Fix parser tests
@@ -36,7 +36,7 @@ def parser(vocab, arc_eager):
@pytest.fixture
def model(arc_eager, tok2vec):
- return Parser.Model(arc_eager.n_moves, token_vector_width=tok2vec.nO)
+ return Parser.Model(arc_eager.n_moves, token_vector_width=tok2vec.nO)[0]
@pytest.fixture
def doc(vocab):
@@ -45,29 +45,29 @@ def doc(vocab):
@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)
+ parser.model = Parser.Model(parser.moves.n_moves)[0]
assert parser.model is not None
-@pytest.mark.xfail
def test_predict_doc(parser, tok2vec, model, doc):
- doc.tensor = tok2vec([doc])
+ doc.tensor = tok2vec([doc])[0]
parser.model = model
parser(doc)
-@pytest.mark.xfail
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
+ d_tokvecs = parser.update(([doc], tokvecs), [gold])
+ assert d_tokvecs[0].shape == tokvecs[0].shape
def optimize(weights, gradient, key=None):
weights -= 0.001 * gradient
bp_tokvecs(d_tokvecs, sgd=optimize)
- assert d_tokvecs.sum() == 0.
+ assert d_tokvecs[0].sum() == 0.
