def test_as_training_data_produces_correct_numpy_arrays_with_background_instances(
self):
instance = IndexedMultipleTrueFalseInstance([
IndexedBackgroundInstance(IndexedTrueFalseInstance([1, 2], False),
[
IndexedTrueFalseInstance([2], None),
IndexedTrueFalseInstance([3], None)
]),
IndexedBackgroundInstance(IndexedTrueFalseInstance([3, 4], False),
[
IndexedTrueFalseInstance([5], None),
IndexedTrueFalseInstance([6], None)
]),
IndexedBackgroundInstance(IndexedTrueFalseInstance([5, 6], False),
[
IndexedTrueFalseInstance([8], None),
IndexedTrueFalseInstance([9], None)
]),
IndexedBackgroundInstance(IndexedTrueFalseInstance([7, 8], True), [
IndexedTrueFalseInstance([11], None),
IndexedTrueFalseInstance([12], None)
]),
], 3)
(word_arrays, background_arrays), label = instance.as_training_data()
assert numpy.all(label == numpy.asarray([0, 0, 0, 1]))
assert numpy.all(
word_arrays == numpy.asarray([[1, 2], [3, 4], [5, 6], [7, 8]]))
assert numpy.all(background_arrays == numpy.asarray(
[[[2], [3]], [[5], [6]], [[8], [9]], [[11], [12]]]))
def setUp(self):
# We'll just test with underlying IndexedTrueFalseInstances for most of these, because it's
# simpler.
self.instance = IndexedMultipleTrueFalseInstance([
IndexedTrueFalseInstance([1], False),
IndexedTrueFalseInstance([2, 3, 4], False),
IndexedTrueFalseInstance([5, 6], True),
IndexedTrueFalseInstance([7, 8], False)
], 2)
class TestIndexedMultipleTrueFalseInstance(TestCase):
def setUp(self):
# We'll just test with underlying IndexedTrueFalseInstances for most of these, because it's
# simpler.
self.instance = IndexedMultipleTrueFalseInstance([
IndexedTrueFalseInstance([1], False),
IndexedTrueFalseInstance([2, 3, 4], False),
IndexedTrueFalseInstance([5, 6], True),
IndexedTrueFalseInstance([7, 8], False)
], 2)
def test_get_lengths_returns_max_of_options(self):
assert self.instance.get_lengths() == {
'word_sequence_length': 3,
'num_options': 4
}
def test_pad_calls_pad_on_all_options(self):
self.instance.pad({'word_sequence_length': 3, 'num_options': 4})
assert self.instance.options[0].word_indices == [0, 0, 1]
assert self.instance.options[1].word_indices == [2, 3, 4]
assert self.instance.options[2].word_indices == [0, 5, 6]
assert self.instance.options[3].word_indices == [0, 7, 8]
def test_pad_adds_empty_options_when_necessary(self):
self.instance.pad({'word_sequence_length': 2, 'num_options': 5})
assert self.instance.options[0].word_indices == [0, 1]
assert self.instance.options[1].word_indices == [3, 4]
assert self.instance.options[2].word_indices == [5, 6]
assert self.instance.options[3].word_indices == [7, 8]
assert self.instance.options[4].word_indices == [0, 0]
assert len(self.instance.options) == 5
def test_pad_removes_options_when_necessary(self):
self.instance.pad({'word_sequence_length': 1, 'num_options': 1})
assert self.instance.options[0].word_indices == [1]
assert len(self.instance.options) == 1
def test_as_training_data_produces_correct_numpy_arrays_with_simple_instances(
self):
self.instance.pad({'word_sequence_length': 3, 'num_options': 4})
inputs, label = self.instance.as_training_data()
assert numpy.all(label == numpy.asarray([0, 0, 1, 0]))
assert numpy.all(inputs == numpy.asarray([[0, 0, 1], [2, 3, 4],
[0, 5, 6], [0, 7, 8]]))
def test_as_training_data_produces_correct_numpy_arrays_with_background_instances(
self):
instance = IndexedMultipleTrueFalseInstance([
IndexedBackgroundInstance(IndexedTrueFalseInstance([1, 2], False),
[
IndexedTrueFalseInstance([2], None),
IndexedTrueFalseInstance([3], None)
]),
IndexedBackgroundInstance(IndexedTrueFalseInstance([3, 4], False),
[
IndexedTrueFalseInstance([5], None),
IndexedTrueFalseInstance([6], None)
]),
IndexedBackgroundInstance(IndexedTrueFalseInstance([5, 6], False),
[
IndexedTrueFalseInstance([8], None),
IndexedTrueFalseInstance([9], None)
]),
IndexedBackgroundInstance(IndexedTrueFalseInstance([7, 8], True), [
IndexedTrueFalseInstance([11], None),
IndexedTrueFalseInstance([12], None)
]),
], 3)
(word_arrays, background_arrays), label = instance.as_training_data()
assert numpy.all(label == numpy.asarray([0, 0, 0, 1]))
assert numpy.all(
word_arrays == numpy.asarray([[1, 2], [3, 4], [5, 6], [7, 8]]))
assert numpy.all(background_arrays == numpy.asarray(
[[[2], [3]], [[5], [6]], [[8], [9]], [[11], [12]]]))