Commit Graph

6 Commits

Author SHA1 Message Date
Daniël de Kok 28299644fc
Speed up the StateC::L feature function (#10019)
* Speed up the StateC::L feature function

This function gets the n-th most-recent left-arc with a particular head.
Before this change, StateC::L would construct a vector of all left-arcs
with the given head and then pick the n-th most recent from that vector.
Since the number of left-arcs strongly correlates with the doc length
and the feature is constructed for every transition, this can make
transition-parsing quadratic.

With this change StateC::L:

- Searches left-arcs backwards.
- Stops early when the n-th matching transition is found.
- Does not construct a vector (reducing memory pressure).

This change doesn't avoid the linear search when the transition that is
queried does not occur in the left-arcs. Regardless, performance is
improved quite a bit with very long docs:

Before:

   N  Time

 400   3.3
 800   5.4
1600  11.6
3200  30.7

After:

   N  Time

 400   3.2
 800   5.0
1600   9.5
3200  23.2

We can probably do better with more tailored data structures, but I
first wanted to make a low-impact PR.

Found while investigating #9858.

* StateC::L: simplify loop
2022-01-13 09:03:55 +01:00
Matthew Honnibal 0fb8d437c0
Fix sentence fragments bug (#7056, #7035) (#7057)
* Add test for #7035

* Update test for issue 7056

* Fix test

* Fix transitions method used in testing

* Fix state eol detection when rebuffer

* Clean up redundant fix
2021-02-14 13:38:13 +11:00
Matthew Honnibal 8656a08777
Add beam_parser and beam_ner components for v3 (#6369)
* Get basic beam tests working

* Get basic beam tests working

* Compile _beam_utils

* Remove prints

* Test beam density

* Beam parser seems to train

* Draft beam NER

* Upd beam

* Add hypothesis as dev dependency

* Implement missing is-gold-parse method

* Implement early update

* Fix state hashing

* Fix test

* Fix test

* Default to non-beam in parser constructor

* Improve oracle for beam

* Start refactoring beam

* Update test

* Refactor beam

* Update nn

* Refactor beam and weight by cost

* Update ner beam settings

* Update test

* Add __init__.pxd

* Upd test

* Fix test

* Upd test

* Fix test

* Remove ring buffer history from StateC

* WIP change arc-eager transitions

* Add state tests

* Support ternary sent start values

* Fix arc eager

* Fix NER

* Pass oracle cut size for beam

* Fix ner test

* Fix beam

* Improve StateC.clone

* Improve StateClass.borrow

* Work directly with StateC, not StateClass

* Remove print statements

* Fix state copy

* Improve state class

* Refactor parser oracles

* Fix arc eager oracle

* Fix arc eager oracle

* Use a vector to implement the stack

* Refactor state data structure

* Fix alignment of sent start

* Add get_aligned_sent_starts method

* Add test for ae oracle when bad sentence starts

* Fix sentence segment handling

* Avoid Reduce that inserts illegal sentence

* Update preset SBD test

* Fix test

* Remove prints

* Fix sent starts in Example

* Improve python API of StateClass

* Tweak comments and debug output of arc eager

* Upd test

* Fix state test

* Fix state test
2020-12-13 09:08:32 +08:00
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
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