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Xfail beam stuff. 9 failures
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@ -118,6 +118,7 @@ def test_beam_advance_too_few_scores(beam, scores):
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beam.advance(scores[:-1])
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@pytest.mark.xfail(reason="no beam parser yet")
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def test_beam_parse(examples, beam_width):
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nlp = Language()
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parser = nlp.add_pipe("beam_parser")
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@ -128,6 +129,7 @@ def test_beam_parse(examples, beam_width):
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parser(doc)
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@pytest.mark.xfail(reason="no beam parser yet")
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@hypothesis.given(hyp=hypothesis.strategies.data())
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def test_beam_density(moves, examples, beam_width, hyp):
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beam_density = float(hyp.draw(hypothesis.strategies.floats(0.0, 1.0, width=32)))
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@ -55,6 +55,8 @@ PARTIAL_DATA = [
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),
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]
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PARSERS = ["parser"] # TODO: Test beam_parser when ready
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eps = 0.1
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@ -215,7 +217,7 @@ def test_parser_set_sent_starts(en_vocab):
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assert token.head in sent
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@pytest.mark.parametrize("pipe_name", ["parser", "beam_parser"])
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@pytest.mark.parametrize("pipe_name", PARSERS)
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def test_incomplete_data(pipe_name):
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# Test that the parser works with incomplete information
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nlp = English()
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@ -241,7 +243,7 @@ def test_incomplete_data(pipe_name):
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assert doc[2].head.i == 1
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@pytest.mark.parametrize("pipe_name", ["parser", "beam_parser"])
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@pytest.mark.parametrize("pipe_name", PARSERS)
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def test_overfitting_IO(pipe_name):
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# Simple test to try and quickly overfit the dependency parser (normal or beam)
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nlp = English()
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@ -292,6 +294,7 @@ def test_overfitting_IO(pipe_name):
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assert_equal(batch_deps_1, no_batch_deps)
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@pytest.mark.xfail(reason="no beam parser yet")
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def test_beam_parser_scores():
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# Test that we can get confidence values out of the beam_parser pipe
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beam_width = 16
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@ -330,6 +333,7 @@ def test_beam_parser_scores():
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assert 0 - eps <= head_score <= 1 + eps
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@pytest.mark.xfail(reason="no beam parser yet")
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def test_beam_overfitting_IO():
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# Simple test to try and quickly overfit the Beam dependency parser
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nlp = English()
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@ -287,6 +287,7 @@ def test_multiple_predictions():
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dummy_pipe(doc)
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@pytest.mark.xfail(reason="no beam parser yet")
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def test_issue4313():
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""" This should not crash or exit with some strange error code """
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beam_width = 16
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