mirror of
https://github.com/explosion/spaCy.git
synced 2025-01-26 01:04:34 +03:00
e48a09df4e
* 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
87 lines
1.8 KiB
Python
87 lines
1.8 KiB
Python
# coding: utf8
|
|
from __future__ import unicode_literals
|
|
|
|
import pytest
|
|
from spacy._ml import Tok2Vec
|
|
from spacy.vocab import Vocab
|
|
from spacy.syntax.arc_eager import ArcEager
|
|
from spacy.syntax.nn_parser import Parser
|
|
from spacy.tokens.doc import Doc
|
|
from spacy.gold import GoldParse
|
|
|
|
|
|
@pytest.fixture
|
|
def vocab():
|
|
return Vocab()
|
|
|
|
|
|
@pytest.fixture
|
|
def arc_eager(vocab):
|
|
actions = ArcEager.get_actions(left_labels=["L"], right_labels=["R"])
|
|
return ArcEager(vocab.strings, actions)
|
|
|
|
|
|
@pytest.fixture
|
|
def tok2vec():
|
|
return Tok2Vec(8, 100)
|
|
|
|
|
|
@pytest.fixture
|
|
def parser(vocab, arc_eager):
|
|
return Parser(vocab, moves=arc_eager, model=None)
|
|
|
|
|
|
@pytest.fixture
|
|
def model(arc_eager, tok2vec):
|
|
return Parser.Model(arc_eager.n_moves, token_vector_width=tok2vec.nO)[0]
|
|
|
|
|
|
@pytest.fixture
|
|
def doc(vocab):
|
|
return Doc(vocab, words=["a", "b", "c"])
|
|
|
|
|
|
@pytest.fixture
|
|
def gold(doc):
|
|
return GoldParse(doc, heads=[1, 1, 1], deps=["L", "ROOT", "R"])
|
|
|
|
|
|
def test_can_init_nn_parser(parser):
|
|
assert parser.model is None
|
|
|
|
|
|
def test_build_model(parser):
|
|
parser.model = Parser.Model(parser.moves.n_moves, hist_size=0)[0]
|
|
assert parser.model is not None
|
|
|
|
|
|
def test_predict_doc(parser, tok2vec, model, doc):
|
|
doc.tensor = tok2vec([doc])[0]
|
|
parser.model = model
|
|
parser(doc)
|
|
|
|
|
|
def test_update_doc(parser, model, doc, gold):
|
|
parser.model = model
|
|
|
|
def optimize(weights, gradient, key=None):
|
|
weights -= 0.001 * gradient
|
|
|
|
parser.update((doc, gold), sgd=optimize)
|
|
|
|
|
|
@pytest.mark.xfail
|
|
def test_predict_doc_beam(parser, model, doc):
|
|
parser.model = model
|
|
parser(doc, beam_width=32, beam_density=0.001)
|
|
|
|
|
|
@pytest.mark.xfail
|
|
def test_update_doc_beam(parser, model, doc, gold):
|
|
parser.model = model
|
|
|
|
def optimize(weights, gradient, key=None):
|
|
weights -= 0.001 * gradient
|
|
|
|
parser.update_beam((doc, gold), sgd=optimize)
|