spaCy/spacy/tests/regression/test_issue4924.py

import pytest
from spacy.language import Language


def test_issue4924():
    nlp = Language()
    docs_golds = [("", {})]
    nlp.evaluate(docs_golds)
fix nlp.evaluate (#4924) (#4925) * new file: test_issue4924.py * modified: spacy/gold.pyx * modified: test_issue4924.py for python2 2020-01-20 14:17:46 +03:00			`import pytest`
Tidy up and fix issues 2020-02-18 17:17:03 +03:00			`from spacy.language import Language`
fix nlp.evaluate (#4924) (#4925) * new file: test_issue4924.py * modified: spacy/gold.pyx * modified: test_issue4924.py for python2 2020-01-20 14:17:46 +03:00

Merge branch 'master' into tmp/sync 2020-03-26 15:38:14 +03:00			`def test_issue4924():`
Tidy up and fix issues 2020-02-18 17:17:03 +03:00			`nlp = Language()`
fix nlp.evaluate (#4924) (#4925) * new file: test_issue4924.py * modified: spacy/gold.pyx * modified: test_issue4924.py for python2 2020-01-20 14:17:46 +03:00			`docs_golds = [("", {})]`
Check whether doc is instantiated in Example.get_gold_parses() (#5167) * Check whether doc is instantiated When creating docs to pair with gold parses, modify test to check whether a doc is unset rather than whether it contains tokens. * Restore test of evaluate on an empty doc * Set a minimal gold.orig for the scorer Without a minimal gold.orig the scorer can't evaluate empty docs. This is the v3 equivalent of #4925. 2020-03-29 14:57:00 +03:00			`nlp.evaluate(docs_golds)`