mirror of https://github.com/explosion/spaCy.git
72 lines
1.7 KiB
Python
72 lines
1.7 KiB
Python
# coding: utf8
|
|
from __future__ import unicode_literals
|
|
from thinc.neural import Model
|
|
from mock import Mock
|
|
import pytest
|
|
import numpy
|
|
|
|
from ..._ml import chain, Tok2Vec, doc2feats
|
|
from ...vocab import Vocab
|
|
from ...pipeline import TokenVectorEncoder
|
|
from ...syntax.arc_eager import ArcEager
|
|
from ...syntax.nn_parser import Parser
|
|
from ...tokens.doc import Doc
|
|
from ...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, preprocess=doc2feats())
|
|
|
|
|
|
@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)
|
|
|
|
@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)
|
|
assert parser.model is not None
|
|
|
|
|
|
def test_predict_doc(parser, tok2vec, model, doc):
|
|
doc.tensor = tok2vec([doc])
|
|
parser.model = model
|
|
parser(doc)
|
|
|
|
|
|
def test_update_doc(parser, tok2vec, model, doc, gold):
|
|
parser.model = model
|
|
tokvecs, bp_tokvecs = tok2vec.begin_update([doc])
|
|
d_tokvecs = parser.update((doc, tokvecs), gold)
|
|
assert d_tokvecs.shape == tokvecs.shape
|
|
def optimize(weights, gradient, key=None):
|
|
weights -= 0.001 * gradient
|
|
bp_tokvecs(d_tokvecs, sgd=optimize)
|
|
assert d_tokvecs.sum() == 0.
|