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Fix Spancat test.
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3a0a3854f7
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@ -865,17 +865,17 @@ def test_cli_find_threshold(capsys):
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for t in [
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(
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"I'm angry and confused in the Bank of America.",
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"I am angry and confused in the Bank of America.",
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{
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"cats": {"ANGRY": 1.0, "CONFUSED": 1.0, "HAPPY": 0.0},
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"spans": {"sc": [(7, 10, "ORG")]},
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"spans": {"sc": [(31, 46, "ORG")]},
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},
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),
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(
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"I'm confused but happy in New York.",
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"I am confused but happy in New York.",
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{
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"cats": {"ANGRY": 0.0, "CONFUSED": 1.0, "HAPPY": 1.0},
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"spans": {"sc": [(6, 7, "GPE")]},
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"spans": {"sc": [(27, 35, "GPE")]},
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},
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),
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]:
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@ -903,12 +903,9 @@ def test_cli_find_threshold(capsys):
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if isinstance(comp, TextCategorizer):
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for label in textcat_labels:
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comp.add_label(label)
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if isinstance(comp, SpanCategorizer):
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comp.add_label("GPE")
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comp.add_label("ORG")
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_nlp.initialize()
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_examples = make_examples(_nlp)
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_nlp.initialize(get_examples=lambda: _examples)
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for i in range(5):
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_nlp.update(_examples)
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@ -936,9 +933,8 @@ def test_cli_find_threshold(capsys):
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== numpy.linspace(0, 1, 10)[1]
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)
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# todo fix spancat test
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# Specifying name of non-MultiLabel_TextCategorizer component should fail.
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nlp, _ = init_nlp((("spancat", {"spans_key": "sc", "threshold": 0.5}),))
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nlp, _ = init_nlp((("spancat", {}),))
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with make_tempdir() as nlp_dir:
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nlp.to_disk(nlp_dir)
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assert (
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