* Update with WIP
* Update with WIP
* Update with pipeline serialization
* Update types and pipe factories
* Add deep merge, tidy up and add tests
* Fix pipe creation from config
* Don't validate default configs on load
* Update spacy/language.py
Co-authored-by: Ines Montani <ines@ines.io>
* Adjust factory/component meta error
* Clean up factory args and remove defaults
* Add test for failing empty dict defaults
* Update pipeline handling and methods
* provide KB as registry function instead of as object
* small change in test to make functionality more clear
* update example script for EL configuration
* Fix typo
* Simplify test
* Simplify test
* splitting pipes.pyx into separate files
* moving default configs to each component file
* fix batch_size type
* removing default values from component constructors where possible (TODO: test 4725)
* skip instead of xfail
* Add test for config -> nlp with multiple instances
* pipeline.pipes -> pipeline.pipe
* Tidy up, document, remove kwargs
* small cleanup/generalization for Tok2VecListener
* use DEFAULT_UPSTREAM field
* revert to avoid circular imports
* Fix tests
* Replace deprecated arg
* Make model dirs require config
* fix pickling of keyword-only arguments in constructor
* WIP: clean up and integrate full config
* Add helper to handle function args more reliably
Now also includes keyword-only args
* Fix config composition and serialization
* Improve config debugging and add visual diff
* Remove unused defaults and fix type
* Remove pipeline and factories from meta
* Update spacy/default_config.cfg
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update spacy/default_config.cfg
* small UX edits
* avoid printing stack trace for debug CLI commands
* Add support for language-specific factories
* specify the section of the config which holds the model to debug
* WIP: add Language.from_config
* Update with language data refactor WIP
* Auto-format
* Add backwards-compat handling for Language.factories
* Update morphologizer.pyx
* Fix morphologizer
* Update and simplify lemmatizers
* Fix Japanese tests
* Port over tagger changes
* Fix Chinese and tests
* Update to latest Thinc
* WIP: xfail first Russian lemmatizer test
* Fix component-specific overrides
* fix nO for output layers in debug_model
* Fix default value
* Fix tests and don't pass objects in config
* Fix deep merging
* Fix lemma lookup data registry
Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed)
* Add types
* Add Vocab.from_config
* Fix typo
* Fix tests
* Make config copying more elegant
* Fix pipe analysis
* Fix lemmatizers and is_base_form
* WIP: move language defaults to config
* Fix morphology type
* Fix vocab
* Remove comment
* Update to latest Thinc
* Add morph rules to config
* Tidy up
* Remove set_morphology option from tagger factory
* Hack use_gpu
* Move [pipeline] to top-level block and make [nlp.pipeline] list
Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them
* Fix use_gpu and resume in CLI
* Auto-format
* Remove resume from config
* Fix formatting and error
* [pipeline] -> [components]
* Fix types
* Fix tagger test: requires set_morphology?
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* remove _convert_examples
* fix test_gold, raise TypeError if tuples are used instead of Example's
* throwing proper errors when the wrong type of objects are passed
* fix deprectated format in tests
* fix deprectated format in parser tests
* fix tests for NEL, morph, senter, tagger, textcat
* update regression tests with new Example format
* use make_doc
* more fixes to nlp.update calls
* few more small fixes for rehearse and evaluate
* only import ml_datasets if really necessary
* entity linker training example: model loading changed according to issue 5668 (https://github.com/explosion/spaCy/issues/5668) + vocab_path is a required argument
* contributor agreement
* setting KB in the EL constructor, similar to how the model is passed on
* removing wikipedia example files - moved to projects
* throw an error when nlp.update is called with 2 positional arguments
* rewriting the config logic in create pipe to accomodate for other objects (e.g. KB) in the config
* update config files with new parameters
* avoid training pipeline components that don't have a model (like sentencizer)
* various small fixes + UX improvements
* small fixes
* set thinc to 8.0.0a9 everywhere
* remove outdated comment
* make disable_pipes deprecated in favour of the new toggle_pipes
* rewrite disable_pipes statements
* update documentation
* remove bin/wiki_entity_linking folder
* one more fix
* remove deprecated link to documentation
* few more doc fixes
* add note about name change to the docs
* restore original disable_pipes
* small fixes
* fix typo
* fix error number to W096
* rename to select_pipes
* also make changes to the documentation
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* simplify creation of KB by skipping dim reduction
* small fixes to train EL example script
* add KB creation and NEL training example scripts to example section
* update descriptions of example scripts in the documentation
* moving wiki_entity_linking folder from bin to projects
* remove test for wiki NEL functionality that is being moved
* Add load_from_config function
* Add train_from_config script
* Merge configs and expose via spacy.config
* Fix script
* Suggest create_evaluation_callback
* Hard-code for NER
* Fix errors
* Register command
* Add TODO
* Update train-from-config todos
* Fix imports
* Allow delayed setting of parser model nr_class
* Get train-from-config working
* Tidy up and fix scores and printing
* Hide traceback if cancelled
* Fix weighted score formatting
* Fix score formatting
* Make output_path optional
* Add Tok2Vec component
* Tidy up and add tok2vec_tensors
* Add option to copy docs in nlp.update
* Copy docs in nlp.update
* Adjust nlp.update() for set_annotations
* Don't shuffle pipes in nlp.update, decruft
* Support set_annotations arg in component update
* Support set_annotations in parser update
* Add get_gradients method
* Add get_gradients to parser
* Update errors.py
* Fix problems caused by merge
* Add _link_components method in nlp
* Add concept of 'listeners' and ControlledModel
* Support optional attributes arg in ControlledModel
* Try having tok2vec component in pipeline
* Fix tok2vec component
* Fix config
* Fix tok2vec
* Update for Example
* Update for Example
* Update config
* Add eg2doc util
* Update and add schemas/types
* Update schemas
* Fix nlp.update
* Fix tagger
* Remove hacks from train-from-config
* Remove hard-coded config str
* Calculate loss in tok2vec component
* Tidy up and use function signatures instead of models
* Support union types for registry models
* Minor cleaning in Language.update
* Make ControlledModel specifically Tok2VecListener
* Fix train_from_config
* Fix tok2vec
* Tidy up
* Add function for bilstm tok2vec
* Fix type
* Fix syntax
* Fix pytorch optimizer
* Add example configs
* Update for thinc describe changes
* Update for Thinc changes
* Update for dropout/sgd changes
* Update for dropout/sgd changes
* Unhack gradient update
* Work on refactoring _ml
* Remove _ml.py module
* WIP upgrade cli scripts for thinc
* Move some _ml stuff to util
* Import link_vectors from util
* Update train_from_config
* Import from util
* Import from util
* Temporarily add ml.component_models module
* Move ml methods
* Move typedefs
* Update load vectors
* Update gitignore
* Move imports
* Add PrecomputableAffine
* Fix imports
* Fix imports
* Fix imports
* Fix missing imports
* Update CLI scripts
* Update spacy.language
* Add stubs for building the models
* Update model definition
* Update create_default_optimizer
* Fix import
* Fix comment
* Update imports in tests
* Update imports in spacy.cli
* Fix import
* fix obsolete thinc imports
* update srsly pin
* from thinc to ml_datasets for example data such as imdb
* update ml_datasets pin
* using STATE.vectors
* small fix
* fix Sentencizer.pipe
* black formatting
* rename Affine to Linear as in thinc
* set validate explicitely to True
* rename with_square_sequences to with_list2padded
* rename with_flatten to with_list2array
* chaining layernorm
* small fixes
* revert Optimizer import
* build_nel_encoder with new thinc style
* fixes using model's get and set methods
* Tok2Vec in component models, various fixes
* fix up legacy tok2vec code
* add model initialize calls
* add in build_tagger_model
* small fixes
* setting model dims
* fixes for ParserModel
* various small fixes
* initialize thinc Models
* fixes
* consistent naming of window_size
* fixes, removing set_dropout
* work around Iterable issue
* remove legacy tok2vec
* util fix
* fix forward function of tok2vec listener
* more fixes
* trying to fix PrecomputableAffine (not succesful yet)
* alloc instead of allocate
* add morphologizer
* rename residual
* rename fixes
* Fix predict function
* Update parser and parser model
* fixing few more tests
* Fix precomputable affine
* Update component model
* Update parser model
* Move backprop padding to own function, for test
* Update test
* Fix p. affine
* Update NEL
* build_bow_text_classifier and extract_ngrams
* Fix parser init
* Fix test add label
* add build_simple_cnn_text_classifier
* Fix parser init
* Set gpu off by default in example
* Fix tok2vec listener
* Fix parser model
* Small fixes
* small fix for PyTorchLSTM parameters
* revert my_compounding hack (iterable fixed now)
* fix biLSTM
* Fix uniqued
* PyTorchRNNWrapper fix
* small fixes
* use helper function to calculate cosine loss
* small fixes for build_simple_cnn_text_classifier
* putting dropout default at 0.0 to ensure the layer gets built
* using thinc util's set_dropout_rate
* moving layer normalization inside of maxout definition to optimize dropout
* temp debugging in NEL
* fixed NEL model by using init defaults !
* fixing after set_dropout_rate refactor
* proper fix
* fix test_update_doc after refactoring optimizers in thinc
* Add CharacterEmbed layer
* Construct tagger Model
* Add missing import
* Remove unused stuff
* Work on textcat
* fix test (again :)) after optimizer refactor
* fixes to allow reading Tagger from_disk without overwriting dimensions
* don't build the tok2vec prematuraly
* fix CharachterEmbed init
* CharacterEmbed fixes
* Fix CharacterEmbed architecture
* fix imports
* renames from latest thinc update
* one more rename
* add initialize calls where appropriate
* fix parser initialization
* Update Thinc version
* Fix errors, auto-format and tidy up imports
* Fix validation
* fix if bias is cupy array
* revert for now
* ensure it's a numpy array before running bp in ParserStepModel
* no reason to call require_gpu twice
* use CupyOps.to_numpy instead of cupy directly
* fix initialize of ParserModel
* remove unnecessary import
* fixes for CosineDistance
* fix device renaming
* use refactored loss functions (Thinc PR 251)
* overfitting test for tagger
* experimental settings for the tagger: avoid zero-init and subword normalization
* clean up tagger overfitting test
* use previous default value for nP
* remove toy config
* bringing layernorm back (had a bug - fixed in thinc)
* revert setting nP explicitly
* remove setting default in constructor
* restore values as they used to be
* add overfitting test for NER
* add overfitting test for dep parser
* add overfitting test for textcat
* fixing init for linear (previously affine)
* larger eps window for textcat
* ensure doc is not None
* Require newer thinc
* Make float check vaguer
* Slop the textcat overfit test more
* Fix textcat test
* Fix exclusive classes for textcat
* fix after renaming of alloc methods
* fixing renames and mandatory arguments (staticvectors WIP)
* upgrade to thinc==8.0.0.dev3
* refer to vocab.vectors directly instead of its name
* rename alpha to learn_rate
* adding hashembed and staticvectors dropout
* upgrade to thinc 8.0.0.dev4
* add name back to avoid warning W020
* thinc dev4
* update srsly
* using thinc 8.0.0a0 !
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
Co-authored-by: Ines Montani <ines@ines.io>
* 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
* document token ent_kb_id
* document span kb_id
* update pipeline documentation
* prior and context weights as bool's instead
* entitylinker api documentation
* drop for both models
* finish entitylinker documentation
* small fixes
* documentation for KB
* candidate documentation
* links to api pages in code
* small fix
* frequency examples as counts for consistency
* consistent documentation about tensors returned by predict
* add entity linking to usage 101
* add entity linking infobox and KB section to 101
* entity-linking in linguistic features
* small typo corrections
* training example and docs for entity_linker
* predefined nlp and kb
* revert back to similarity encodings for simplicity (for now)
* set prior probabilities to 0 when excluded
* code clean up
* bugfix: deleting kb ID from tokens when entities were removed
* refactor train el example to use either model or vocab
* pretrain_kb example for example kb generation
* add to training docs for KB + EL example scripts
* small fixes
* error numbering
* ensure the language of vocab and nlp stay consistent across serialization
* equality with =
* avoid conflict in errors file
* add error 151
* final adjustements to the train scripts - consistency
* update of goldparse documentation
* small corrections
* push commit
* typo fix
* add candidate API to kb documentation
* update API sidebar with EntityLinker and KnowledgeBase
* remove EL from 101 docs
* remove entity linker from 101 pipelines / rephrase
* custom el model instead of existing model
* set version to 2.2 for EL functionality
* update documentation for 2 CLI scripts
* Fix typo in rule-based matching docs
* Improve token pattern checking without validation
Add more detailed token pattern checks without full JSON pattern validation and
provide more detailed error messages.
Addresses #4070 (also related: #4063, #4100).
* Check whether top-level attributes in patterns and attr for PhraseMatcher are
in token pattern schema
* Check whether attribute value types are supported in general (as opposed to
per attribute with full validation)
* Report various internal error types (OverflowError, AttributeError, KeyError)
as ValueError with standard error messages
* Check for tagger/parser in PhraseMatcher pipeline for attributes TAG, POS,
LEMMA, and DEP
* Add error messages with relevant details on how to use validate=True or nlp()
instead of nlp.make_doc()
* Support attr=TEXT for PhraseMatcher
* Add NORM to schema
* Expand tests for pattern validation, Matcher, PhraseMatcher, and EntityRuler
* Remove unnecessary .keys()
* Rephrase error messages
* Add another type check to Matcher
Add another type check to Matcher for more understandable error messages
in some rare cases.
* Support phrase_matcher_attr=TEXT for EntityRuler
* Don't use spacy.errors in examples and bin scripts
* Fix error code
* Auto-format
Also try get Azure pipelines to finally start a build :(
* Update errors.py
Co-authored-by: Ines Montani <ines@ines.io>
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* document token ent_kb_id
* document span kb_id
* update pipeline documentation
* prior and context weights as bool's instead
* entitylinker api documentation
* drop for both models
* finish entitylinker documentation
* small fixes
* documentation for KB
* candidate documentation
* links to api pages in code
* small fix
* frequency examples as counts for consistency
* consistent documentation about tensors returned by predict
* add entity linking to usage 101
* add entity linking infobox and KB section to 101
* entity-linking in linguistic features
* small typo corrections
* training example and docs for entity_linker
* predefined nlp and kb
* revert back to similarity encodings for simplicity (for now)
* set prior probabilities to 0 when excluded
* code clean up
* bugfix: deleting kb ID from tokens when entities were removed
* refactor train el example to use either model or vocab
* pretrain_kb example for example kb generation
* add to training docs for KB + EL example scripts
* small fixes
* error numbering
* ensure the language of vocab and nlp stay consistent across serialization
* equality with =
* avoid conflict in errors file
* add error 151
* final adjustements to the train scripts - consistency
* update of goldparse documentation
* small corrections
* push commit
* turn kb_creator into CLI script (wip)
* proper parameters for training entity vectors
* wikidata pipeline split up into two executable scripts
* remove context_width
* move wikidata scripts in bin directory, remove old dummy script
* refine KB script with logs and preprocessing options
* small edits
* small improvements to logging of EL CLI script
Ines Montani