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35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from spacy.lang.en import English
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from spacy.util import fix_random_seed
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def test_issue6177():
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"""Test that after fixing the random seed, the results of the pipeline are truly identical"""
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# NOTE: no need to transform this code to v3 when 'master' is merged into 'develop'.
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# A similar test exists already for v3: test_issue5551
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# This is just a backport
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results = []
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for i in range(3):
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fix_random_seed(0)
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nlp = English()
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example = (
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"Once hot, form ping-pong-ball-sized balls of the mixture, each weighing roughly 25 g.",
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{"cats": {"Labe1": 1.0, "Label2": 0.0, "Label3": 0.0}},
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)
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textcat = nlp.create_pipe("textcat")
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nlp.add_pipe(textcat)
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for label in set(example[1]["cats"]):
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textcat.add_label(label)
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nlp.begin_training()
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# Store the result of each iteration
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result = textcat.model.predict([nlp.make_doc(example[0])])
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results.append(list(result[0]))
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# All results should be the same because of the fixed seed
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assert len(results) == 3
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assert results[0] == results[1]
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assert results[0] == results[2] |