def test_add_factor(self):
"""
Testing output of add_factor() function
"""
expected_logmass = torch.tensor(-100.0)
val = torch.tensor(-1.0)
def model():
add_factor(val, 'exp_util_test') # alpha is 100.0
posterior = Importance(model, num_samples=1).run()
actual_logmass = next(posterior._traces())[1]
self.assertEqual(actual_logmass, expected_logmass)
def test_action_model_add_logmass(self):
"""
Test to see if add_factor() changes logmass
to desired output with Importance sampling
"""
agent = Agent()
state = torch.tensor(1.0)
time_left = torch.tensor(0.0)
dummy_utility = torch.tensor(1.0)
# Create dummy utility function
def dummy_utility_func(state, action, time_left):
return dummy_utility
# Set expected utility to the dummy function
agent.expected_utility = dummy_utility_func
posterior = Importance(agent.action_model,
num_samples=1).run(state, time_left)
actual_logmass = next(posterior._traces(state, time_left))[1]
expected_logmass = 100 * dummy_utility
self.assertEqual(actual_logmass, expected_logmass)