def test_decay_period(env):
policy = ConstantPolicy(env.action_space.sample())
exp_policy = AddGaussianNoise(env,
policy,
total_timesteps=2,
max_sigma=1.,
min_sigma=0.)
assert (exp_policy.get_action(None)[0] != policy.get_action(None)[0]).all()
assert (exp_policy.get_action(None)[0] != policy.get_action(None)[0]).all()
assert (exp_policy.get_action(None)[0] == policy.get_action(None)[0]).all()
def test_params(env):
policy1 = ConstantPolicy(env.action_space.sample())
policy2 = ConstantPolicy(env.action_space.sample())
assert (policy1.get_action(None)[0] != policy2.get_action(None)[0]).all()
exp_policy1 = AddGaussianNoise(env, policy1, 1)
exp_policy2 = AddGaussianNoise(env, policy2, 1)
exp_policy2.get_action(None)
assert exp_policy1._sigma() != exp_policy2._sigma()
exp_policy1.set_param_values(exp_policy2.get_param_values())
assert (policy1.get_action(None)[0] == policy2.get_action(None)[0]).all()
assert exp_policy1._sigma() == exp_policy2._sigma()
def test_update(env):
policy = ConstantPolicy(env.action_space.sample())
exp_policy = AddGaussianNoise(env,
policy,
total_timesteps=10,
max_sigma=1.,
min_sigma=0.)
exp_policy.get_action(None)
exp_policy.get_action(None)
DummyBatch = collections.namedtuple('EpisodeBatch', ['lengths'])
batch = DummyBatch(np.array([1, 2]))
# new sigma will be 1 - 0.1 * (1 + 2) = 0.7
exp_policy.update(batch)
assert np.isclose(exp_policy._sigma(), 0.7)
exp_policy.get_action(None)
batch = DummyBatch(np.array([1, 1, 2]))
# new sigma will be 0.7 - 0.1 * (1 + 1 + 2) = 0.3
exp_policy.update(batch)
assert np.isclose(exp_policy._sigma(), 0.3)