def test_single_positive_sample():
nn_state = PositiveWaveFunction(10, 7, gpu=False)
sample = nn_state.sample(k=10).squeeze()
h_sample = nn_state.sample_h_given_v(sample)
v_prob = nn_state.prob_v_given_h(h_sample)
msg = "Single hidden sample should give a "
assert v_prob.dim() == 1, msg
def test_sampling_with_overwrite():
nn_state = PositiveWaveFunction(10, gpu=False)
old_state = torch.empty(100, 10).bernoulli_().to(dtype=torch.double)
initial_state = old_state.clone()
sample = nn_state.sample(k=10, initial_state=initial_state, overwrite=True)
assert torch.equal(sample, initial_state), "initial_state did not get overwritten!"
assert not torch.equal(sample, old_state), "Markov Chain did not get updated!"