2020-10-08 01:43:46 +03:00
|
|
|
# coding: utf8
|
|
|
|
from __future__ import unicode_literals
|
|
|
|
|
|
|
|
from spacy.lang.en import English
|
|
|
|
from spacy.util import fix_random_seed
|
|
|
|
|
|
|
|
|
|
|
|
def test_issue6177():
|
|
|
|
"""Test that after fixing the random seed, the results of the pipeline are truly identical"""
|
|
|
|
|
|
|
|
# NOTE: no need to transform this code to v3 when 'master' is merged into 'develop'.
|
|
|
|
# A similar test exists already for v3: test_issue5551
|
|
|
|
# This is just a backport
|
|
|
|
results = []
|
|
|
|
for i in range(3):
|
|
|
|
fix_random_seed(0)
|
|
|
|
nlp = English()
|
|
|
|
example = (
|
|
|
|
"Once hot, form ping-pong-ball-sized balls of the mixture, each weighing roughly 25 g.",
|
|
|
|
{"cats": {"Labe1": 1.0, "Label2": 0.0, "Label3": 0.0}},
|
|
|
|
)
|
|
|
|
textcat = nlp.create_pipe("textcat")
|
|
|
|
nlp.add_pipe(textcat)
|
|
|
|
for label in set(example[1]["cats"]):
|
|
|
|
textcat.add_label(label)
|
2020-11-23 14:29:35 +03:00
|
|
|
# Train
|
|
|
|
optimizer = nlp.begin_training()
|
|
|
|
text, annots = example
|
|
|
|
nlp.update([text], [annots], sgd=optimizer)
|
2020-10-08 01:43:46 +03:00
|
|
|
# Store the result of each iteration
|
2020-11-23 14:29:35 +03:00
|
|
|
result = textcat.model.predict([nlp.make_doc(text)])
|
2020-10-08 01:43:46 +03:00
|
|
|
results.append(list(result[0]))
|
|
|
|
|
|
|
|
# All results should be the same because of the fixed seed
|
|
|
|
assert len(results) == 3
|
|
|
|
assert results[0] == results[1]
|
2020-11-23 14:29:35 +03:00
|
|
|
assert results[0] == results[2]
|