def test_deterministic(space: Space, n: int, base_seed: int):
"""Tests the batched spaces are deterministic by using a copied version"""
# Copy the spaces and check that the np_random are not reference equal
space_a = space
space_a.seed(base_seed)
space_b = copy.deepcopy(space_a)
assert_rng_equal(space_a.np_random, space_b.np_random)
assert space_a.np_random is not space_b.np_random
# Batch the spaces and check that the np_random are not reference equal
space_a_batched = batch_space(space_a, n)
space_b_batched = batch_space(space_b, n)
assert_rng_equal(space_a_batched.np_random, space_b_batched.np_random)
assert space_a_batched.np_random is not space_b_batched.np_random
# Create that the batched space is not reference equal to the origin spaces
assert space_a.np_random is not space_a_batched.np_random
# Check that batched space a and b random number generator are not effected by the original space
space_a.sample()
space_a_batched_sample = space_a_batched.sample()
space_b_batched_sample = space_b_batched.sample()
for a_sample, b_sample in zip(
iterate(space_a_batched, space_a_batched_sample),
iterate(space_b_batched, space_b_batched_sample),
):
if isinstance(a_sample, tuple):
assert len(a_sample) == len(b_sample)
for a_subsample, b_subsample in zip(a_sample, b_sample):
assert_array_equal(a_subsample, b_subsample)
else:
assert_array_equal(a_sample, b_sample)
def test_sync_vector_env_seed():
env = make_env("BipedalWalker-v3", seed=123)()
sync_vector_env = SyncVectorEnv([make_env("BipedalWalker-v3", seed=123)])
assert_rng_equal(env.action_space.np_random, sync_vector_env.action_space.np_random)
for _ in range(100):
env_action = env.action_space.sample()
vector_action = sync_vector_env.action_space.sample()
assert np.all(env_action == vector_action)
def test_sync_vector_determinism(spec: EnvSpec, seed: int = 123, n: int = 3):
"""Check that for all environments, the sync vector envs produce the same action samples using the same seeds"""
env_1 = SyncVectorEnv([make_env(spec.id, seed=seed) for _ in range(n)])
env_2 = SyncVectorEnv([make_env(spec.id, seed=seed) for _ in range(n)])
assert_rng_equal(env_1.action_space.np_random, env_2.action_space.np_random)
for _ in range(100):
env_1_samples = env_1.action_space.sample()
env_2_samples = env_2.action_space.sample()
assert np.all(env_1_samples == env_2_samples)
def test_rng_different_at_each_index(space: Space, n: int, base_seed: int):
"""
Tests that the rng values produced at each index are different
to prevent if the rng is copied for each subspace
"""
space.seed(base_seed)
batched_space = batch_space(space, n)
assert space.np_random is not batched_space.np_random
assert_rng_equal(space.np_random, batched_space.np_random)
batched_sample = batched_space.sample()
sample = list(iterate(batched_space, batched_sample))
assert not all(np.all(element == sample[0]) for element in sample), sample