Consolidate and freeze symbols
Instead of having symbol values defined in three potentially conflicting
places (`spacy.attrs`, `spacy.parts_of_speech`, `spacy.symbols`), define
all symbols in `spacy.symbols` and reference those values in
`spacy.attrs` and `spacy.parts_of_speech`.
Remove deprecated and placeholder symbols from `spacy.attrs.IDS`.
Make `spacy.attrs.NAMES` and `spacy.symbols.NAMES` reverse dicts rather
than lists in order to support future use of hash values in `attr_id_t`.
Minor changes:
* Use `uint64_t` for attrs in `Doc.to_array` to support future use of
hash values
* Remove unneeded attrs filter for error message in `Doc.to_array`
* Remove unused attr `SENT_END`
* Handle dynamic size of attr_id_t in Doc.to_array
* Undo added warnings
* Refactor to make Doc.to_array more similar to Doc.from_array
* Improve refactoring
* adding unit test for spacy.load with disable/exclude string arg
* allow pure strings in from_config
* update docs
* upstream type adjustements
* docs update
* make docstring more consistent
* Update spacy/language.py
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* two more cleanups
* fix type in internal method
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Clean up old Matcher call style related stuff
In v2 Matcher.add was called with (key, on_match, *patterns). In v3 this
was changed to (key, patterns, *, on_match=None), but there were various
points where the old call syntax was documented or handled specially.
This removes all those.
The Matcher itself didn't need any code changes, as it just gives a
generic type error. However the PhraseMatcher required some changes
because it would automatically "fix" the old call style.
Surprisingly, the tokenizer was still using the old call style in one
place.
After these changes tests failed in two places:
1. one test for the "new" call style, including the "old" call style. I
removed this test.
2. deserializing the PhraseMatcher fails because the input docs are a
set.
I am not sure why 2 is happening - I guess it's a quirk of the
serialization format? - so for now I just convert the set to a list when
deserializing. The check that the input Docs are a List in the
PhraseMatcher is a new check, but makes it parallel with the other
Matchers, which seemed like the right thing to do.
* Add notes related to input docs / deserialization type
* Remove Typing import
* Remove old note about call style change
* Apply suggestions from code review
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Use separate method for setting internal doc representations
In addition to the title change, this changes the internal dict to be a
defaultdict, instead of a dict with frequent use of setdefault.
* Add _add_from_arrays for unpickling
* Cleanup around adding from arrays
This moves adding to internal structures into the private batch method,
and removes the single-add method.
This has one behavioral change for `add`, in that if something is wrong
with the list of input Docs (such as one of the items not being a Doc),
valid items before the invalid one will not be added. Also the callback
will not be updated if anything is invalid. This change should not be
significant.
This also adds a test to check failure when given a non-Doc.
* Update spacy/matcher/phrasematcher.pyx
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Fix `test_{prefer,require}_gpu`
These tests assumed that GPUs are only supported with CuPy, but since Thinc 8.1
we also support Metal Performance Shaders.
* test_misc: arrange thinc imports to be together
* Add lang folder for la (Latin)
* Add Latin lang classes
* Add minimal tokenizer exceptions
* Add minimal stopwords
* Add minimal lex_attrs
* Update stopwords, tokenizer exceptions
* Add la tests; register la_tokenizer in conftest.py
* Update spacy/lang/la/lex_attrs.py
Remove duplicate form in Latin lex_attrs
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update natto-py version spec (#11222)
* Update natto-py version spec
* Update setup.cfg
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Add scorer to textcat API docs config settings (#11263)
* Update docs for pipeline initialize() methods (#11221)
* Update documentation for dependency parser
* Update documentation for trainable_lemmatizer
* Update documentation for entity_linker
* Update documentation for ner
* Update documentation for morphologizer
* Update documentation for senter
* Update documentation for spancat
* Update documentation for tagger
* Update documentation for textcat
* Update documentation for tok2vec
* Run prettier on edited files
* Apply similar changes in transformer docs
* Remove need to say annotated example explicitly
I removed the need to say "Must contain at least one annotated Example"
because it's often a given that Examples will contain some gold-standard
annotation.
* Run prettier on transformer docs
* chore: add 'concepCy' to spacy universe (#11255)
* chore: add 'concepCy' to spacy universe
* docs: add 'slogan' to concepCy
* Support full prerelease versions in the compat table (#11228)
* Support full prerelease versions in the compat table
* Fix types
* adding spans to doc_annotation in Example.to_dict (#11261)
* adding spans to doc_annotation in Example.to_dict
* to_dict compatible with from_dict: tuples instead of spans
* use strings for label and kb_id
* Simplify test
* Update data formats docs
Co-authored-by: Stefanie Wolf <stefanie.wolf@vitecsoftware.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Fix regex invalid escape sequences (#11276)
* Add W605 to the errors raised by flake8 in the CI (#11283)
* Clean up automated label-based issue handling (#11284)
* Clean up automated label-based issue handline
1. upgrade tiangolo/issue-manager to latest
2. move needs-more-info to tiangolo
3. change needs-more-info close time to 7 days
4. delete old needs-more-info config
* Use old, longer message
* Fix label name
* Fix Dutch noun chunks to skip overlapping spans (#11275)
* Add test for overlapping noun chunks
* Skip overlapping noun chunks
* Update spacy/tests/lang/nl/test_noun_chunks.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Docs: displaCy documentation - data types, `parse_{deps,ents,spans}`, spans example (#10950)
* add in spans example and parse references
* rm autoformatter
* rm extra ents copy
* TypedDict draft
* type fixes
* restore non-documentation files
* docs update
* fix spans example
* fix hyperlinks
* add parse example
* example fix + argument fix
* fix api arg in docs
* fix bad variable replacement
* fix spacing in style
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* fix spacing on table
* fix spacing on table
* rm temp files
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* include span_ruler for default warning filter (#11333)
* Add uk pipelines to website (#11332)
* Check for . in factory names (#11336)
* Make fixes for PR #11349
* Fix roman numeral coverage in #11349
Co-authored-by: Patrick J. Burns <patricks@diyclassics.org>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Lj Miranda <12949683+ljvmiranda921@users.noreply.github.com>
Co-authored-by: Jules Belveze <32683010+JulesBelveze@users.noreply.github.com>
Co-authored-by: stefawolf <wlf.ste@gmail.com>
Co-authored-by: Stefanie Wolf <stefanie.wolf@vitecsoftware.com>
Co-authored-by: Peter Baumgartner <5107405+pmbaumgartner@users.noreply.github.com>
* Switch to mecab-ko as default Korean tokenizer
Switch to the (confusingly-named) mecab-ko python module for default Korean
tokenization.
Maintain the previous `natto-py` tokenizer as
`spacy.KoreanNattoTokenizer.v1`.
* Temporarily run tests with mecab-ko tokenizer
* Fix types
* Fix duplicate test names
* Update requirements test
* Revert "Temporarily run tests with mecab-ko tokenizer"
This reverts commit d2083e7044.
* Add mecab_args setting, fix pickle for KoreanNattoTokenizer
* Fix length check
* Update docs
* Formatting
* Update natto-py error message
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
