def test_random_space():
for _ in range(100):
obs_spec = create_random_space()
act_spec = create_random_space()
print(obs_spec)
print(act_spec)
c1 = DoubleQCritic(obs_spec, act_spec, [60, 50])
c2 = DoubleVCritic(obs_spec, [60, 50])
obs = torchify(obs_spec.sample())
act = torchify(act_spec.sample())
c1.forward(obs, act)
c2.forward(obs)
def test_integration():
obs_spec = Box(low=np.zeros(10, dtype=np.float32),
high=np.ones(10, dtype=np.float32))
act_spec = Box(low=np.zeros(3, dtype=np.float32),
high=np.ones(3, dtype=np.float32))
c1 = DoubleQCritic(obs_spec, act_spec, [60, 50])
c2 = DoubleVCritic(obs_spec, [60, 50])
obs = torch.rand((100, 10))
act = torch.rand((100, 3))
q = c1.forward(obs, act)
assert q.shape == (100, 1)
v = c2.forward(obs)
assert v.shape == (100, 1)