def test_compute_from_network():
"""Tests the it works given an arbitrary network and planes.
"""
if not Network.has_connection():
pytest.skip("No server connected.")
network = Network([ReluLayer()])
planes = [np.array([[1.0, 2.0], [3.0, 4.0], [1.0, 2.0]]),
np.array([[3.0, 2.0], [7.0, 4.0], [5.0, 2.0]])]
classifier = PlanesClassifier(network, planes, preimages=True)
classifier.partial_compute()
assert classifier.partially_computed
transformed = network.transform_planes(planes, True, True)
assert all(all(np.allclose(actual_polytope[0], truth_polytope[0]) and
np.allclose(actual_polytope[1], truth_polytope[1])
for actual_polytope, truth_polytope in zip(actual, truth))
for actual, truth in zip(classifier.transformed_planes,
transformed))
classified = classifier.compute()
assert len(classified) == len(planes)
regions, labels = classified[0]
assert np.allclose(regions, planes[0])
assert np.allclose(labels, [1])
regions, labels = classified[1]
assert np.allclose(regions, planes[1])
assert np.allclose(labels, [0])
# Ensure it doesn't re-compute things it already knows.
assert classifier.compute() is classified
def test_compute_from_syrenn():
"""Tests the it works given an arbitrary network and planes.
"""
if not Network.has_connection():
pytest.skip("No server connected.")
network = Network([ReluLayer()])
planes = [np.array([[1.0, 2.0], [3.0, 4.0], [1.0, 2.0]]),
np.array([[3.0, 2.0], [7.0, 4.0], [5.0, 2.0]])]
transformed = network.transform_planes(planes, True, True)
classifier = PlanesClassifier.from_syrenn(transformed)
assert classifier.partially_computed
classified = classifier.compute()
assert len(classified) == len(planes)
regions, labels = classified[0]
assert np.allclose(regions, planes[0])
assert np.allclose(labels, [1])
regions, labels = classified[1]
assert np.allclose(regions, planes[1])
assert np.allclose(labels, [0])
# Ensure it doesn't re-compute things it already knows.
assert classifier.compute() is classified
