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Convert values to numpy for label smoothing tests (#12472)

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Adriane Boyd 2023-03-31 13:41:41 +02:00 committed by GitHub
parent ce258670b7
commit 140d53649d
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2 changed files with 9 additions and 5 deletions
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7
spacy/tests/pipeline/test_morphologizer.py
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@ -1,6 +1,8 @@
import pytest import pytest
from numpy.testing import assert_equal, assert_almost_equal from numpy.testing import assert_equal, assert_almost_equal
from thinc.api import get_current_ops
from spacy import util from spacy import util
from spacy.training import Example from spacy.training import Example
from spacy.lang.en import English from spacy.lang.en import English
@ -52,8 +54,9 @@ def test_label_smoothing():
tag_scores, bp_tag_scores = morph_ls.model.begin_update( tag_scores, bp_tag_scores = morph_ls.model.begin_update(
[eg.predicted for eg in train_examples] [eg.predicted for eg in train_examples]
) )
no_ls_grads = morph_no_ls.get_loss(train_examples, tag_scores)[1][0] ops = get_current_ops()
ls_grads = morph_ls.get_loss(train_examples, tag_scores)[1][0] no_ls_grads = ops.to_numpy(morph_no_ls.get_loss(train_examples, tag_scores)[1][0])
ls_grads = ops.to_numpy(morph_ls.get_loss(train_examples, tag_scores)[1][0])
assert_almost_equal(ls_grads / no_ls_grads, 0.94285715) assert_almost_equal(ls_grads / no_ls_grads, 0.94285715)

7
spacy/tests/pipeline/test_tagger.py
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@ -6,7 +6,7 @@ from spacy import util
from spacy.training import Example from spacy.training import Example
from spacy.lang.en import English from spacy.lang.en import English
from spacy.language import Language from spacy.language import Language
from thinc.api import compounding from thinc.api import compounding, get_current_ops
from ..util import make_tempdir from ..util import make_tempdir
@ -85,8 +85,9 @@ def test_label_smoothing():
tag_scores, bp_tag_scores = tagger_ls.model.begin_update( tag_scores, bp_tag_scores = tagger_ls.model.begin_update(
[eg.predicted for eg in train_examples] [eg.predicted for eg in train_examples]
) )
no_ls_grads = tagger_no_ls.get_loss(train_examples, tag_scores)[1][0] ops = get_current_ops()
ls_grads = tagger_ls.get_loss(train_examples, tag_scores)[1][0] no_ls_grads = ops.to_numpy(tagger_no_ls.get_loss(train_examples, tag_scores)[1][0])
ls_grads = ops.to_numpy(tagger_ls.get_loss(train_examples, tag_scores)[1][0])
assert_almost_equal(ls_grads / no_ls_grads, 0.925) assert_almost_equal(ls_grads / no_ls_grads, 0.925)