def test_sample(self):
sys.stdout.write(
'GaussianBinaryLabelRBM -> Performing sample test ...')
numx.random.seed(42)
data_dim = 12
label_dim = 8
input_dim = data_dim + label_dim
hidden_dim = 10
batchsize = 3
rbm = Model.GaussianBinaryLabelRBM(data_dim, label_dim, hidden_dim)
data = numx.random.rand(batchsize, input_dim)
h = rbm.probability_h_given_v(data)
assert numx.all(h.shape == (batchsize, hidden_dim))
h = rbm.sample_h(h)
assert numx.all(h.shape == (batchsize, hidden_dim))
v = rbm.probability_v_given_h(h)
assert numx.all(v.shape == (batchsize, input_dim))
v = rbm.sample_v(v)
assert numx.all(v.shape == (batchsize, input_dim))
assert numx.all(
numx.abs(numx.sum(v[:, data_dim:]) - batchsize) < self.epsilon)
assert numx.all(v[:, 0:data_dim] != 0.0)
assert numx.all(v[:, 0:data_dim] != 1.0)
sys.stdout.flush()
print(' successfully passed!')
sys.stdout.flush()
pass
def test___init__(self):
sys.stdout.write('GaussianBinaryLabelRBM -> Performing init test ...')
numx.random.seed(42)
data_dim = 12
label_dim = 8
input_dim = data_dim + label_dim
hidden_dim = 10
batchsize = 3
rbm = Model.GaussianBinaryLabelRBM(data_dim, label_dim, hidden_dim)
assert numx.all(rbm.w.shape == (input_dim, hidden_dim))
assert numx.all(rbm.bv.shape == (1, input_dim))
assert numx.all(rbm.bh.shape == (1, hidden_dim))
assert numx.all(rbm.data_dim == data_dim)
assert numx.all(rbm.label_dim == label_dim)
assert numx.all(rbm.input_dim == input_dim)
assert numx.all(rbm.output_dim == hidden_dim)
print(' successfully passed!')
sys.stdout.flush()
pass