def test_weights_stay_tied(self, weights_and_gradient_and_groups):
weights, gradient, groups = weights_and_gradient_and_groups
tying = optimization.WeightTying(*groups)
decent = optimization.GradientDecent()
weights = tying(weights)
weights = decent(weights, gradient, 0.1)
self._is_tied(weights, groups)
def test_copy_data(self, weights_and_gradient_and_groups):
weights, _, groups = weights_and_gradient_and_groups
tying = optimization.WeightTying(*groups)
before = weights.copy()
updated = tying(weights)
assert (before.flat == weights.flat).all()
assert updated.flat[0] != 42
weights.flat[0] = 42
assert updated.flat[0] != 42
def test_dont_affect_others(self, weights_and_gradient_and_groups):
weights, _, _ = weights_and_gradient_and_groups
if len(weights.shapes) < 2:
pytest.skip()
group = (np.s_[0, :, :], np.s_[1, :, :])
tying = optimization.WeightTying(group)
updated = tying(weights)
assert (updated[0] == updated[1]).all()
for before, after in zip(weights[2:], updated[2:]):
assert (before == after).all()
def test_shapes_match(self, weights_and_gradient_and_groups):
weights, _, groups = weights_and_gradient_and_groups
tying = optimization.WeightTying(*groups)
updated = tying(weights)
assert weights.shapes == updated.shapes
def test_calculation(self, weights_and_gradient_and_groups):
weights, _, groups = weights_and_gradient_and_groups
tying = optimization.WeightTying(*groups)
updated = tying(weights)
self._is_tied(updated, groups)