Commit Graph

8 Commits

Author SHA1 Message Date
Sofie Van Landeghem
8e7557656f
Renaming gold & annotation_setter (#6042)
* version bump to 3.0.0a16

* rename "gold" folder to "training"

* rename 'annotation_setter' to 'set_extra_annotations'

* formatting
2020-09-09 10:31:03 +02:00
Sofie Van Landeghem
60f22e1800
Pipe API (#6034)
* ensure Language passes on valid examples for initialization

* fix tagger model initialization

* check for valid get_examples across components

* assume labels were added before begin_training

* fix senter initialization

* fix morphologizer initialization

* use methods to check arguments

* test textcat init, requires thinc>=8.0.0a31

* fix tok2vec init

* fix entity linker init

* use islice

* fix simple NER

* cleanup debug model

* fix assert statements

* fix tests

* throw error when adding a label if the output layer can't be resized anymore

* fix test

* add failing test for simple_ner

* UX improvements

* morphologizer UX

* assume begin_training gets a representative set and processes the labels

* remove assumptions for output of untrained NER model

* restore test for original purpose
2020-09-08 22:44:25 +02:00
Matthew Honnibal
737a1408d9 Improve implementation of fix #6010
Follow-ups to the parser efficiency fix.

* Avoid introducing new counter for number of pushes
* Base cut on number of transitions, keeping it more even
* Reintroduce the randomization we had in v2.
2020-09-02 14:42:32 +02:00
Matthew Honnibal
c1bf3a5602
Fix significant performance bug in parser training (#6010)
The parser training makes use of a trick for long documents, where we
use the oracle to cut up the document into sections, so that we can have
batch items in the middle of a document. For instance, if we have one
document of 600 words, we might make 6 states, starting at words 0, 100,
200, 300, 400 and 500.

The problem is for v3, I screwed this up and didn't stop parsing! So
instead of a batch of [100, 100, 100, 100, 100, 100], we'd have a batch
of [600, 500, 400, 300, 200, 100]. Oops.

The implementation here could probably be improved, it's annoying to
have this extra variable in the state. But this'll do.

This makes the v3 parser training 5-10 times faster, depending on document
lengths. This problem wasn't in v2.
2020-09-02 12:57:13 +02:00
Ines Montani
8128e5eb35 Replace lexeme_norm warning with logging 2020-08-14 15:00:52 +02:00
Ines Montani
950832f087
Tidy up pipes (#5906)
* Tidy up pipes

* Fix init, defaults and raise custom errors

* Update docs

* Update docs [ci skip]

* Apply suggestions from code review

Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>

* Tidy up error handling and validation, fix consistency

* Simplify get_examples check

* Remove unused import [ci skip]

Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
2020-08-11 23:29:31 +02:00
Ines Montani
56c17973aa Use "raise ... from" in custom errors for better tracebacks 2020-08-05 23:53:21 +02:00
Sofie Van Landeghem
ca491722ad
The Parser is now a Pipe (2) (#5844)
* moving syntax folder to _parser_internals

* moving nn_parser and transition_system

* move nn_parser and transition_system out of internals folder

* moving nn_parser code into transition_system file

* rename transition_system to transition_parser

* moving parser_model and _state to ml

* move _state back to internals

* The Parser now inherits from Pipe!

* small code fixes

* removing unnecessary imports

* remove link_vectors_to_models

* transition_system to internals folder

* little bit more cleanup

* newlines
2020-07-30 23:30:54 +02:00