def test_random_split_gives_error_on_wrong_ratios(self):
source_dataset = Dataset.from_iterable([DatasetItem(id=1)])
with self.assertRaises(Exception):
transforms.RandomSplit(source_dataset, splits=[
('train', 0.5),
('test', 0.7),
])
with self.assertRaises(Exception):
transforms.RandomSplit(source_dataset, splits=[])
with self.assertRaises(Exception):
transforms.RandomSplit(source_dataset, splits=[
('train', -0.5),
('test', 1.5),
])
def test_random_split_gives_error_on_wrong_ratios(self):
class SrcExtractor(Extractor):
def __iter__(self):
return iter([DatasetItem(id=1)])
with self.assertRaises(Exception):
transforms.RandomSplit(SrcExtractor(),
splits=[
('train', 0.5),
('test', 0.7),
])
with self.assertRaises(Exception):
transforms.RandomSplit(SrcExtractor(), splits=[])
with self.assertRaises(Exception):
transforms.RandomSplit(SrcExtractor(),
splits=[
('train', -0.5),
('test', 1.5),
])
def test_random_split(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id=1, subset="a"),
DatasetItem(id=2, subset="a"),
DatasetItem(id=3, subset="b"),
DatasetItem(id=4, subset="b"),
DatasetItem(id=5, subset="b"),
DatasetItem(id=6, subset=""),
DatasetItem(id=7, subset=""),
])
actual = transforms.RandomSplit(source_dataset, splits=[
('train', 4.0 / 7.0),
('test', 3.0 / 7.0),
])
self.assertEqual(4, len(actual.get_subset('train')))
self.assertEqual(3, len(actual.get_subset('test')))
def test_random_split(self):
class SrcExtractor(Extractor):
def __iter__(self):
return iter([
DatasetItem(id=1, subset="a"),
DatasetItem(id=2, subset="a"),
DatasetItem(id=3, subset="b"),
DatasetItem(id=4, subset="b"),
DatasetItem(id=5, subset="b"),
DatasetItem(id=6, subset=""),
DatasetItem(id=7, subset=""),
])
actual = transforms.RandomSplit(SrcExtractor(),
splits=[
('train', 4.0 / 7.0),
('test', 3.0 / 7.0),
])
self.assertEqual(4, len(actual.get_subset('train')))
self.assertEqual(3, len(actual.get_subset('test')))
