Matthew Honnibal
78498a072d
Return Transition for missing actions in lookup_action
2017-08-06 14:16:36 +02:00
Matthew Honnibal
bfffdeabb2
Fix parser batch-size bug introduced during cleanup
2017-08-06 14:10:48 +02:00
Matthew Honnibal
7f876a7a82
Clean up some unused code in parser
2017-08-06 00:00:21 +02:00
Matthew Honnibal
8fce187de4
Fix ArcEager for missing values
2017-08-01 22:10:05 +02:00
Matthew Honnibal
27abc56e98
Add method to get beam entities
2017-07-29 21:59:02 +02:00
Matthew Honnibal
c86445bdfd
Merge branch 'develop' of https://github.com/explosion/spaCy into develop
2017-07-22 01:14:28 +02:00
Matthew Honnibal
3da1063b36
Add beam decoding to parser, to allow NER uncertainties
2017-07-20 15:02:55 +02:00
Matthew Honnibal
0ca5832427
Improve negative example handling in NER oracle
2017-07-20 00:18:49 +02:00
Tpt
57e8254f63
Adds function to extract french noun chunks
2017-06-12 15:20:49 +02:00
Matthew Honnibal
6d0356e6cc
Whitespace
2017-06-04 14:55:24 -05:00
ines
6669583f4e
Use OrderedDict
2017-06-02 21:07:56 +02:00
ines
2f1025a94c
Port over Spanish changes from #1096
2017-06-02 19:09:58 +02:00
ines
fdd0923be4
Translate model=True in exclude to lower_model and upper_model
2017-06-02 18:37:07 +02:00
Matthew Honnibal
4c97371051
Fixes for thinc 6.7
2017-06-01 04:22:16 -05:00
Matthew Honnibal
ae8010b526
Move weight serialization to Thinc
2017-06-01 02:56:12 -05:00
Matthew Honnibal
097ab9c6e4
Fix transition system to/from disk
2017-05-31 13:44:00 +02:00
Matthew Honnibal
33e5ec737f
Fix to/from disk methods
2017-05-31 13:43:10 +02:00
Matthew Honnibal
53a3824334
Fix mistake in ner feature
2017-05-31 03:01:02 +02:00
Matthew Honnibal
cc911feab2
Fix bug in NER state
2017-05-30 22:12:19 +02:00
Matthew Honnibal
be4a640f0c
Fix arc eager label costs for uint64
2017-05-30 20:37:58 +02:00
Matthew Honnibal
aa4c33914b
Work on serialization
2017-05-29 08:40:45 -05:00
Matthew Honnibal
59f355d525
Fixes for serialization
2017-05-29 13:38:20 +02:00
Matthew Honnibal
ff26aa6c37
Work on to/from bytes/disk serialization methods
2017-05-29 11:45:45 +02:00
Matthew Honnibal
6b019b0540
Update to/from bytes methods
2017-05-29 10:14:20 +02:00
Matthew Honnibal
9239f06ed3
Fix german noun chunks iterator
2017-05-28 20:13:03 +02:00
Matthew Honnibal
fd9b6722a9
Fix noun chunks iterator for new stringstore
2017-05-28 20:12:10 +02:00
Matthew Honnibal
7996d21717
Fixes for new StringStore
2017-05-28 11:09:27 -05:00
Matthew Honnibal
8a24c60c1e
Merge branch 'develop' of https://github.com/explosion/spaCy into develop
2017-05-28 08:12:05 -05:00
Matthew Honnibal
bc97bc292c
Fix __call__ method
2017-05-28 08:11:58 -05:00
Matthew Honnibal
84e66ca6d4
WIP on stringstore change. 27 failures
2017-05-28 14:06:40 +02:00
Matthew Honnibal
39293ab2ee
Merge branch 'develop' of https://github.com/explosion/spaCy into develop
2017-05-28 11:46:57 +02:00
Matthew Honnibal
dd052572d4
Update arc eager for SBD changes
2017-05-28 11:46:51 +02:00
Matthew Honnibal
c1263a844b
Merge branch 'develop' of https://github.com/explosion/spaCy into develop
2017-05-27 18:32:57 -05:00
Matthew Honnibal
9e711c3476
Divide d_loss by batch size
2017-05-27 18:32:46 -05:00
Matthew Honnibal
a1d4c97fb7
Improve correctness of minibatching
2017-05-27 17:59:00 -05:00
Matthew Honnibal
49235017bf
Merge branch 'develop' of https://github.com/explosion/spaCy into develop
2017-05-27 16:34:28 -05:00
Matthew Honnibal
7ebd26b8aa
Use ordered dict to specify transitions
2017-05-27 15:52:20 -05:00
Matthew Honnibal
3eea5383a1
Add move_names property to parser
2017-05-27 15:51:55 -05:00
Matthew Honnibal
99316fa631
Use ordered dict to specify actions
2017-05-27 15:50:21 -05:00
Matthew Honnibal
655ca58c16
Clarifying change to StateC.clone
2017-05-27 15:49:37 -05:00
Matthew Honnibal
3d22fcaf0b
Return None from parser if there are no annotations
2017-05-26 14:02:59 -05:00
Matthew Honnibal
3d5a536eaa
Improve efficiency of parser batching
2017-05-26 11:31:23 -05:00
Matthew Honnibal
2cb7cc2db7
Remove commented code from parser
2017-05-25 14:55:09 -05:00
Matthew Honnibal
c245ff6b27
Rebatch parser inputs, with mid-sentence states
2017-05-25 11:18:59 -05:00
Matthew Honnibal
679efe79c8
Make parser update less hacky
2017-05-25 06:49:00 -05:00
Matthew Honnibal
e1cb5be0c7
Adjust dropout, depth and multi-task in parser
2017-05-24 20:11:41 -05:00
Matthew Honnibal
620df0414f
Fix dropout in parser
2017-05-23 15:20:45 -05:00
Matthew Honnibal
8026c183d0
Add hacky logic to accelerate depth=0 case in parser
2017-05-23 11:06:49 -05:00
Matthew Honnibal
a8b6d11c5b
Support optional maxout layer
2017-05-23 05:58:07 -05:00
Matthew Honnibal
c55b8fa7c5
Fix bugs in parse_batch
2017-05-23 05:57:52 -05:00
Matthew Honnibal
964707d795
Restore support for deeper networks in parser
2017-05-23 05:31:13 -05:00
Matthew Honnibal
6b918cc58e
Support making updates periodically during training
2017-05-23 04:23:29 -05:00
Matthew Honnibal
3f725ff7b3
Roll back changes to parser update
2017-05-23 04:23:05 -05:00
Matthew Honnibal
3959d778ac
Revert "Revert "WIP on improving parser efficiency""
...
This reverts commit 532afef4a8
.
2017-05-23 03:06:53 -05:00
Matthew Honnibal
532afef4a8
Revert "WIP on improving parser efficiency"
...
This reverts commit bdaac7ab44
.
2017-05-23 03:05:25 -05:00
Matthew Honnibal
bdaac7ab44
WIP on improving parser efficiency
2017-05-23 02:59:31 -05:00
Matthew Honnibal
8a9e318deb
Put the parsing loop in a nogil prange block
2017-05-22 17:58:12 -05:00
Matthew Honnibal
e2136232f9
Exclude states with no matching gold annotations from parsing
2017-05-22 10:30:12 -05:00
Matthew Honnibal
f00f821496
Fix pseudoprojectivity->nonproj
2017-05-22 06:14:42 -05:00
Matthew Honnibal
5d59e74cf6
PseudoProjectivity->nonproj
2017-05-22 05:49:53 -05:00
Matthew Honnibal
b45b4aa392
PseudoProjectivity --> nonproj
2017-05-22 05:17:44 -05:00
Matthew Honnibal
aae97f00e9
Fix nonproj import
2017-05-22 05:15:06 -05:00
Matthew Honnibal
2a5eb9f61e
Make nonproj methods top-level functions, instead of class methods
2017-05-22 04:51:08 -05:00
Matthew Honnibal
33e2222839
Remove unused code in deprojectivize
2017-05-22 04:51:08 -05:00
Matthew Honnibal
025d9bbc37
Fix handling of non-projective deps
2017-05-22 04:51:08 -05:00
Matthew Honnibal
1b5fa68996
Do pseudo-projective pre-processing for parser
2017-05-22 04:51:08 -05:00
Matthew Honnibal
1d5d9838a2
Fix action collection for parser
2017-05-22 04:51:08 -05:00
Matthew Honnibal
3b7c108246
Pass tokvecs through as a list, instead of concatenated. Also fix padding
2017-05-20 13:23:32 -05:00
Matthew Honnibal
d52b65aec2
Revert "Move to contiguous buffer for token_ids and d_vectors"
...
This reverts commit 3ff8c35a79
.
2017-05-20 11:26:23 -05:00
Matthew Honnibal
b272890a8c
Try to move parser to simpler PrecomputedAffine class. Currently broken -- maybe the previous change
2017-05-20 06:40:10 -05:00
Matthew Honnibal
3ff8c35a79
Move to contiguous buffer for token_ids and d_vectors
2017-05-20 04:17:30 -05:00
Matthew Honnibal
8b04b0af9f
Remove freqs from transition_system
2017-05-20 02:20:48 -05:00
Matthew Honnibal
a1ba20e2b1
Fix over-run on parse_batch
2017-05-19 18:57:30 -05:00
Matthew Honnibal
e84de028b5
Remove 'rebatch' op, and remove min-batch cap
2017-05-19 18:16:36 -05:00
Matthew Honnibal
c12ab47a56
Remove state argument in pipeline. Other changes
2017-05-19 13:26:36 -05:00
Matthew Honnibal
c2c825127a
Fix use_params and pipe methods
2017-05-18 08:30:59 -05:00
Matthew Honnibal
fc8d3a112c
Add util.env_opt support: Can set hyper params through environment variables.
2017-05-18 04:36:53 -05:00
Matthew Honnibal
d2626fdb45
Fix name error in nn parser
2017-05-18 04:31:01 -05:00
Matthew Honnibal
793430aa7a
Get spaCy train command working with neural network
...
* Integrate models into pipeline
* Add basic serialization (maybe incorrect)
* Fix pickle on vocab
2017-05-17 12:04:50 +02:00
Matthew Honnibal
8cf097ca88
Redesign training to integrate NN components
...
* Obsolete .parser, .entity etc names in favour of .pipeline
* Components no longer create models on initialization
* Models created by loading method (from_disk(), from_bytes() etc), or
.begin_training()
* Add .predict(), .set_annotations() methods in components
* Pass state through pipeline, to allow components to share information
more flexibly.
2017-05-16 16:17:30 +02:00
Matthew Honnibal
5211645af3
Get data flowing through pipeline. Needs redesign
2017-05-16 11:21:59 +02:00
Matthew Honnibal
a9edb3aa1d
Improve integration of NN parser, to support unified training API
2017-05-15 21:53:27 +02:00
Matthew Honnibal
4b9d69f428
Merge branch 'v2' into develop
...
* Move v2 parser into nn_parser.pyx
* New TokenVectorEncoder class in pipeline.pyx
* New spacy/_ml.py module
Currently the two parsers live side-by-side, until we figure out how to
organize them.
2017-05-14 01:10:23 +02:00
Matthew Honnibal
5cac951a16
Move new parser to nn_parser.pyx, and restore old parser, to make tests pass.
2017-05-14 00:55:01 +02:00
Matthew Honnibal
f8c02b4341
Remove cupy imports from parser, so it can work on CPU
2017-05-14 00:37:53 +02:00
Matthew Honnibal
e6d71e1778
Small fixes to parser
2017-05-13 17:19:04 -05:00
Matthew Honnibal
188c0f6949
Clean up unused import
2017-05-13 17:18:27 -05:00
Matthew Honnibal
f85c8464f7
Draft support of regression loss in parser
2017-05-13 17:17:27 -05:00
Matthew Honnibal
827b5af697
Update draft of parser neural network model
...
Model is good, but code is messy. Currently requires Chainer, which may cause the build to fail on machines without a GPU.
Outline of the model:
We first predict context-sensitive vectors for each word in the input:
(embed_lower | embed_prefix | embed_suffix | embed_shape)
>> Maxout(token_width)
>> convolution ** 4
This convolutional layer is shared between the tagger and the parser. This prevents the parser from needing tag features.
To boost the representation, we make a "super tag" with POS, morphology and dependency label. The tagger predicts this
by adding a softmax layer onto the convolutional layer --- so, we're teaching the convolutional layer to give us a
representation that's one affine transform from this informative lexical information. This is obviously good for the
parser (which backprops to the convolutions too).
The parser model makes a state vector by concatenating the vector representations for its context tokens. Current
results suggest few context tokens works well. Maybe this is a bug.
The current context tokens:
* S0, S1, S2: Top three words on the stack
* B0, B1: First two words of the buffer
* S0L1, S0L2: Leftmost and second leftmost children of S0
* S0R1, S0R2: Rightmost and second rightmost children of S0
* S1L1, S1L2, S1R2, S1R, B0L1, B0L2: Likewise for S1 and B0
This makes the state vector quite long: 13*T, where T is the token vector width (128 is working well). Fortunately,
there's a way to structure the computation to save some expense (and make it more GPU friendly).
The parser typically visits 2*N states for a sentence of length N (although it may visit more, if it back-tracks
with a non-monotonic transition). A naive implementation would require 2*N (B, 13*T) @ (13*T, H) matrix multiplications
for a batch of size B. We can instead perform one (B*N, T) @ (T, 13*H) multiplication, to pre-compute the hidden
weights for each positional feature wrt the words in the batch. (Note that our token vectors come from the CNN
-- so we can't play this trick over the vocabulary. That's how Stanford's NN parser works --- and why its model
is so big.)
This pre-computation strategy allows a nice compromise between GPU-friendliness and implementation simplicity.
The CNN and the wide lower layer are computed on the GPU, and then the precomputed hidden weights are moved
to the CPU, before we start the transition-based parsing process. This makes a lot of things much easier.
We don't have to worry about variable-length batch sizes, and we don't have to implement the dynamic oracle
in CUDA to train.
Currently the parser's loss function is multilabel log loss, as the dynamic oracle allows multiple states to
be 0 cost. This is defined as:
(exp(score) / Z) - (exp(score) / gZ)
Where gZ is the sum of the scores assigned to gold classes. I'm very interested in regressing on the cost directly,
but so far this isn't working well.
Machinery is in place for beam-search, which has been working well for the linear model. Beam search should benefit
greatly from the pre-computation trick.
2017-05-12 16:09:15 -05:00
Matthew Honnibal
b44f7e259c
Clean up unused parser code
2017-05-08 15:42:04 +02:00
Matthew Honnibal
17efb1c001
Change width
2017-05-08 08:40:13 -05:00
Matthew Honnibal
bef89ef23d
Mergery
2017-05-08 08:29:36 -05:00
Matthew Honnibal
50ddc9fc45
Fix infinite loop bug
2017-05-08 07:54:26 -05:00
Matthew Honnibal
a66a4a4d0f
Replace einsums
2017-05-08 14:46:50 +02:00
Matthew Honnibal
8d2eab74da
Use PretrainableMaxouts
2017-05-08 14:24:55 +02:00
Matthew Honnibal
2e2268a442
Precomputable hidden now working
2017-05-08 11:36:37 +02:00
Matthew Honnibal
10682d35ab
Get pre-computed version working
2017-05-08 00:38:35 +02:00
Matthew Honnibal
35458987e8
Checkpoint -- nearly finished reimpl
2017-05-07 23:05:01 +02:00
Matthew Honnibal
4441866f55
Checkpoint -- nearly finished reimpl
2017-05-07 22:47:06 +02:00
Matthew Honnibal
6782eedf9b
Tmp GPU code
2017-05-07 11:04:24 -05:00
Matthew Honnibal
e420e5a809
Tmp
2017-05-07 07:31:09 -05:00
Matthew Honnibal
700979fb3c
CPU/GPU compat
2017-05-07 04:01:11 +02:00
Matthew Honnibal
f99f5b75dc
working residual net
2017-05-07 03:57:26 +02:00
Matthew Honnibal
bdf2dba9fb
WIP on refactor, with hidde pre-computing
2017-05-07 02:02:43 +02:00
Matthew Honnibal
b439e04f8d
Learning smoothly
2017-05-06 20:38:12 +02:00
Matthew Honnibal
08bee76790
Learns things
2017-05-06 18:24:38 +02:00
Matthew Honnibal
bcf4cd0a5f
Learns things
2017-05-06 17:37:36 +02:00
Matthew Honnibal
8e48b58cd6
Gradients look correct
2017-05-06 16:47:15 +02:00
Matthew Honnibal
7e04260d38
Data running through, likely errors in model
2017-05-06 14:22:20 +02:00
Matthew Honnibal
ef4fa594aa
Draft of NN parser, to be tested
2017-05-05 19:20:39 +02:00
Matthew Honnibal
ccaf26206b
Pseudocode for parser
2017-05-04 12:17:59 +02:00
Matthew Honnibal
2da16adcc2
Add dropout optin for parser and NER
...
Dropout can now be specified in the `Parser.update()` method via
the `drop` keyword argument, e.g.
nlp.entity.update(doc, gold, drop=0.4)
This will randomly drop 40% of features, and multiply the value of the
others by 1. / 0.4. This may be useful for generalising from small data
sets.
This commit also patches the examples/training/train_new_entity_type.py
example, to use dropout and fix the output (previously it did not output
the learned entity).
2017-04-27 13:18:39 +02:00
Matthew Honnibal
d2436dc17b
Update fix for Issue #999
2017-04-23 18:14:37 +02:00
Matthew Honnibal
60703cede5
Ensure noun chunks can't be nested. Closes #955
2017-04-23 17:56:39 +02:00
Matthew Honnibal
4eef200bab
Persist the actions within spacy.parser.cfg
2017-04-20 17:02:44 +02:00
Matthew Honnibal
137b210bcf
Restore use of FTRL training
2017-04-16 18:02:42 +02:00
Matthew Honnibal
45464d065e
Remove print statement
2017-04-15 16:11:43 +02:00
Matthew Honnibal
c76cb8af35
Fix training for new labels
2017-04-15 16:11:26 +02:00
Matthew Honnibal
4884b2c113
Refix StepwiseState
2017-04-15 16:00:28 +02:00
Matthew Honnibal
1a98e48b8e
Fix Stepwisestate'
2017-04-15 13:35:01 +02:00
ines
0739ae7b76
Tidy up and fix formatting and imports
2017-04-15 13:05:15 +02:00
Matthew Honnibal
354458484c
WIP on add_label bug during NER training
...
Currently when a new label is introduced to NER during training,
it causes the labels to be read in in an unexpected order. This
invalidates the model.
2017-04-14 23:52:17 +02:00
Matthew Honnibal
49e2de900e
Add costs property to StepwiseState, to show which moves are gold.
2017-04-10 11:37:04 +02:00
Matthew Honnibal
cc36c308f4
Fix noun_chunk rules around coordination
...
Closes #693 .
2017-04-07 17:06:40 +02:00
Matthew Honnibal
1bb7b4ca71
Add comment
2017-03-31 13:59:19 +02:00
Matthew Honnibal
47a3ef06a6
Unhack deprojetivization, moving it into pipeline
...
Previously the deprojectivize() call was attached to the transition
system, and only called for German. Instead it should be a separate
process, called after the parser. This makes it available for any
language. Closes #898 .
2017-03-31 12:31:50 +02:00
Matthew Honnibal
a9b1f23c7d
Enable regression loss for parser
2017-03-26 09:26:30 -05:00
Matthew Honnibal
b487b8735a
Decrease beam density, and fix Python 3 problem in beam
2017-03-20 12:56:05 +01:00
Matthew Honnibal
c90dc7ac29
Clean up state initiatisation in transition system
2017-03-16 11:59:11 -05:00
Matthew Honnibal
a46933a8fe
Clean up FTRL parsing stuff.
2017-03-16 11:58:20 -05:00
Matthew Honnibal
2611ac2a89
Fix scorer bug for NER, related to ambiguity between missing annotations and misaligned tokens
2017-03-16 09:38:28 -05:00
Matthew Honnibal
3d0833c3df
Fix off-by-1 in parse features fill_context
2017-03-15 19:55:35 -05:00
Matthew Honnibal
4ef68c413f
Approximate cost in Break transition, to speed things up a bit.
2017-03-15 16:40:27 -05:00
Matthew Honnibal
8543db8a5b
Use ftrl optimizer in parser
2017-03-15 11:56:37 -05:00
Matthew Honnibal
d719f8e77e
Use nogil in parser, and set L1 to 0.0 by default
2017-03-15 09:31:01 -05:00
Matthew Honnibal
c61c501406
Update beam-parser to allow parser to maintain nogil
2017-03-15 09:30:22 -05:00
Matthew Honnibal
c79b3129e3
Fix setting of empty lexeme in initial parse state
2017-03-15 09:26:53 -05:00
Matthew Honnibal
6c4108c073
Add header for beam parser
2017-03-11 12:45:12 -06:00
Matthew Honnibal
931feb3360
Allow beam parsing for NER
2017-03-11 11:12:01 -06:00
Matthew Honnibal
ca9c8c57c0
Add iteration argument to parser.update
2017-03-11 07:00:47 -06:00
Matthew Honnibal
d59c6926c1
I think this fixes the segfault
2017-03-11 06:58:34 -06:00
Matthew Honnibal
318b9e32ff
WIP on beam parser. Currently segfaults.
2017-03-11 06:19:52 -06:00
Matthew Honnibal
b0d80dc9ae
Update name of 'train' function in BeamParser
2017-03-10 14:35:43 -06:00
Matthew Honnibal
d11f1a4ddf
Record negative costs in non-monotonic arc eager oracle
2017-03-10 11:22:04 -06:00
Matthew Honnibal
ecf91a2dbb
Support beam parser
2017-03-10 11:21:21 -06:00
Matthew Honnibal
c62da02344
Use ftrl training, to learn compressed model.
2017-03-09 18:43:21 -06:00
Matthew Honnibal
40703988bc
Use FTRL training in parser
2017-03-08 01:38:51 +01:00
Roman Inflianskas
66e1109b53
Add support for Universal Dependencies v2.0
2017-03-03 13:17:34 +01:00
Matthew Honnibal
97a1286129
Revert changes to tagger and parser for thinc 6
2017-01-09 10:08:34 -06:00
Matthew Honnibal
af81ac8bb0
Use thinc 6.0
2016-12-29 11:58:42 +01:00