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Fix parser tests
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@ -36,7 +36,7 @@ def parser(vocab, arc_eager):
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@pytest.fixture
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def model(arc_eager, tok2vec):
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return Parser.Model(arc_eager.n_moves, token_vector_width=tok2vec.nO)
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return Parser.Model(arc_eager.n_moves, token_vector_width=tok2vec.nO)[0]
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@pytest.fixture
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def doc(vocab):
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@ -45,29 +45,29 @@ def doc(vocab):
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@pytest.fixture
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def gold(doc):
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return GoldParse(doc, heads=[1, 1, 1], deps=['L', 'ROOT', 'R'])
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def test_can_init_nn_parser(parser):
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assert parser.model is None
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def test_build_model(parser):
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parser.model = Parser.Model(parser.moves.n_moves)
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parser.model = Parser.Model(parser.moves.n_moves)[0]
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assert parser.model is not None
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@pytest.mark.xfail
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def test_predict_doc(parser, tok2vec, model, doc):
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doc.tensor = tok2vec([doc])
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doc.tensor = tok2vec([doc])[0]
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parser.model = model
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parser(doc)
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@pytest.mark.xfail
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def test_update_doc(parser, tok2vec, model, doc, gold):
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parser.model = model
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tokvecs, bp_tokvecs = tok2vec.begin_update([doc])
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d_tokvecs = parser.update((doc, tokvecs), gold)
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assert d_tokvecs.shape == tokvecs.shape
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d_tokvecs = parser.update(([doc], tokvecs), [gold])
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assert d_tokvecs[0].shape == tokvecs[0].shape
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def optimize(weights, gradient, key=None):
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weights -= 0.001 * gradient
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bp_tokvecs(d_tokvecs, sgd=optimize)
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assert d_tokvecs.sum() == 0.
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assert d_tokvecs[0].sum() == 0.
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