Commit Graph

518 Commits

Author SHA1 Message Date
Sofie Van Landeghem c0f4a1e43b
train is from-config by default (#5575)
* verbose and tag_map options

* adding init_tok2vec option and only changing the tok2vec that is specified

* adding omit_extra_lookups and verifying textcat config

* wip

* pretrain bugfix

* add replace and resume options

* train_textcat fix

* raw text functionality

* improve UX when KeyError or when input data can't be parsed

* avoid unnecessary access to goldparse in TextCat pipe

* save performance information in nlp.meta

* add noise_level to config

* move nn_parser's defaults to config file

* multitask in config - doesn't work yet

* scorer offering both F and AUC options, need to be specified in config

* add textcat verification code from old train script

* small fixes to config files

* clean up

* set default config for ner/parser to allow create_pipe to work as before

* two more test fixes

* small fixes

* cleanup

* fix NER pickling + additional unit test

* create_pipe as before
2020-06-12 02:02:07 +02:00
Matthew Honnibal 8411d4f4e6
Merge pull request #5543 from svlandeg/feature/pretrain-config
pretrain from config
2020-06-04 19:07:12 +02:00
Ines Montani 810fce3bb1 Merge branch 'develop' into master-tmp 2020-06-03 14:36:59 +02:00
svlandeg e0f9f448f1 remove Tensorizer 2020-06-01 23:38:48 +02:00
Ines Montani e47e5a4b10 Use more sophisticated version parsing logic 2020-05-30 15:01:58 +02:00
Adriane Boyd 25de2a2191 Improve vector name loading from model meta 2020-05-27 14:48:54 +02:00
Ines Montani 1a15896ba9 unicode -> str consistency [ci skip] 2020-05-24 18:51:10 +02:00
Ines Montani 5d3806e059 unicode -> str consistency 2020-05-24 17:20:58 +02:00
Ines Montani 4465cad6c5 Rename spacy.analysis to spacy.pipe_analysis 2020-05-22 17:42:06 +02:00
Ines Montani 25d6ed3fb8
Merge pull request #5489 from explosion/feature/connected-components 2020-05-22 17:40:11 +02:00
Matthew Honnibal f7f6df7275 Move to spacy.analysis 2020-05-22 16:43:18 +02:00
Matthew Honnibal 78d79d94ce Guess set_annotations=True in nlp.update
During `nlp.update`, components can be passed a boolean set_annotations
to indicate whether they should assign annotations to the `Doc`. This
needs to be called if downstream components expect to use the
annotations during training, e.g. if we wanted to use tagger features in
the parser.

Components can specify their assignments and requirements, so we can
figure out which components have these inter-dependencies. After
figuring this out, we can guess whether to pass set_annotations=True.

We could also call set_annotations=True always, or even just have this
as the only behaviour. The downside of this is that it would require the
`Doc` objects to be created afresh to avoid problematic modifications.
One approach would be to make a fresh copy of the `Doc` objects within
`nlp.update()`, so that we can write to the objects without any
problems. If we do that, we can drop this logic and also drop the
`set_annotations` mechanism. I would be fine with that approach,
although it runs the risk of introducing some performance overhead, and
we'll have to take care to copy all extension attributes etc.
2020-05-22 15:55:45 +02:00
Ines Montani 6e6db6afb6 Better model compatibility and validation 2020-05-22 15:42:46 +02:00
Adriane Boyd e4a1b5dab1 Rename to url_match
Rename to `url_match` and update docs.
2020-05-22 12:41:03 +02:00
Adriane Boyd 730fa493a4 Merge remote-tracking branch 'upstream/master' into bugfix/revert-token-match 2020-05-22 12:18:00 +02:00
Matthew Honnibal 93c4d13588
Merge pull request #5264 from lfiedler/issue-5230
Fix ResourceWarnings during unittest
2020-05-22 00:31:07 +02:00
Matthew Honnibal 5ce02c1b17
Merge pull request #5470 from svlandeg/bugfix/noun-chunks
Bugfix in noun chunks
2020-05-21 20:51:31 +02:00
Ines Montani 0f1beb5ff2 Tidy up and avoid absolute spacy imports in core 2020-05-21 20:05:03 +02:00
svlandeg 84d5b7ad0a Merge remote-tracking branch 'upstream/master' into bugfix/noun-chunks
# Conflicts:
#	spacy/lang/el/syntax_iterators.py
#	spacy/lang/en/syntax_iterators.py
#	spacy/lang/fa/syntax_iterators.py
#	spacy/lang/fr/syntax_iterators.py
#	spacy/lang/id/syntax_iterators.py
#	spacy/lang/nb/syntax_iterators.py
#	spacy/lang/sv/syntax_iterators.py
2020-05-21 19:19:50 +02:00
Ines Montani 24f72c669c Merge branch 'develop' into master-tmp 2020-05-21 18:39:06 +02:00
Ines Montani d8f3190c0a Tidy up and auto-format 2020-05-21 14:14:01 +02:00
svlandeg b509a3e7fc fix: use actual range in 'seen' instead of subtree 2020-05-20 23:06:39 +02:00
Sofie Van Landeghem 7f5715a081
Various fixes to NEL functionality, Example class etc (#5460)
* 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
2020-05-20 11:41:12 +02:00
Sofie Van Landeghem f00de445dd
default models defined in component decorator (#5452)
* move defaults to pipeline and use in component decorator

* black formatting

* relative import
2020-05-19 16:20:03 +02:00
adrianeboyd a5cd203284
Reduce stored lexemes data, move feats to lookups (#5238)
* Reduce stored lexemes data, move feats to lookups

* Move non-derivable lexemes features (`norm / cluster / prob`) to
`spacy-lookups-data` as lookups
  * Get/set `norm` in both lookups and `LexemeC`, serialize in lookups
  * Remove `cluster` and `prob` from `LexemesC`, get/set/serialize in
    lookups only
* Remove serialization of lexemes data as `vocab/lexemes.bin`
  * Remove `SerializedLexemeC`
  * Remove `Lexeme.to_bytes/from_bytes`
* Modify normalization exception loading:
  * Always create `Vocab.lookups` table `lexeme_norm` for
    normalization exceptions
  * Load base exceptions from `lang.norm_exceptions`, but load
    language-specific exceptions from lookups
  * Set `lex_attr_getter[NORM]` including new lookups table in
    `BaseDefaults.create_vocab()` and when deserializing `Vocab`
* Remove all cached lexemes when deserializing vocab to override
  existing normalizations with the new normalizations (as a replacement
  for the previous step that replaced all lexemes data with the
  deserialized data)

* Skip English normalization test

Skip English normalization test because the data is now in
`spacy-lookups-data`.

* Remove norm exceptions

Moved to spacy-lookups-data.

* Move norm exceptions test to spacy-lookups-data

* Load extra lookups from spacy-lookups-data lazily

Load extra lookups (currently for cluster and prob) lazily from the
entry point `lg_extra` as `Vocab.lookups_extra`.

* Skip creating lexeme cache on load

To improve model loading times, do not create the full lexeme cache when
loading. The lexemes will be created on demand when processing.

* Identify numeric values in Lexeme.set_attrs()

With the removal of a special case for `PROB`, also identify `float` to
avoid trying to convert it with the `StringStore`.

* Skip lexeme cache init in from_bytes

* Unskip and update lookups tests for python3.6+

* Update vocab pickle to include lookups_extra

* Update vocab serialization tests

Check strings rather than lexemes since lexemes aren't initialized
automatically, account for addition of "_SP".

* Re-skip lookups test because of python3.5

* Skip PROB/float values in Lexeme.set_attrs

* Convert is_oov from lexeme flag to lex in vectors

Instead of storing `is_oov` as a lexeme flag, `is_oov` reports whether
the lexeme has a vector.

Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-05-19 15:59:14 +02:00
Sofie Van Landeghem 0d94737857
Feature toggle_pipes (#5378)
* 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>
2020-05-18 22:27:10 +02:00
Matthew Honnibal 333b1a308b
Adapt parser and NER for transformers (#5449)
* Draft layer for BILUO actions

* Fixes to biluo layer

* WIP on BILUO layer

* Add tests for BILUO layer

* Format

* Fix transitions

* Update test

* Link in the simple_ner

* Update BILUO tagger

* Update __init__

* Import simple_ner

* Update test

* Import

* Add files

* Add config

* Fix label passing for BILUO and tagger

* Fix label handling for simple_ner component

* Update simple NER test

* Update config

* Hack train script

* Update BILUO layer

* Fix SimpleNER component

* Update train_from_config

* Add biluo_to_iob helper

* Add IOB layer

* Add IOBTagger model

* Update biluo layer

* Update SimpleNER tagger

* Update BILUO

* Read random seed in train-from-config

* Update use of normal_init

* Fix normalization of gradient in SimpleNER

* Update IOBTagger

* Remove print

* Tweak masking in BILUO

* Add dropout in SimpleNER

* Update thinc

* Tidy up simple_ner

* Fix biluo model

* Unhack train-from-config

* Update setup.cfg and requirements

* Add tb_framework.py for parser model

* Try to avoid memory leak in BILUO

* Move ParserModel into spacy.ml, avoid need for subclass.

* Use updated parser model

* Remove incorrect call to model.initializre in PrecomputableAffine

* Update parser model

* Avoid divide by zero in tagger

* Add extra dropout layer in tagger

* Refine minibatch_by_words function to avoid oom

* Fix parser model after refactor

* Try to avoid div-by-zero in SimpleNER

* Fix infinite loop in minibatch_by_words

* Use SequenceCategoricalCrossentropy in Tagger

* Fix parser model when hidden layer

* Remove extra dropout from tagger

* Add extra nan check in tagger

* Fix thinc version

* Update tests and imports

* Fix test

* Update test

* Update tests

* Fix tests

* Fix test

Co-authored-by: Ines Montani <ines@ines.io>
2020-05-18 22:23:33 +02:00
svlandeg e0fda2bd81 throw warning when model_cfg is None 2020-05-15 11:02:10 +02:00
adrianeboyd 908dea3939
Skip duplicate lexeme rank setting (#5401)
Skip duplicate lexeme rank setting within
`_fix_pretrained_vectors_name()`.
2020-05-14 18:26:12 +02:00
Adriane Boyd 565e0eef73 Add tokenizer option for token match with affixes
To fix the slow tokenizer URL (#4374) and allow `token_match` to take
priority over prefixes and suffixes by default, introduce a new
tokenizer option for a token match pattern that's applied after prefixes
and suffixes but before infixes.
2020-05-05 10:35:33 +02:00
Adriane Boyd bc39f97e11 Simplify warnings 2020-04-28 13:37:37 +02:00
adrianeboyd f7471abd82
Add pkuseg and serialization support for Chinese (#5308)
* Add pkuseg and serialization support for Chinese

Add support for pkuseg alongside jieba

* Specify model through `Language` meta:

  * split on characters (if no word segmentation packages are installed)

```
Chinese(meta={"tokenizer": {"config": {"use_jieba": False, "use_pkuseg": False}}})
```

  * jieba (remains the default tokenizer if installed)

```
Chinese()
Chinese(meta={"tokenizer": {"config": {"use_jieba": True}}}) # explicit
```

  * pkuseg

```
Chinese(meta={"tokenizer": {"config": {"pkuseg_model": "default", "use_jieba": False, "use_pkuseg": True}}})
```

* The new tokenizer setting `require_pkuseg` is used to override
`use_jieba` default, which is intended for models that provide a pkuseg
model:

```
nlp_pkuseg = Chinese(meta={"tokenizer": {"config": {"pkuseg_model": "default", "require_pkuseg": True}}})
nlp = Chinese() # has `use_jieba` as `True` by default
nlp.from_bytes(nlp_pkuseg.to_bytes()) # `require_pkuseg` overrides `use_jieba` when calling the tokenizer
```

Add support for serialization of tokenizer settings and pkuseg model, if
loaded

* Add sorting for `Language.to_bytes()` serialization of `Language.meta`
so that the (emptied, but still present) tokenizer metadata is in a
consistent position in the serialized data

Extend tests to cover all three tokenizer configurations and
serialization

* Fix from_disk and tests without jieba or pkuseg

* Load cfg first and only show error if `use_pkuseg`
* Fix blank/default initialization in serialization tests

* Explicitly initialize jieba's cache on init

* Add serialization for pkuseg pre/postprocessors

* Reformat pkuseg install message
2020-04-18 17:01:53 +02:00
Leander Fiedler 1cd975d4a5 issue5230: fixed resource warnings in language 2020-04-06 18:54:32 +02:00
Ines Montani 7453df79d1 Fix argument 2020-03-26 14:09:02 +01:00
Ines Montani 46568f40a7 Merge branch 'master' into tmp/sync 2020-03-26 13:38:14 +01:00
Ines Montani 828acffc12 Tidy up and auto-format 2020-03-25 12:28:12 +01:00
svlandeg fba219f737 remove unnecessary itertools call 2020-03-16 08:31:36 +01:00
Sofie Van Landeghem 5847be6022
Tok2Vec: extract-embed-encode (#5102)
* avoid changing original config

* fix elif structure, batch with just int crashes otherwise

* tok2vec example with doc2feats, encode and embed architectures

* further clean up MultiHashEmbed

* further generalize Tok2Vec to work with extract-embed-encode parts

* avoid initializing the charembed layer with Docs (for now ?)

* small fixes for bilstm config (still does not run)

* rename to core layer

* move new configs

* walk model to set nI instead of using core ref

* fix senter overfitting test to be more similar to the training data (avoid flakey behaviour)
2020-03-08 13:23:18 +01:00
adrianeboyd 993758c58f
Remove unnecessary iterator in Language.pipe (#5101)
Remove iterator over `raw_texts` with `iterator.tee()` in
`Language.pipe` that is never consumed and consumes memory
unnecessarily.
2020-03-08 13:22:25 +01:00
adrianeboyd c95ce96c44
Update sentence recognizer (#5109)
* Update sentence recognizer

* rename `sentrec` to `senter`
* use `spacy.HashEmbedCNN.v1` by default
* update to follow `Tagger` modifications
* remove component methods that can be inherited from `Tagger`
* add simple initialization and overfitting pipeline tests

* Update serialization test for senter
2020-03-06 14:45:02 +01:00
Sofie Van Landeghem d307e9ca58
take care of global vectors in multiprocessing (#5081)
* restore load_nlp.VECTORS in the child process

* add unit test

* fix test

* remove unnecessary import

* add utf8 encoding

* import unicode_literals
2020-03-03 13:58:22 +01:00
Ines Montani 37691e6d5d Simplify warnings 2020-02-28 12:20:23 +01:00
Ines Montani 5da3ad682a Tidy up and auto-format 2020-02-28 11:57:41 +01:00
Sofie Van Landeghem 06f0a8daa0
Default settings to configurations (#4995)
* fix grad_clip naming

* cleaning up pretrained_vectors out of cfg

* further refactoring Model init's

* move Model building out of pipes

* further refactor to require a model config when creating a pipe

* small fixes

* making cfg in nn_parser more consistent

* fixing nr_class for parser

* fixing nn_parser's nO

* fix printing of loss

* architectures in own file per type, consistent naming

* convenience methods default_tagger_config and default_tok2vec_config

* let create_pipe access default config if available for that component

* default_parser_config

* move defaults to separate folder

* allow reading nlp from package or dir with argument 'name'

* architecture spacy.VocabVectors.v1 to read static vectors from file

* cleanup

* default configs for nel, textcat, morphologizer, tensorizer

* fix imports

* fixing unit tests

* fixes and clean up

* fixing defaults, nO, fix unit tests

* restore parser IO

* fix IO

* 'fix' serialization test

* add *.cfg to manifest

* fix example configs with additional arguments

* replace Morpohologizer with Tagger

* add IO bit when testing overfitting of tagger (currently failing)

* fix IO - don't initialize when reading from disk

* expand overfitting tests to also check IO goes OK

* remove dropout from HashEmbed to fix Tagger performance

* add defaults for sentrec

* update thinc

* always pass a Model instance to a Pipe

* fix piped_added statement

* remove obsolete W029

* remove obsolete errors

* restore byte checking tests (work again)

* clean up test

* further test cleanup

* convert from config to Model in create_pipe

* bring back error when component is not initialized

* cleanup

* remove calls for nlp2.begin_training

* use thinc.api in imports

* allow setting charembed's nM and nC

* fix for hardcoded nM/nC + unit test

* formatting fixes

* trigger build
2020-02-27 18:42:27 +01:00
Ines Montani 4440a072d2
Merge pull request #5006 from svlandeg/bugfix/multiproc-underscore
load Underscore state when multiprocessing
2020-02-25 14:46:02 +01:00
Ines Montani e3f40a6a0f Tidy up and auto-format 2020-02-18 15:38:18 +01:00
Ines Montani de11ea753a Merge branch 'master' into develop 2020-02-18 14:47:23 +01:00
Sofie Van Landeghem 72c964bcf4
define pretrained_dims which is used by build_text_classifier (#5004) 2020-02-16 17:21:17 +01:00
svlandeg 65f5b48b5d add comment 2020-02-12 12:06:27 +01:00
svlandeg ecbb9c4b9f load Underscore state when multiprocessing 2020-02-12 11:50:42 +01:00
Sofie Van Landeghem cabd60fa1e
Small fixes to as_example (#4957)
* label in span not writable anymore

* Revert "label in span not writable anymore"

This reverts commit ab442338c8.

* fixing yield - remove redundant list
2020-02-03 13:02:12 +01:00
Sofie Van Landeghem 569cc98982
Update spaCy for thinc 8.0.0 (#4920)
* 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>
2020-01-29 17:06:46 +01:00
adrianeboyd e1b493ae85 Add sentrec shortcut to Language (#4890) 2020-01-08 16:51:24 +01:00
Sofie Van Landeghem a1b22e90cd serialize ENT_ID (#4852)
* expand serialization test for custom token attribute

* add failing test for issue 4849

* define ENT_ID as attr and use in doc serialization

* fix few typos
2020-01-06 14:57:34 +01:00
Ines Montani a892821c51 More formatting changes 2019-12-25 17:59:52 +01:00
Ines Montani db55577c45
Drop Python 2.7 and 3.5 (#4828)
* Remove unicode declarations

* Remove Python 3.5 and 2.7 from CI

* Don't require pathlib

* Replace compat helpers

* Remove OrderedDict

* Use f-strings

* Set Cython compiler language level

* Fix typo

* Re-add OrderedDict for Table

* Update setup.cfg

* Revert CONTRIBUTING.md

* Revert lookups.md

* Revert top-level.md

* Small adjustments and docs [ci skip]
2019-12-22 01:53:56 +01:00
Ines Montani 158b98a3ef Merge branch 'master' into develop 2019-12-21 18:55:03 +01:00
adrianeboyd 392c4880d9 Restructure Example with merged sents as default (#4632)
* Switch to train_dataset() function in train CLI

* Fixes for pipe() methods in pipeline components

* Don't clobber `examples` variable with `as_example` in pipe() methods
* Remove unnecessary traversals of `examples`

* Update Parser.pipe() for Examples

* Add `as_examples` kwarg to `pipe()` with implementation to return
`Example`s

* Accept `Doc` or `Example` in `pipe()` with `_get_doc()` (copied from
`Pipe`)

* Fixes to Example implementation in spacy.gold

* Move `make_projective` from an attribute of Example to an argument of
`Example.get_gold_parses()`

* Head of 0 are not treated as unset

* Unset heads are set to self rather than `None` (which causes problems
while projectivizing)

* Check for `Doc` (not just not `None`) when creating GoldParses for
pre-merged example

* Don't clobber `examples` variable in `iter_gold_docs()`

* Add/modify gold tests for handling projectivity

* In JSON roundtrip compare results from `dev_dataset` rather than
`train_dataset` to avoid projectivization (and other potential
modifications)

* Add test for projective train vs. nonprojective dev versions of the
same `Doc`

* Handle ignore_misaligned as arg rather than attr

Move `ignore_misaligned` from an attribute of `Example` to an argument
to `Example.get_gold_parses()`, which makes it parallel to
`make_projective`.

Add test with old and new align that checks whether `ignore_misaligned`
errors are raised as expected (only for new align).

* Remove unused attrs from gold.pxd

Remove `ignore_misaligned` and `make_projective` from `gold.pxd`

* Restructure Example with merged sents as default

An `Example` now includes a single `TokenAnnotation` that includes all
the information from one `Doc` (=JSON `paragraph`). If required, the
individual sentences can be returned as a list of examples with
`Example.split_sents()` with no raw text available.

* Input/output a single `Example.token_annotation`

* Add `sent_starts` to `TokenAnnotation` to handle sentence boundaries

* Replace `Example.merge_sents()` with `Example.split_sents()`

* Modify components to use a single `Example.token_annotation`

  * Pipeline components
  * conllu2json converter

* Rework/rename `add_token_annotation()` and `add_doc_annotation()` to
`set_token_annotation()` and `set_doc_annotation()`, functions that set
rather then appending/extending.

* Rename `morphology` to `morphs` in `TokenAnnotation` and `GoldParse`

* Add getters to `TokenAnnotation` to supply default values when a given
attribute is not available

* `Example.get_gold_parses()` in `spacy.gold._make_golds()` is only
applied on single examples, so the `GoldParse` is returned saved in the
provided `Example` rather than creating a new `Example` with no other
internal annotation

* Update tests for API changes and `merge_sents()` vs. `split_sents()`

* Refer to Example.goldparse in iter_gold_docs()

Use `Example.goldparse` in `iter_gold_docs()` instead of `Example.gold`
because a `None` `GoldParse` is generated with ignore_misaligned and
generating it on-the-fly can raise an unwanted AlignmentError

* Fix make_orth_variants()

Fix bug in make_orth_variants() related to conversion from multiple to
one TokenAnnotation per Example.

* Add basic test for make_orth_variants()

* Replace try/except with conditionals

* Replace default morph value with set
2019-11-25 16:03:28 +01:00
Ines Montani 3bd15055ce
Fix bug in Language.evaluate for components without .pipe (#4662) 2019-11-16 20:20:37 +01:00
adrianeboyd faaa832518 Generalize handling of tokenizer special cases (#4259)
* Generalize handling of tokenizer special cases

Handle tokenizer special cases more generally by using the Matcher
internally to match special cases after the affix/token_match
tokenization is complete.

Instead of only matching special cases while processing balanced or
nearly balanced prefixes and suffixes, this recognizes special cases in
a wider range of contexts:

* Allows arbitrary numbers of prefixes/affixes around special cases
* Allows special cases separated by infixes

Existing tests/settings that couldn't be preserved as before:

* The emoticon '")' is no longer a supported special case
* The emoticon ':)' in "example:)" is a false positive again

When merged with #4258 (or the relevant cache bugfix), the affix and
token_match properties should be modified to flush and reload all
special cases to use the updated internal tokenization with the Matcher.

* Remove accidentally added test case

* Really remove accidentally added test

* Reload special cases when necessary

Reload special cases when affixes or token_match are modified. Skip
reloading during initialization.

* Update error code number

* Fix offset and whitespace in Matcher special cases

* Fix offset bugs when merging and splitting tokens
* Set final whitespace on final token in inserted special case

* Improve cache flushing in tokenizer

* Separate cache and specials memory (temporarily)
* Flush cache when adding special cases
* Repeated `self._cache = PreshMap()` and `self._specials = PreshMap()`
are necessary due to this bug:
https://github.com/explosion/preshed/issues/21

* Remove reinitialized PreshMaps on cache flush

* Update UD bin scripts

* Update imports for `bin/`
* Add all currently supported languages
* Update subtok merger for new Matcher validation
* Modify blinded check to look at tokens instead of lemmas (for corpora
with tokens but not lemmas like Telugu)

* Use special Matcher only for cases with affixes

* Reinsert specials cache checks during normal tokenization for special
cases as much as possible
  * Additionally include specials cache checks while splitting on infixes
  * Since the special Matcher needs consistent affix-only tokenization
    for the special cases themselves, introduce the argument
    `with_special_cases` in order to do tokenization with or without
    specials cache checks
* After normal tokenization, postprocess with special cases Matcher for
special cases containing affixes

* Replace PhraseMatcher with Aho-Corasick

Replace PhraseMatcher with the Aho-Corasick algorithm over numpy arrays
of the hash values for the relevant attribute. The implementation is
based on FlashText.

The speed should be similar to the previous PhraseMatcher. It is now
possible to easily remove match IDs and matches don't go missing with
large keyword lists / vocabularies.

Fixes #4308.

* Restore support for pickling

* Fix internal keyword add/remove for numpy arrays

* Add test for #4248, clean up test

* Improve efficiency of special cases handling

* Use PhraseMatcher instead of Matcher
* Improve efficiency of merging/splitting special cases in document
  * Process merge/splits in one pass without repeated token shifting
  * Merge in place if no splits

* Update error message number

* Remove UD script modifications

Only used for timing/testing, should be a separate PR

* Remove final traces of UD script modifications

* Update UD bin scripts

* Update imports for `bin/`
* Add all currently supported languages
* Update subtok merger for new Matcher validation
* Modify blinded check to look at tokens instead of lemmas (for corpora
with tokens but not lemmas like Telugu)

* Add missing loop for match ID set in search loop

* Remove cruft in matching loop for partial matches

There was a bit of unnecessary code left over from FlashText in the
matching loop to handle partial token matches, which we don't have with
PhraseMatcher.

* Replace dict trie with MapStruct trie

* Fix how match ID hash is stored/added

* Update fix for match ID vocab

* Switch from map_get_unless_missing to map_get

* Switch from numpy array to Token.get_struct_attr

Access token attributes directly in Doc instead of making a copy of the
relevant values in a numpy array.

Add unsatisfactory warning for hash collision with reserved terminal
hash key. (Ideally it would change the reserved terminal hash and redo
the whole trie, but for now, I'm hoping there won't be collisions.)

* Restructure imports to export find_matches

* Implement full remove()

Remove unnecessary trie paths and free unused maps.

Parallel to Matcher, raise KeyError when attempting to remove a match ID
that has not been added.

* Switch to PhraseMatcher.find_matches

* Switch to local cdef functions for span filtering

* Switch special case reload threshold to variable

Refer to variable instead of hard-coded threshold

* Move more of special case retokenize to cdef nogil

Move as much of the special case retokenization to nogil as possible.

* Rewrap sort as stdsort for OS X

* Rewrap stdsort with specific types

* Switch to qsort

* Fix merge

* Improve cmp functions

* Fix realloc

* Fix realloc again

* Initialize span struct while retokenizing

* Temporarily skip retokenizing

* Revert "Move more of special case retokenize to cdef nogil"

This reverts commit 0b7e52c797.

* Revert "Switch to qsort"

This reverts commit a98d71a942.

* Fix specials check while caching

* Modify URL test with emoticons

The multiple suffix tests result in the emoticon `:>`, which is now
retokenized into one token as a special case after the suffixes are
split off.

* Refactor _apply_special_cases()

* Use cdef ints for span info used in multiple spots

* Modify _filter_special_spans() to prefer earlier

Parallel to #4414, modify _filter_special_spans() so that the earlier
span is preferred for overlapping spans of the same length.

* Replace MatchStruct with Entity

Replace MatchStruct with Entity since the existing Entity struct is
nearly identical.

* Replace Entity with more general SpanC

* Replace MatchStruct with SpanC

* Add error in debug-data if no dev docs are available (see #4575)

* Update azure-pipelines.yml

* Revert "Update azure-pipelines.yml"

This reverts commit ed1060cf59.

* Use latest wasabi

* Reorganise install_requires

* add dframcy to universe.json (#4580)

* Update universe.json [ci skip]

* Fix multiprocessing for as_tuples=True (#4582)

* Fix conllu script (#4579)

* force extensions to avoid clash between example scripts

* fix arg order and default file encoding

* add example config for conllu script

* newline

* move extension definitions to main function

* few more encodings fixes

* Add load_from_docbin example [ci skip]

TODO: upload the file somewhere

* Update README.md

* Add warnings about 3.8 (resolves #4593) [ci skip]

* Fixed typo: Added space between "recognize" and "various" (#4600)

* Fix DocBin.merge() example (#4599)

* Replace function registries with catalogue (#4584)

* Replace functions registries with catalogue

* Update __init__.py

* Fix test

* Revert unrelated flag [ci skip]

* Bugfix/dep matcher issue 4590 (#4601)

* add contributor agreement for prilopes

* add test for issue #4590

* fix on_match params for DependencyMacther (#4590)

* Minor updates to language example sentences (#4608)

* Add punctuation to Spanish example sentences

* Combine multilanguage examples for lang xx

* Add punctuation to nb examples

* Always realloc to a larger size

Avoid potential (unlikely) edge case and cymem error seen in #4604.

* Add error in debug-data if no dev docs are available (see #4575)

* Update debug-data for GoldCorpus / Example

* Ignore None label in misaligned NER data
2019-11-13 21:24:35 +01:00
Sofie Van Landeghem e48a09df4e Example class for training data (#4543)
* 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
2019-11-11 17:35:27 +01:00
Ines Montani 09cec3e41b
Replace function registries with catalogue (#4584)
* Replace functions registries with catalogue

* Update __init__.py

* Fix test

* Revert unrelated flag [ci skip]
2019-11-07 11:45:22 +01:00
Matthew Honnibal 4e43c0ba93 Fix multiprocessing for as_tuples=True (#4582) 2019-11-04 20:29:03 +01:00
Ines Montani afe4a428f7
Fix pipeline analysis on remove pipe (#4557)
Validate *after* component is removed, not before
2019-10-30 19:04:17 +01:00
Ines Montani c5e41247e8 Tidy up and auto-format 2019-10-28 12:43:55 +01:00
Matthew Honnibal f8d740bfb1
Fix --gold-preproc train cli command (#4392)
* Fix get labels for textcat

* Fix char_embed for gpu

* Revert "Fix char_embed for gpu"

This reverts commit 055b9a9e85.

* Fix passing of cats in gold.pyx

* Revert "Match pop with append for training format (#4516)"

This reverts commit 8e7414dace.

* Fix popping gold parses

* Fix handling of cats in gold tuples

* Fix name

* Fix ner_multitask_objective script

* Add test for 4402
2019-10-27 21:58:50 +01:00
Sofie Van Landeghem 8e7414dace Match pop with append for training format (#4516)
* trying to fix script - not succesful yet

* match pop() with extend() to avoid changing the data

* few more pop-extend fixes

* reinsert deleted print statement

* fix print statement

* add last tested version

* append instead of extend

* add in few comments

* quick fix for 4402 + unit test

* fixing number of docs (not counting cats)

* more fixes

* fix len

* print tmp file instead of using data from examples dir

* print tmp file instead of using data from examples dir (2)
2019-10-27 16:01:32 +01:00
Ines Montani a9c6104047 Component decorator and component analysis (#4517)
* Add work in progress

* Update analysis helpers and component decorator

* Fix porting of docstrings for Python 2

* Fix docstring stuff on Python 2

* Support meta factories when loading model

* Put auto pipeline analysis behind flag for now

* Analyse pipes on remove_pipe and replace_pipe

* Move analysis to root for now

Try to find a better place for it, but it needs to go for now to avoid circular imports

* Simplify decorator

Don't return a wrapped class and instead just write to the object

* Update existing components and factories

* Add condition in factory for classes vs. functions

* Add missing from_nlp classmethods

* Add "retokenizes" to printed overview

* Update assigns/requires declarations of builtins

* Only return data if no_print is enabled

* Use multiline table for overview

* Don't support Span

* Rewrite errors/warnings and move them to spacy.errors
2019-10-27 13:35:49 +01:00
Ines Montani d2da117114 Also support passing list to Language.disable_pipes (#4521)
* Also support passing list to Language.disable_pipes

* Adjust internals
2019-10-25 16:19:08 +02:00
Ines Montani 2c96a5e5b0
Remove lemma attrs on BaseDefaults (#4468) 2019-10-19 23:18:09 +02:00
Ines Montani 692d7f4291 Fix formatting [ci skip] 2019-10-18 11:33:38 +02:00
Ines Montani fb11852750 Remove unused imports 2019-10-18 11:06:41 +02:00
Sofie Van Landeghem 2d249a9502 KB extensions and better parsing of WikiData (#4375)
* fix overflow error on windows

* more documentation & logging fixes

* md fix

* 3 different limit parameters to play with execution time

* bug fixes directory locations

* small fixes

* exclude dev test articles from prior probabilities stats

* small fixes

* filtering wikidata entities, removing numeric and meta items

* adding aliases from wikidata also to the KB

* fix adding WD aliases

* adding also new aliases to previously added entities

* fixing comma's

* small doc fixes

* adding subclassof filtering

* append alias functionality in KB

* prevent appending the same entity-alias pair

* fix for appending WD aliases

* remove date filter

* remove unnecessary import

* small corrections and reformatting

* remove WD aliases for now (too slow)

* removing numeric entities from training and evaluation

* small fixes

* shortcut during prediction if there is only one candidate

* add counts and fscore logging, remove FP NER from evaluation

* fix entity_linker.predict to take docs instead of single sentences

* remove enumeration sentences from the WP dataset

* entity_linker.update to process full doc instead of single sentence

* spelling corrections and dump locations in readme

* NLP IO fix

* reading KB is unnecessary at the end of the pipeline

* small logging fix

* remove empty files
2019-10-14 12:28:53 +02:00
Ines Montani f8f68bb062 Auto-format [ci skip] 2019-10-10 17:08:39 +02:00
tamuhey 650cbfe82d multiprocessing pipe (#1303) (#4371)
* refactor: separate formatting docs and golds in Language.update

* fix return typo

* add pipe test

* unpickleable object cannot be assigned to p.map

* passed test pipe

* passed test!

* pipe terminate

* try pipe

* passed test

* fix ch

* add comments

* fix len(texts)

* add comment

* add comment

* fix: multiprocessing of pipe is not supported in 2

* test: use assert_docs_equal

* fix: is_python3 -> is_python2

* fix: change _pipe arg to use functools.partial

* test: add vector modification test

* test: add sample ner_pipe and user_data pipe

* add warnings test

* test: fix user warnings

* test: fix warnings capture

* fix: remove islice import

* test: remove warnings test

* test: add stream test

* test: rename

* fix: multiproc stream

* fix: stream pipe

* add comment

* mp.Pipe seems to be able to use with relative small data

* test: skip stream test in python2

* sort imports

* test: add reason to skiptest

* fix: use pipe for docs communucation

* add comments

* add comment
2019-10-08 12:20:55 +02:00
Ines Montani b6670bf0c2 Use consistent spelling 2019-10-02 10:37:39 +02:00
Ines Montani cf65a80f36 Refactor lemmatizer and data table integration (#4353)
* Move test

* Allow default in Lookups.get_table

* Start with blank tables in Lookups.from_bytes

* Refactor lemmatizer to hold instance of Lookups

* Get lookups table within the lemmatization methods to make sure it references the correct table (even if the table was replaced or modified, e.g. when loading a model from disk)
* Deprecate other arguments on Lemmatizer.__init__ and expect Lookups for consistency
* Remove old and unsupported Lemmatizer.load classmethod
* Refactor language-specific lemmatizers to inherit as much as possible from base class and override only what they need

* Update tests and docs

* Fix more tests

* Fix lemmatizer

* Upgrade pytest to try and fix weird CI errors

* Try pytest 4.6.5
2019-10-01 21:36:03 +02:00
Ines Montani e0cf4796a5 Move lookup tables out of the core library (#4346)
* Add default to util.get_entry_point

* Tidy up entry points

* Read lookups from entry points

* Remove lookup tables and related tests

* Add lookups install option

* Remove lemmatizer tests

* Remove logic to process language data files

* Update setup.cfg
2019-10-01 00:01:27 +02:00
tamuhey b408b5b29e Refactor language update (#4316)
* refactor: separate formatting docs and golds in Language.update

* fix return typo
2019-09-27 16:20:21 +02:00
Ines Montani 00a8cbc306 Tidy up and auto-format 2019-09-18 20:27:03 +02:00
adrianeboyd b5d999e510 Add textcat to train CLI (#4226)
* Add doc.cats to spacy.gold at the paragraph level

Support `doc.cats` as `"cats": [{"label": string, "value": number}]` in
the spacy JSON training format at the paragraph level.

* `spacy.gold.docs_to_json()` writes `docs.cats`

* `GoldCorpus` reads in cats in each `GoldParse`

* Update instances of gold_tuples to handle cats

Update iteration over gold_tuples / gold_parses to handle addition of
cats at the paragraph level.

* Add textcat to train CLI

* Add textcat options to train CLI
* Add textcat labels in `TextCategorizer.begin_training()`
* Add textcat evaluation to `Scorer`:
  * For binary exclusive classes with provided label: F1 for label
  * For 2+ exclusive classes: F1 macro average
  * For multilabel (not exclusive): ROC AUC macro average (currently
relying on sklearn)
* Provide user info on textcat evaluation settings, potential
incompatibilities
* Provide pipeline to Scorer in `Language.evaluate` for textcat config
* Customize train CLI output to include only metrics relevant to current
pipeline
* Add textcat evaluation to evaluate CLI

* Fix handling of unset arguments and config params

Fix handling of unset arguments and model confiug parameters in Scorer
initialization.

* Temporarily add sklearn requirement

* Remove sklearn version number

* Improve Scorer handling of models without textcats

* Fixing Scorer handling of models without textcats

* Update Scorer output for python 2.7

* Modify inf in Scorer for python 2.7

* Auto-format

Also make small adjustments to make auto-formatting with black easier and produce nicer results

* Move error message to Errors

* Update documentation

* Add cats to annotation JSON format [ci skip]

* Fix tpl flag and docs [ci skip]

* Switch to internal roc_auc_score

Switch to internal `roc_auc_score()` adapted from scikit-learn.

* Add AUCROCScore tests and improve errors/warnings

* Add tests for AUCROCScore and roc_auc_score
* Add missing error for only positive/negative values
* Remove unnecessary warnings and errors

* Make reduced roc_auc_score functions private

Because most of the checks and warnings have been stripped for the
internal functions and access is only intended through `ROCAUCScore`,
make the functions for roc_auc_score adapted from scikit-learn private.

* Check that data corresponds with multilabel flag

Check that the training instances correspond with the multilabel flag,
adding the multilabel flag if required.

* Add textcat score to early stopping check

* Add more checks to debug-data for textcat

* Add example training data for textcat

* Add more checks to textcat train CLI

* Check configuration when extending base model
* Fix typos

* Update textcat example data

* Provide licensing details and licenses for data
* Remove two labels with no positive instances from jigsaw-toxic-comment
data.


Co-authored-by: Ines Montani <ines@ines.io>
2019-09-15 22:31:31 +02:00
Paul O'Leary McCann 7d8df69158 Bloom-filter backed Lookup Tables (#4268)
* Improve load_language_data helper

* WIP: Add Lookups implementation

* Start moving lemma data over to JSON

* WIP: move data over for more languages

* Convert more languages

* Fix lemmatizer fixtures in tests

* Finish conversion

* Auto-format JSON files

* Fix test for now

* Make sure tables are stored on instance

* Update docstrings

* Update docstrings and errors

* Update test

* Add Lookups.__len__

* Add serialization methods

* Add Lookups.remove_table

* Use msgpack for serialization to disk

* Fix file exists check

* Try using OrderedDict for everything

* Update .flake8 [ci skip]

* Try fixing serialization

* Update test_lookups.py

* Update test_serialize_vocab_strings.py

* Lookups / Tables now work

This implements the stubs in the Lookups/Table classes. Currently this
is in Cython but with no type declarations, so that could be improved.

* Add lookups to setup.py

* Actually add lookups pyx

The previous commit added the old py file...

* Lookups work-in-progress

* Move from pyx back to py

* Add string based lookups, fix serialization

* Update tests, language/lemmatizer to work with string lookups

There are some outstanding issues here:

- a pickling-related test fails due to the bloom filter
- some custom lemmatizers (fr/nl at least) have issues

More generally, there's a question of how to deal with the case where
you have a string but want to use the lookup table. Currently the table
allows access by string or id, but that's getting pretty awkward.

* Change lemmatizer lookup method to pass (orth, string)

* Fix token lookup

* Fix French lookup

* Fix lt lemmatizer test

* Fix Dutch lemmatizer

* Fix lemmatizer lookup test

This was using a normal dict instead of a Table, so checks for the
string instead of an integer key failed.

* Make uk/nl/ru lemmatizer lookup methods consistent

The mentioned tokenizers all have their own implementation of the
`lookup` method, which accesses a `Lookups` table. The way that was
called in `token.pyx` was changed so this should be updated to have the
same arguments as `lookup` in `lemmatizer.py` (specificially (orth/id,
string)).

Prior to this change tests weren't failing, but there would probably be
issues with normal use of a model. More tests should proably be added.

Additionally, the language-specific `lookup` implementations seem like
they might not be needed, since they handle things like lower-casing
that aren't actually language specific.

* Make recently added Greek method compatible

* Remove redundant class/method

Leftovers from a merge not cleaned up adequately.
2019-09-12 17:26:11 +02:00
Ines Montani 625ce2db8e Update Language docs [ci skip] 2019-09-12 13:03:38 +02:00
Ines Montani 655b434553 Merge branch 'master' into develop 2019-09-12 11:39:18 +02:00
Ines Montani 4d4b3b0783 Add "labels" to Language.meta 2019-09-12 11:34:25 +02:00
Ines Montani ac0e27a825
💫 Add Language.pipe_labels (#4276)
* Add Language.pipe_labels

* Update spacy/language.py

Co-Authored-By: Matthew Honnibal <honnibal+gh@gmail.com>
2019-09-12 10:56:28 +02:00
Matthew Honnibal 1a65c5b7af Update develop from master 2019-09-08 18:21:41 +02:00
Matthew Honnibal fde4f8ac8e Create lookups if not passed in 2019-09-08 18:08:09 +02:00
Ines Montani cd90752193 Tidy up and auto-format [ci skip] 2019-08-31 13:39:06 +02:00
Matthew Honnibal 6b2ea883ed
Merge pull request #4205 from adrianeboyd/feature/gold-train-orth-variants
Add train_docs() option to add orth variants
2019-08-28 16:54:06 +02:00
Adriane Boyd aae05ff16b Add train_docs() option to add orth variants
Filtering by orth and tag, create variants of training docs with
alternate orth variants, e.g., unicode quotes, dashes, and ellipses.

The variants can be single tokens (dashes) or paired tokens (quotes)
with left and right versions.

Currently restricted to only add variants to training documents without
raw text provided, where only gold.words needs to be modified.
2019-08-28 09:18:36 +02:00
Matthew Honnibal c308cf3e3e
Merge branch 'master' into feature/lemmatizer 2019-08-25 13:52:27 +02:00
Ines Montani 5ca7dd0f94
💫 WIP: Basic lookup class scaffolding and JSON for all lemmati… (#4167)
* Improve load_language_data helper

* WIP: Add Lookups implementation

* Start moving lemma data over to JSON

* WIP: move data over for more languages

* Convert more languages

* Fix lemmatizer fixtures in tests

* Finish conversion

* Auto-format JSON files

* Fix test for now

* Make sure tables are stored on instance
2019-08-22 14:21:32 +02:00
Matthew Honnibal bcd08f20af Merge changes from master 2019-08-21 14:18:52 +02:00
Ines Montani f580302673 Tidy up and auto-format 2019-08-20 17:36:34 +02:00
Jeno 15be09ceb0 Raise error if annotation dict in simple training style has unexpected keys #4074 (#4079)
* adding enhancement #4074.

* modified behavior to strictly require top level dictionary keys - issue #4074

* pass expected keys to error message and add links as expected top level key
2019-08-06 11:01:25 +02:00
Ines Montani 87ddbdc33e Fix handling of kwargs in Language.evaluate
Makes it consistent with other methods
2019-08-04 13:44:21 +02:00
Sofie Van Landeghem f7d950de6d ensure the lang of vocab and nlp stay consistent (#4057)
* ensure the language of vocab and nlp stay consistent across serialization

* equality with =
2019-08-01 17:13:01 +02:00
Ines Montani fc69da0acb
💫 Support simple training format in nlp.evaluate and add tests (#4033)
* Support simple training format in nlp.evaluate and add tests

* Update docs [ci skip]
2019-07-27 17:30:18 +02:00
Ines Montani 7634812172 Document Language.evaluate 2019-05-24 14:06:36 +02:00
Ines Montani 45e6855550 Update Language.update docs 2019-05-24 14:06:26 +02:00
BreakBB ed18a6efbd Add check for callable to 'Language.replace_pipe' to fix #3737 (#3741) 2019-05-14 16:59:31 +02:00
Sofie a4a6bfa4e1
Merge branch 'master' into feature/el-framework 2019-03-26 11:00:02 +01:00
Ines Montani 06bf130890 💫 Add better and serializable sentencizer (#3471)
* Add better serializable sentencizer component

* Replace default factory

* Add tests

* Tidy up

* Pass test

* Update docs
2019-03-23 15:45:02 +01:00
svlandeg 5318ce88fa 'entity_linker' instead of 'el' 2019-03-22 13:55:10 +01:00
svlandeg c593607ce2 minimal EL pipe 2019-03-22 11:36:45 +01:00
svlandeg d849eb2455 adding kb_id as field to token, el as nlp pipeline component 2019-03-22 11:34:46 +01:00
Matthew Honnibal 58d562d9b0
Merge pull request #3416 from explosion/feature/improve-beam
Improve beam search support
2019-03-16 18:42:18 +01:00
Ines Montani 278e9d2eb0 Merge branch 'master' into feature/lemmatizer 2019-03-16 13:44:22 +01:00
Ines Montani bec8db91e6 Add actual deprecation warning for n_threads (resolves #3410) 2019-03-15 16:38:44 +01:00
Ines Montani cb5dbfa63a Tidy up references to n_threads and fix default 2019-03-15 16:24:26 +01:00
Ines Montani 852e1f105c Tidy up docstrings 2019-03-15 16:23:17 +01:00
Matthew Honnibal ad56641324 Fix Language.evaluate 2019-03-15 15:20:09 +01:00
Matthew Honnibal 8a4121cbc2 Fix bug introduced by component_cfg 2019-03-12 13:32:56 +01:00
Matthew Honnibal 39a4741e26 Add support for vocab.writing_system property (#3390)
* Add xfail test for vocab.writing_system

* Add vocab.writing_system property

* Set Language.Defaults.writing_system

* Set default writing system

* Remove xfail on test_vocab_writing_system
2019-03-11 15:23:20 +01:00
Matthew Honnibal 98acf5ffe4 💫 Allow passing of config parameters to specific pipeline components (#3386)
* Add component_cfg kwarg to begin_training

* Document component_cfg arg to begin_training

* Update docs and auto-format

* Support component_cfg across Language

* Format

* Update docs and docstrings [ci skip]

* Fix begin_training
2019-03-10 23:36:47 +01:00
Ines Montani 7ba3a5d95c 💫 Make serialization methods consistent (#3385)
* Make serialization methods consistent

exclude keyword argument instead of random named keyword arguments and deprecation handling

* Update docs and add section on serialization fields
2019-03-10 19:16:45 +01:00
Matthew Honnibal 4cf897e8e1 Update from develop 2019-03-08 16:56:54 +01:00
Ines Montani 296446a1c8
Tidy up and improve docs and docstrings (#3370)
<!--- Provide a general summary of your changes in the title. -->

## Description
* tidy up and adjust Cython code to code style
* improve docstrings and make calling `help()` nicer
* add URLs to new docs pages to docstrings wherever possible, mostly to user-facing objects
* fix various typos and inconsistencies in docs

### Types of change
enhancement, docs

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2019-03-08 11:42:26 +01:00
Matthew Honnibal fc1cc4c529 Move morphologizer under spacy/pipes 2019-03-07 01:36:26 +01:00
Matthew Honnibal 3993f41cc4 Update morphology branch from develop 2019-03-07 00:14:43 +01:00
Matthew Honnibal f2fae1f186 Add batch size argument to Language.evaluate(). Closes #3263 2019-02-25 19:30:33 +01:00
Ines Montani bb9ad37e05 Improve entry points and allow custom language classes via entry points (#3080)
* Remove check for overwritten factory

This needs to be handled differently – on first initialization, a new factory will be added and any subsequent initializations will trigger this warning, even if it's a new entry point that doesn't overwrite a built-in.

* Add helper to only load specific entry point

Useful for loading languages via entry points, so that they can be lazy-loaded. Otherwise, all entry point languages would have to be loaded upfront.

* Check entry points for custom languages
2018-12-20 23:58:43 +01:00
Ines Montani 61d09c481b Merge branch 'master' into develop 2018-12-18 13:48:10 +01:00
Matthew Honnibal 83ac227bd3
💫 Better support for semi-supervised learning (#3035)
The new spacy pretrain command implemented BERT/ULMFit/etc-like transfer learning, using our Language Modelling with Approximate Outputs version of BERT's cloze task. Pretraining is convenient, but in some ways it's a bit of a strange solution. All we're doing is initialising the weights. At the same time, we're putting a lot of work into our optimisation so that it's less sensitive to initial conditions, and more likely to find good optima. I discuss this a bit in the pseudo-rehearsal blog post: https://explosion.ai/blog/pseudo-rehearsal-catastrophic-forgetting
Support semi-supervised learning in spacy train

One obvious way to improve these pretraining methods is to do multi-task learning, instead of just transfer learning. This has been shown to work very well: https://arxiv.org/pdf/1809.08370.pdf . This patch makes it easy to do this sort of thing.

    Add a new argument to spacy train, --raw-text. This takes a jsonl file with unlabelled data that can be used in arbitrary ways to do semi-supervised learning.

    Add a new method to the Language class and to pipeline components, .rehearse(). This is like .update(), but doesn't expect GoldParse objects. It takes a batch of Doc objects, and performs an update on some semi-supervised objective.

    Move the BERT-LMAO objective out from spacy/cli/pretrain.py into spacy/_ml.py, so we can create a new pipeline component, ClozeMultitask. This can be specified as a parser or NER multitask in the spacy train command. Example usage:

python -m spacy train en ./tmp ~/data/en-core-web/train/nw.json ~/data/en-core-web/dev/nw.json --pipeline parser --raw-textt ~/data/unlabelled/reddit-100k.jsonl --vectors en_vectors_web_lg --parser-multitasks cloze

Implement rehearsal methods for pipeline components

The new --raw-text argument and nlp.rehearse() method also gives us a good place to implement the the idea in the pseudo-rehearsal blog post in the parser. This works as follows:

    Add a new nlp.resume_training() method. This allocates copies of pre-trained models in the pipeline, setting things up for the rehearsal updates. It also returns an optimizer object. This also greatly reduces confusion around the nlp.begin_training() method, which randomises the weights, making it not suitable for adding new labels or otherwise fine-tuning a pre-trained model.

    Implement rehearsal updates on the Parser class, making it available for the dependency parser and NER. During rehearsal, the initial model is used to supervise the model being trained. The current model is asked to match the predictions of the initial model on some data. This minimises catastrophic forgetting, by keeping the model's predictions close to the original. See the blog post for details.

    Implement rehearsal updates for tagger

    Implement rehearsal updates for text categoriz
2018-12-10 16:25:33 +01:00
Ines Montani f37863093a 💫 Replace ujson, msgpack and dill/pickle/cloudpickle with srsly (#3003)
Remove hacks and wrappers, keep code in sync across our libraries and move spaCy a few steps closer to only depending on packages with binary wheels 🎉

See here: https://github.com/explosion/srsly

    Serialization is hard, especially across Python versions and multiple platforms. After dealing with many subtle bugs over the years (encodings, locales, large files) our libraries like spaCy and Prodigy have steadily grown a number of utility functions to wrap the multiple serialization formats we need to support (especially json, msgpack and pickle). These wrapping functions ended up duplicated across our codebases, so we wanted to put them in one place.

    At the same time, we noticed that having a lot of small dependencies was making maintainence harder, and making installation slower. To solve this, we've made srsly standalone, by including the component packages directly within it. This way we can provide all the serialization utilities we need in a single binary wheel.

    srsly currently includes forks of the following packages:

        ujson
        msgpack
        msgpack-numpy
        cloudpickle



* WIP: replace json/ujson with srsly

* Replace ujson in examples

Use regular json instead of srsly to make code easier to read and follow

* Update requirements

* Fix imports

* Fix typos

* Replace msgpack with srsly

* Fix warning
2018-12-03 01:28:22 +01:00
Gavriel Loria 919729d38c replace user-facing references to "sbd" with "sentencizer" (#2985)
## Description
Fixes #2693
Previously, the tokens `sbd` and `sentencizer` would create the same nlp pipe. Internally, both would be called `sbd`. This setup became problematic because it was hard for a user relying on the `sentencizer` pipe name to realize that their pipe's name would be `sbd` for all functions other than creating a pipe. This PR intends to change the API and API documentation to fully support `sentencizer` and drop any user-facing references to `sbd`.

### Types of change
end-user API bug

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 21:22:40 +01:00
Ines Montani 323fc26880 Tidy up and format remaining files 2018-11-30 17:43:08 +01:00
Ines Montani eddeb36c96
💫 Tidy up and auto-format .py files (#2983)
<!--- Provide a general summary of your changes in the title. -->

## Description
- [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files.
- [x] Update flake8 config to exclude very large files (lemmatization tables etc.)
- [x] Update code to be compatible with flake8 rules
- [x] Fix various small bugs, inconsistencies and messy stuff in the language data
- [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means)

Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results.

At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information.

### Types of change
enhancement, code style

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 17:03:03 +01:00
Ines Montani d33953037e
💫 Port master changes over to develop (#2979)
* Create aryaprabhudesai.md (#2681)

* Update _install.jade (#2688)

Typo fix: "models" -> "model"

* Add FAC to spacy.explain (resolves #2706)

* Remove docstrings for deprecated arguments (see #2703)

* When calling getoption() in conftest.py, pass a default option (#2709)

* When calling getoption() in conftest.py, pass a default option

This is necessary to allow testing an installed spacy by running:

  pytest --pyargs spacy

* Add contributor agreement

* update bengali token rules for hyphen and digits (#2731)

* Less norm computations in token similarity (#2730)

* Less norm computations in token similarity

* Contributor agreement

* Remove ')' for clarity (#2737)

Sorry, don't mean to be nitpicky, I just noticed this when going through the CLI and thought it was a quick fix. That said, if this was intention than please let me know.

* added contributor agreement for mbkupfer (#2738)

* Basic support for Telugu language (#2751)

* Lex _attrs for polish language (#2750)

* Signed spaCy contributor agreement

* Added polish version of english lex_attrs

* Introduces a bulk merge function, in order to solve issue #653 (#2696)

* Fix comment

* Introduce bulk merge to increase performance on many span merges

* Sign contributor agreement

* Implement pull request suggestions

* Describe converters more explicitly (see #2643)

* Add multi-threading note to Language.pipe (resolves #2582) [ci skip]

* Fix formatting

* Fix dependency scheme docs (closes #2705) [ci skip]

* Don't set stop word in example (closes #2657) [ci skip]

* Add words to portuguese language _num_words (#2759)

* Add words to portuguese language _num_words

* Add words to portuguese language _num_words

* Update Indonesian model (#2752)

* adding e-KTP in tokenizer exceptions list

* add exception token

* removing lines with containing space as it won't matter since we use .split() method in the end, added new tokens in exception

* add tokenizer exceptions list

* combining base_norms with norm_exceptions

* adding norm_exception

* fix double key in lemmatizer

* remove unused import on punctuation.py

* reformat stop_words to reduce number of lines, improve readibility

* updating tokenizer exception

* implement is_currency for lang/id

* adding orth_first_upper in tokenizer_exceptions

* update the norm_exception list

* remove bunch of abbreviations

* adding contributors file

* Fixed spaCy+Keras example (#2763)

* bug fixes in keras example

* created contributor agreement

* Adding French hyphenated first name (#2786)

* Fix typo (closes #2784)

* Fix typo (#2795) [ci skip]

Fixed typo on line 6 "regcognizer --> recognizer"

* Adding basic support for Sinhala language. (#2788)

* adding Sinhala language package, stop words, examples and lex_attrs.

* Adding contributor agreement

* Updating contributor agreement

* Also include lowercase norm exceptions

* Fix error (#2802)

* Fix error
ValueError: cannot resize an array that references or is referenced
by another array in this way.  Use the resize function

* added spaCy Contributor Agreement

* Add charlax's contributor agreement (#2805)

* agreement of contributor, may I introduce a tiny pl languge contribution (#2799)

* Contributors agreement

* Contributors agreement

* Contributors agreement

* Add jupyter=True to displacy.render in documentation (#2806)

* Revert "Also include lowercase norm exceptions"

This reverts commit 70f4e8adf3.

* Remove deprecated encoding argument to msgpack

* Set up dependency tree pattern matching skeleton (#2732)

* Fix bug when too many entity types. Fixes #2800

* Fix Python 2 test failure

* Require older msgpack-numpy

* Restore encoding arg on msgpack-numpy

* Try to fix version pin for msgpack-numpy

* Update Portuguese Language (#2790)

* Add words to portuguese language _num_words

* Add words to portuguese language _num_words

* Portuguese - Add/remove stopwords, fix tokenizer, add currency symbols

* Extended punctuation and norm_exceptions in the Portuguese language

* Correct error in spacy universe docs concerning spacy-lookup (#2814)

* Update Keras Example for (Parikh et al, 2016) implementation  (#2803)

* bug fixes in keras example

* created contributor agreement

* baseline for Parikh model

* initial version of parikh 2016 implemented

* tested asymmetric models

* fixed grevious error in normalization

* use standard SNLI test file

* begin to rework parikh example

* initial version of running example

* start to document the new version

* start to document the new version

* Update Decompositional Attention.ipynb

* fixed calls to similarity

* updated the README

* import sys package duh

* simplified indexing on mapping word to IDs

* stupid python indent error

* added code from https://github.com/tensorflow/tensorflow/issues/3388 for tf bug workaround

* Fix typo (closes #2815) [ci skip]

* Update regex version dependency

* Set version to 2.0.13.dev3

* Skip seemingly problematic test

* Remove problematic test

* Try previous version of regex

* Revert "Remove problematic test"

This reverts commit bdebbef455.

* Unskip test

* Try older version of regex

* 💫 Update training examples and use minibatching (#2830)

<!--- Provide a general summary of your changes in the title. -->

## Description
Update the training examples in `/examples/training` to show usage of spaCy's `minibatch` and `compounding` helpers ([see here](https://spacy.io/usage/training#tips-batch-size) for details). The lack of batching in the examples has caused some confusion in the past, especially for beginners who would copy-paste the examples, update them with large training sets and experienced slow and unsatisfying results.

### Types of change
enhancements

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.

* Visual C++ link updated (#2842) (closes #2841) [ci skip]

* New landing page

* Add contribution agreement

* Correcting lang/ru/examples.py (#2845)

* Correct some grammatical inaccuracies in lang\ru\examples.py; filled Contributor Agreement

* Correct some grammatical inaccuracies in lang\ru\examples.py

* Move contributor agreement to separate file

* Set version to 2.0.13.dev4

* Add Persian(Farsi) language support (#2797)

* Also include lowercase norm exceptions

* Remove in favour of https://github.com/explosion/spaCy/graphs/contributors

* Rule-based French Lemmatizer (#2818)

<!--- Provide a general summary of your changes in the title. -->

## Description
<!--- Use this section to describe your changes. If your changes required
testing, include information about the testing environment and the tests you
ran. If your test fixes a bug reported in an issue, don't forget to include the
issue number. If your PR is still a work in progress, that's totally fine – just
include a note to let us know. -->

Add a rule-based French Lemmatizer following the english one and the excellent PR for [greek language optimizations](https://github.com/explosion/spaCy/pull/2558) to adapt the Lemmatizer class.

### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->

- Lemma dictionary used can be found [here](http://infolingu.univ-mlv.fr/DonneesLinguistiques/Dictionnaires/telechargement.html), I used the XML version.
- Add several files containing exhaustive list of words for each part of speech 
- Add some lemma rules
- Add POS that are not checked in the standard Lemmatizer, i.e PRON, DET, ADV and AUX
- Modify the Lemmatizer class to check in lookup table as a last resort if POS not mentionned
- Modify the lemmatize function to check in lookup table as a last resort
- Init files are updated so the model can support all the functionalities mentioned above
- Add words to tokenizer_exceptions_list.py in respect to regex used in tokenizer_exceptions.py

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [X] I have submitted the spaCy Contributor Agreement.
- [X] I ran the tests, and all new and existing tests passed.
- [X] My changes don't require a change to the documentation, or if they do, I've added all required information.

* Set version to 2.0.13

* Fix formatting and consistency

* Update docs for new version [ci skip]

* Increment version [ci skip]

* Add info on wheels [ci skip]

* Adding "This is a sentence" example to Sinhala (#2846)

* Add wheels badge

* Update badge [ci skip]

* Update README.rst [ci skip]

* Update murmurhash pin

* Increment version to 2.0.14.dev0

* Update GPU docs for v2.0.14

* Add wheel to setup_requires

* Import prefer_gpu and require_gpu functions from Thinc

* Add tests for prefer_gpu() and require_gpu()

* Update requirements and setup.py

* Workaround bug in thinc require_gpu

* Set version to v2.0.14

* Update push-tag script

* Unhack prefer_gpu

* Require thinc 6.10.6

* Update prefer_gpu and require_gpu docs [ci skip]

* Fix specifiers for GPU

* Set version to 2.0.14.dev1

* Set version to 2.0.14

* Update Thinc version pin

* Increment version

* Fix msgpack-numpy version pin

* Increment version

* Update version to 2.0.16

* Update version [ci skip]

* Redundant ')' in the Stop words' example (#2856)

<!--- Provide a general summary of your changes in the title. -->

## Description
<!--- Use this section to describe your changes. If your changes required
testing, include information about the testing environment and the tests you
ran. If your test fixes a bug reported in an issue, don't forget to include the
issue number. If your PR is still a work in progress, that's totally fine – just
include a note to let us know. -->

### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [ ] I have submitted the spaCy Contributor Agreement.
- [ ] I ran the tests, and all new and existing tests passed.
- [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.

* Documentation improvement regarding joblib and SO (#2867)

Some documentation improvements

## Description
1. Fixed the dead URL to joblib
2. Fixed Stack Overflow brand name (with space)

### Types of change
Documentation

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.

* raise error when setting overlapping entities as doc.ents (#2880)

* Fix out-of-bounds access in NER training

The helper method state.B(1) gets the index of the first token of the
buffer, or -1 if no such token exists. Normally this is safe because we
pass this to functions like state.safe_get(), which returns an empty
token. Here we used it directly as an array index, which is not okay!

This error may have been the cause of out-of-bounds access errors during
training. Similar errors may still be around, so much be hunted down.
Hunting this one down took a long time...I printed out values across
training runs and diffed, looking for points of divergence between
runs, when no randomness should be allowed.

* Change PyThaiNLP Url (#2876)

* Fix missing comma

* Add example showing a fix-up rule for space entities

* Set version to 2.0.17.dev0

* Update regex version

* Revert "Update regex version"

This reverts commit 62358dd867.

* Try setting older regex version, to align with conda

* Set version to 2.0.17

* Add spacy-js to universe [ci-skip]

* Add spacy-raspberry to universe (closes #2889)

* Add script to validate universe json [ci skip]

* Removed space in docs + added contributor indo (#2909)

* - removed unneeded space in documentation

* - added contributor info

* Allow input text of length up to max_length, inclusive (#2922)

* Include universe spec for spacy-wordnet component (#2919)

* feat: include universe spec for spacy-wordnet component

* chore: include spaCy contributor agreement

* Minor formatting changes [ci skip]

* Fix image [ci skip]

Twitter URL doesn't work on live site

* Check if the word is in one of the regular lists specific to each POS (#2886)

* 💫 Create random IDs for SVGs to prevent ID clashes (#2927)

Resolves #2924.

## Description
Fixes problem where multiple visualizations in Jupyter notebooks would have clashing arc IDs, resulting in weirdly positioned arc labels. Generating a random ID prefix so even identical parses won't receive the same IDs for consistency (even if effect of ID clash isn't noticable here.)

### Types of change
bug fix

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.

* Fix typo [ci skip]

* fixes symbolic link on py3 and windows (#2949)

* fixes symbolic link on py3 and windows
during setup of spacy using command
python -m spacy link en_core_web_sm en
closes #2948

* Update spacy/compat.py

Co-Authored-By: cicorias <cicorias@users.noreply.github.com>

* Fix formatting

* Update universe [ci skip]

* Catalan Language Support (#2940)

* Catalan language Support

* Ddding Catalan to documentation

* Sort languages alphabetically [ci skip]

* Update tests for pytest 4.x (#2965)

<!--- Provide a general summary of your changes in the title. -->

## Description
- [x] Replace marks in params for pytest 4.0 compat ([see here](https://docs.pytest.org/en/latest/deprecations.html#marks-in-pytest-mark-parametrize))
- [x] Un-xfail passing tests (some fixes in a recent update resolved a bunch of issues, but tests were apparently never updated here)

### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.

* Fix regex pin to harmonize with conda (#2964)

* Update README.rst

* Fix bug where Vocab.prune_vector did not use 'batch_size' (#2977)

Fixes #2976

* Fix typo

* Fix typo

* Remove duplicate file

* Require thinc 7.0.0.dev2

Fixes bug in gpu_ops that would use cupy instead of numpy on CPU

* Add missing import

* Fix error IDs

* Fix tests
2018-11-29 16:30:29 +01:00
Daniel Hershcovich d3d419ecc0 Allow input text of length up to max_length, inclusive (#2922) 2018-11-13 16:46:29 +01:00
Matthew Honnibal 6350234929 Add morphologizer pipeline component to Language 2018-09-26 21:03:20 +02:00
Matthew Honnibal a26fe8e7bb Small hack in Language.update to make torch work 2018-09-13 22:51:52 +00:00
Ines Montani e9022f7b33 Remove docstrings for deprecated arguments (see #2703) 2018-08-26 14:23:13 +02:00
Ines Montani e7b075565d
💫 Rule-based NER component (#2513)
* Add helper function for reading in JSONL

* Add rule-based NER component

* Fix whitespace

* Add component to factories

* Add tests

* Add option to disable indent on json_dumps compat

Otherwise, reading JSONL back in line by line won't work

* Fix error code
2018-07-18 19:43:16 +02:00
ines f08c871adf Fix typo in Language.from_disk 2018-06-29 14:32:16 +02:00
Ines Montani 862da5e793 Support pipeline factories via entry points (#2348) 2018-05-22 18:29:45 +02:00
Matthew Honnibal 2c4a6d66fa Merge master into develop. Big merge, many conflicts -- need to review 2018-04-29 14:49:26 +02:00
Matthew Honnibal a350be0601 Fix vector-name loading fix 2018-04-04 01:31:25 +02:00
Matthew Honnibal 81f4005f3d Fix loading models with pretrained vectors 2018-04-03 23:11:48 +02:00
ines e5f47cd82d Update errors 2018-04-03 21:40:29 +02:00
Ines Montani 3141e04822
💫 New system for error messages and warnings (#2163)
* Add spacy.errors module

* Update deprecation and user warnings

* Replace errors and asserts with new error message system

* Remove redundant asserts

* Fix whitespace

* Add messages for print/util.prints statements

* Fix typo

* Fix typos

* Move CLI messages to spacy.cli._messages

* Add decorator to display error code with message

An implementation like this is nice because it only modifies the string when it's retrieved from the containing class – so we don't have to worry about manipulating tracebacks etc.

* Remove unused link in spacy.about

* Update errors for invalid pipeline components

* Improve error for unknown factories

* Add displaCy warnings

* Update formatting consistency

* Move error message to spacy.errors

* Update errors and check if doc returned by component is None
2018-04-03 15:50:31 +02:00
Matthew Honnibal f3b7c5e537 Fix syntax error 2018-03-29 21:50:32 +02:00
Matthew Honnibal 23afa6429f Add input length error, to address #1826 2018-03-29 21:45:26 +02:00
Matthew Honnibal a7c5ae2beb Avoid forcing a name on empty vectors, and remove print statement 2018-03-28 21:08:58 +02:00
Matthew Honnibal 95a9615221 Fix loading of multiple pre-trained vectors
This patch addresses #1660, which was caused by keying all pre-trained
vectors with the same ID when telling Thinc how to refer to them. This
meant that if multiple models were loaded that had pre-trained vectors,
errors or incorrect behaviour resulted.

The vectors class now includes a .name attribute, which defaults to:
{nlp.meta['lang']_nlp.meta['name']}.vectors
The vectors name is set in the cfg of the pipeline components under the
key pretrained_vectors. This replaces the previous cfg key
pretrained_dims.

In order to make existing models compatible with this change, we check
for the pretrained_dims key when loading models in from_disk and
from_bytes, and add the cfg key pretrained_vectors if we find it.
2018-03-28 16:02:59 +02:00
Matthew Honnibal 1f7229f40f Revert "Merge branch 'develop' of https://github.com/explosion/spaCy into develop"
This reverts commit c9ba3d3c2d, reversing
changes made to 92c26a35d4.
2018-03-27 19:23:02 +02:00
Matthew Honnibal f57bfbccdc Fix non-projective label filtering 2018-03-27 13:41:33 +02:00
Matthew Honnibal dd54511c4f Pass data as a function in begin_training methods 2018-03-27 09:39:59 +00:00
Matthew Honnibal bede11b67c
Improve label management in parser and NER (#2108)
This patch does a few smallish things that tighten up the training workflow a little, and allow memory use during training to be reduced by letting the GoldCorpus stream data properly.

Previously, the parser and entity recognizer read and saved labels as lists, with extra labels noted separately. Lists were used becaue ordering is very important, to ensure that the label-to-class mapping is stable.

We now manage labels as nested dictionaries, first keyed by the action, and then keyed by the label. Values are frequencies. The trick is, how do we save new labels? We need to make sure we iterate over these in the same order they're added. Otherwise, we'll get different class IDs, and the model's predictions won't make sense.

To allow stable sorting, we map the new labels to negative values. If we have two new labels, they'll be noted as having "frequency" -1 and -2. The next new label will then have "frequency" -3. When we sort by (frequency, label), we then get a stable sort.

Storing frequencies then allows us to make the next nice improvement. Previously we had to iterate over the whole training set, to pre-process it for the deprojectivisation. This led to storing the whole training set in memory. This was most of the required memory during training.

To prevent this, we now store the frequencies as we stream in the data, and deprojectivize as we go. Once we've built the frequencies, we can then apply a frequency cut-off when we decide how many classes to make.

Finally, to allow proper data streaming, we also have to have some way of shuffling the iterator. This is awkward if the training files have multiple documents in them. To solve this, the GoldCorpus class now writes the training data to disk in msgpack files, one per document. We can then shuffle the data by shuffling the paths.

This is a squash merge, as I made a lot of very small commits. Individual commit messages below.

* Simplify label management for TransitionSystem and its subclasses

* Fix serialization for new label handling format in parser

* Simplify and improve GoldCorpus class. Reduce memory use, write to temp dir

* Set actions in transition system

* Require thinc 6.11.1.dev4

* Fix error in parser init

* Add unicode declaration

* Fix unicode declaration

* Update textcat test

* Try to get model training on less memory

* Print json loc for now

* Try rapidjson to reduce memory use

* Remove rapidjson requirement

* Try rapidjson for reduced mem usage

* Handle None heads when projectivising

* Stream json docs

* Fix train script

* Handle projectivity in GoldParse

* Fix projectivity handling

* Add minibatch_by_words util from ud_train

* Minibatch by number of words in spacy.cli.train

* Move minibatch_by_words util to spacy.util

* Fix label handling

* More hacking at label management in parser

* Fix encoding in msgpack serialization in GoldParse

* Adjust batch sizes in parser training

* Fix minibatch_by_words

* Add merge_subtokens function to pipeline.pyx

* Register merge_subtokens factory

* Restore use of msgpack tmp directory

* Use minibatch-by-words in train

* Handle retokenization in scorer

* Change back-off approach for missing labels. Use 'dep' label

* Update NER for new label management

* Set NER tags for over-segmented words

* Fix label alignment in gold

* Fix label back-off for infrequent labels

* Fix int type in labels dict key

* Fix int type in labels dict key

* Update feature definition for 8 feature set

* Update ud-train script for new label stuff

* Fix json streamer

* Print the line number if conll eval fails

* Update children and sentence boundaries after deprojectivisation

* Export set_children_from_heads from doc.pxd

* Render parses during UD training

* Remove print statement

* Require thinc 6.11.1.dev6. Try adding wheel as install_requires

* Set different dev version, to flush pip cache

* Update thinc version

* Update GoldCorpus docs

* Remove print statements

* Fix formatting and links [ci skip]
2018-03-19 02:58:08 +01:00