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Don't train in any test_save_activations test
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@ -1212,11 +1212,7 @@ def test_save_activations():
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assert "Q2146908" in entity_linker.kb.vocab.strings
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assert "Q2146908" in entity_linker.kb.vocab.strings
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# initialize the NEL pipe
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# initialize the NEL pipe
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optimizer = nlp.initialize(get_examples=lambda: train_examples)
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nlp.initialize(get_examples=lambda: train_examples)
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for i in range(2):
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losses = {}
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nlp.update(train_examples, sgd=optimizer, losses=losses)
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nO = entity_linker.model.get_dim("nO")
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nO = entity_linker.model.get_dim("nO")
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@ -426,7 +426,7 @@ def test_save_activations():
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nlp = English()
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nlp = English()
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spancat = nlp.add_pipe("spancat", config={"spans_key": SPAN_KEY})
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spancat = nlp.add_pipe("spancat", config={"spans_key": SPAN_KEY})
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train_examples = make_examples(nlp)
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train_examples = make_examples(nlp)
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optimizer = nlp.initialize(get_examples=lambda: train_examples)
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nlp.initialize(get_examples=lambda: train_examples)
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nO = spancat.model.get_dim("nO")
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nO = spancat.model.get_dim("nO")
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assert nO == 2
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assert nO == 2
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assert set(spancat.labels) == {"LOC", "PERSON"}
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assert set(spancat.labels) == {"LOC", "PERSON"}
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