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change test to check difference in distributions

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vinit 2023-02-17 18:17:58 +05:30
parent 3b9e147b28
commit b0929271a8
1 changed files with 9 additions and 10 deletions
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19
spacy/tests/pipeline/test_tagger.py
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@ -1,5 +1,5 @@
import pytest import pytest
from numpy.testing import assert_equal from numpy.testing import assert_equal, assert_array_almost_equal
from spacy.attrs import TAG from spacy.attrs import TAG
from spacy import util from spacy import util
@ -68,7 +68,6 @@ PARTIAL_DATA = [
def test_label_smoothing(): def test_label_smoothing():
util.fix_random_seed()
nlp = Language() nlp = Language()
tagger_no_ls = nlp.add_pipe( tagger_no_ls = nlp.add_pipe(
"tagger", "no_label_smoothing", config=dict(label_smoothing=False) "tagger", "no_label_smoothing", config=dict(label_smoothing=False)
@ -83,14 +82,14 @@ def test_label_smoothing():
tagger_ls.add_label(tag) tagger_ls.add_label(tag)
for t in TRAIN_DATA: for t in TRAIN_DATA:
train_examples.append(Example.from_dict(nlp.make_doc(t[0]), t[1])) train_examples.append(Example.from_dict(nlp.make_doc(t[0]), t[1]))
optimizer = nlp.initialize(get_examples=lambda: train_examples)
for i in range(5): nlp.initialize(get_examples=lambda: train_examples)
losses = {} tag_scores, bp_tag_scores = tagger_ls.model.begin_update(
nlp.update(train_examples, sgd=optimizer, losses=losses) [eg.predicted for eg in train_examples]
assert losses == { )
"no_label_smoothing": 1.4892945885658264, no_ls_probs = tagger_no_ls.get_loss(train_examples, tag_scores)[1][0]
"label_smoothing": 1.1432453989982605, ls_probs = tagger_ls.get_loss(train_examples, tag_scores)[1][0]
} assert_array_almost_equal((ls_probs - no_ls_probs)[0], [0.05, -0.025, -0.025])
def test_no_label(): def test_no_label():