def test_residual_dbn_forward():
new_residual_dbn = residual_dbn.ResidualDBN(n_visible=784,
n_hidden=(128, 128),
steps=(1, 1),
learning_rate=(0.1, 0.1),
momentum=(0, 0),
decay=(0, 0),
temperature=(1, 1),
use_gpu=False)
v = torch.ones(1, 784)
probs = new_residual_dbn.forward(v)
assert probs.size(1) == 128
def test_residual_dbn_zetta2_setter():
new_residual_dbn = residual_dbn.ResidualDBN()
try:
new_residual_dbn.zetta2 = "a"
except:
new_residual_dbn.zetta2 = 0.1
assert new_residual_dbn.zetta2 == 0.1
try:
new_residual_dbn.zetta2 = -1
except:
new_residual_dbn.zetta2 = 0.1
assert new_residual_dbn.zetta2 == 0.1
def test_residual_dbn_zetta1_setter():
new_residual_dbn = residual_dbn.ResidualDBN()
try:
new_residual_dbn.zetta1 = 'a'
except:
new_residual_dbn.zetta1 = 0.1
assert new_residual_dbn.zetta1 == 0.1
try:
new_residual_dbn.zetta1 = -1
except:
new_residual_dbn.zetta1 = 0.1
assert new_residual_dbn.zetta1 == 0.1
def test_residual_dbn_calculate_residual():
new_residual_dbn = residual_dbn.ResidualDBN(
n_visible=784,
n_hidden=(128, 128),
steps=(1, 1),
learning_rate=(0.1, 0.1),
momentum=(0, 0),
decay=(0, 0),
temperature=(1, 1),
use_gpu=False,
)
v = torch.ones(1, 784)
res = new_residual_dbn.calculate_residual(v)
assert res.size(1) == 784
def test_residual_dbn_zetta1():
new_residual_dbn = residual_dbn.ResidualDBN()
assert new_residual_dbn.zetta1 == 1