def test_batch_normalized_mlp_allocation():
"""Test that BatchNormalizedMLP performs allocation correctly."""
mlp = BatchNormalizedMLP([Tanh(), Tanh()], [5, 7, 9])
mlp.allocate()
assert mlp.activations[0].children[0].input_dim == 7
assert mlp.activations[1].children[0].input_dim == 9
assert not any(l.use_bias for l in mlp.linear_transformations)
def test_batch_normalized_mlp_learn_scale_propagated_at_alloc():
"""Test that setting learn_scale on a BatchNormalizedMLP works."""
mlp = BatchNormalizedMLP([Tanh(), Tanh()], [5, 7, 9], learn_scale=False)
assert not mlp.learn_scale
assert all(act.children[0].learn_scale for act in mlp.activations)
mlp.allocate()
assert not any(act.children[0].learn_scale for act in mlp.activations)
def test_batch_normalized_mlp_mean_only_propagated_at_alloc():
"""Test that setting mean_only on a BatchNormalizedMLP works."""
mlp = BatchNormalizedMLP([Tanh(), Tanh()], [5, 7, 9], mean_only=True)
assert mlp.mean_only
assert not any(act.children[0].mean_only for act in mlp.activations)
mlp.allocate()
assert all(act.children[0].mean_only for act in mlp.activations)
def test_batch_normalized_mlp_learn_scale_propagated_at_alloc():
"""Test that setting learn_scale on a BatchNormalizedMLP works."""
mlp = BatchNormalizedMLP([Tanh(), Tanh()], [5, 7, 9],
learn_scale=False)
assert not mlp.learn_scale
assert all(act.children[0].learn_scale for act in mlp.activations)
mlp.allocate()
assert not any(act.children[0].learn_scale for act in mlp.activations)
def test_batch_normalized_mlp_mean_only_propagated_at_alloc():
"""Test that setting mean_only on a BatchNormalizedMLP works."""
mlp = BatchNormalizedMLP([Tanh(), Tanh()], [5, 7, 9],
mean_only=True)
assert mlp.mean_only
assert not any(act.children[0].mean_only for act in mlp.activations)
mlp.allocate()
assert all(act.children[0].mean_only for act in mlp.activations)
