9 Commits

Author	SHA1	Message	Date
svlandeg	0e3b6a87d6	Merge branch 'upstream_master' into sync_v4	2023-07-19 16:37:31 +02:00
Basile Dura	b0228d8ea6	ci: add cython linter (#12694) ... * chore: add cython-linter dev dependency * fix: lexeme.pyx * fix: morphology.pxd * fix: tokenizer.pxd * fix: vocab.pxd * fix: morphology.pxd (line length) * ci: add cython-lint * ci: fix cython-lint call * Fix kb/candidate.pyx. * Fix kb/kb.pyx. * Fix kb/kb_in_memory.pyx. * Fix kb. * Fix training/ partially. * Fix training/. Ignore trailing whitespaces and too long lines. * Fix ml/. * Fix matcher/. * Fix pipeline/. * Fix tokens/. * Fix build errors. Fix vocab.pyx. * Fix cython-lint install and run. * Fix lexeme.pyx, parts_of_speech.pxd, vectors.pyx. Temporarily disable cython-lint execution. * Fix attrs.pyx, lexeme.pyx, symbols.pxd, isort issues. * Make cython-lint install conditional. Fix tokenizer.pyx. * Fix remaining files. Reenable cython-lint check. * Readded parentheses. * Fix test_build_dependencies(). * Add explanatory comment to cython-lint execution. --------- Co-authored-by: Raphael Mitsch <r.mitsch@outlook.com>	2023-07-19 12:03:31 +02:00
Daniël de Kok	2468742cb8	isort all the things	2023-06-26 11:41:03 +02:00
Daniël de Kok	e2b70df012	Configure isort to use the Black profile, recursively isort the spacy module (#12721) ... * Use isort with Black profile * isort all the things * Fix import cycles as a result of import sorting * Add DOCBIN_ALL_ATTRS type definition * Add isort to requirements * Remove isort from build dependencies check * Typo	2023-06-14 17:48:41 +02:00
Daniël de Kok	a183db3cef	Merge the parser refactor into v4 (#10940) ... * 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>	2023-01-18 11:27:45 +01:00
Matthew Honnibal	6f5e308d17	Support negative examples in partial NER annotations (#8106) ... * Support a cfg field in transition system * Make NER 'has gold' check use right alignment for span * Pass 'negative_samples_key' property into NER transition system * Add field for negative samples to NER transition system * Check neg_key in NER has_gold * Support negative examples in NER oracle * Test for negative examples in NER * Fix name of config variable in NER * Remove vestiges of old-style partial annotation * Remove obsolete tests * Add comment noting lack of support for negative samples in parser * Additions to "neg examples" PR (#8201) * add custom error and test for deprecated format * add test for unlearning an entity * add break also for Begin's cost * add negative_samples_key property on Parser * rename * extend docs & fix some older docs issues * add subclass constructors, clean up tests, fix docs * add flaky test with ValueError if gold parse was not found * remove ValueError if n_gold == 0 * fix docstring * Hack in environment variables to try out training * Remove hack * Remove NER hack, and support 'negative O' samples * Fix O oracle * Fix transition parser * Remove 'not O' from oracle * Fix NER oracle * check for spans in both gold.ents and gold.spans and raise if so, to prevent memory access violation * use set instead of list in consistency check Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>	2021-06-17 17:33:00 +10:00
Matthew Honnibal	8656a08777	Add beam_parser and beam_ner components for v3 (#6369) ... * Get basic beam tests working * Get basic beam tests working * Compile _beam_utils * Remove prints * Test beam density * Beam parser seems to train * Draft beam NER * Upd beam * Add hypothesis as dev dependency * Implement missing is-gold-parse method * Implement early update * Fix state hashing * Fix test * Fix test * Default to non-beam in parser constructor * Improve oracle for beam * Start refactoring beam * Update test * Refactor beam * Update nn * Refactor beam and weight by cost * Update ner beam settings * Update test * Add __init__.pxd * Upd test * Fix test * Upd test * Fix test * Remove ring buffer history from StateC * WIP change arc-eager transitions * Add state tests * Support ternary sent start values * Fix arc eager * Fix NER * Pass oracle cut size for beam * Fix ner test * Fix beam * Improve StateC.clone * Improve StateClass.borrow * Work directly with StateC, not StateClass * Remove print statements * Fix state copy * Improve state class * Refactor parser oracles * Fix arc eager oracle * Fix arc eager oracle * Use a vector to implement the stack * Refactor state data structure * Fix alignment of sent start * Add get_aligned_sent_starts method * Add test for ae oracle when bad sentence starts * Fix sentence segment handling * Avoid Reduce that inserts illegal sentence * Update preset SBD test * Fix test * Remove prints * Fix sent starts in Example * Improve python API of StateClass * Tweak comments and debug output of arc eager * Upd test * Fix state test * Fix state test	2020-12-13 09:08:32 +08:00
Sofie Van Landeghem	8e7557656f	Renaming gold & annotation_setter (#6042) ... * version bump to 3.0.0a16 * rename "gold" folder to "training" * rename 'annotation_setter' to 'set_extra_annotations' * formatting	2020-09-09 10:31:03 +02:00
Sofie Van Landeghem	ca491722ad	The Parser is now a Pipe (2) (#5844) ... * moving syntax folder to _parser_internals * moving nn_parser and transition_system * move nn_parser and transition_system out of internals folder * moving nn_parser code into transition_system file * rename transition_system to transition_parser * moving parser_model and _state to ml * move _state back to internals * The Parser now inherits from Pipe! * small code fixes * removing unnecessary imports * remove link_vectors_to_models * transition_system to internals folder * little bit more cleanup * newlines	2020-07-30 23:30:54 +02:00