def test_composite_rule():
rule = CompositeRule([StepClipping(4), Scale(0.1)])
gradients = {0: shared_floatx(3.0), 1: shared_floatx(4.0)}
result, _ = rule.compute_steps(gradients)
assert_allclose(result[0].eval(), 12 / 50.0)
assert_allclose(result[1].eval(), 16 / 50.0)
class RuleWithUpdates(StepRule):
def __init__(self, updates):
self.updates = updates
def compute_steps(self, previous_steps):
return previous_steps, self.updates
rule = CompositeRule([RuleWithUpdates([(1, 2)]),
RuleWithUpdates([(3, 4)])])
assert rule.compute_steps(None)[1] == [(1, 2), (3, 4)]
def test_composite_rule():
rule = CompositeRule([StepClipping(4), Scale(0.1)])
gradients = {0: shared_floatx(3.0), 1: shared_floatx(4.0)}
result, _ = rule.compute_steps(gradients)
assert_allclose(result[0].eval(), 12 / 50.0)
assert_allclose(result[1].eval(), 16 / 50.0)
class RuleWithUpdates(StepRule):
def __init__(self, updates):
self.updates = updates
def compute_steps(self, previous_steps):
return previous_steps, self.updates
rule = CompositeRule([RuleWithUpdates([(1, 2)]),
RuleWithUpdates([(3, 4)])])
assert rule.compute_steps(None)[1] == [(1, 2), (3, 4)]
def test_composite_rule():
rule = CompositeRule([GradientClipping(4), SteepestDescent(0.1)])
gradients = {0: shared_floatx(3.0), 1: shared_floatx(4.0)}
result = rule.compute_steps(gradients)
assert_allclose(result[0].eval(), -12 / 50.0)
assert_allclose(result[1].eval(), -16 / 50.0)
class RuleWithUpdates(StepRule):
def __init__(self, updates):
self.updates = updates
def additional_updates(self):
return self.updates
rule = CompositeRule([RuleWithUpdates([(1, 2)]),
RuleWithUpdates([(3, 4)])])
assert rule.additional_updates() == [(1, 2), (3, 4)]
