def test_rew_lambda():
env = supersuit.reward_lambda_v0(new_dummy(), lambda x: x / 10)
env.reset()
obs, rew, done, info = env.step(0)
assert rew == 1.0 / 10
def new_dummy():
return DummyEnv(base_obs, base_obs_space, base_act_spaces)
wrappers = [
supersuit.color_reduction_v0(new_dummy(), "R"),
supersuit.resize_v0(dtype_v0(new_dummy(), np.uint8), x_size=5, y_size=10),
supersuit.resize_v0(dtype_v0(new_dummy(), np.uint8), x_size=5, y_size=10, linear_interp=True),
supersuit.dtype_v0(new_dummy(), np.int32),
supersuit.flatten_v0(new_dummy()),
supersuit.reshape_v0(new_dummy(), (64, 3)),
supersuit.normalize_obs_v0(new_dummy(), env_min=-1, env_max=5.0),
supersuit.frame_stack_v1(new_dummy(), 8),
supersuit.reward_lambda_v0(new_dummy(), lambda x: x / 10),
supersuit.clip_reward_v0(new_dummy()),
supersuit.clip_actions_v0(new_continuous_dummy()),
supersuit.frame_skip_v0(new_dummy(), 4),
supersuit.frame_skip_v0(new_dummy(), (4, 6)),
supersuit.sticky_actions_v0(new_dummy(), 0.75),
supersuit.delay_observations_v0(new_dummy(), 1),
]
@pytest.mark.parametrize("env", wrappers)
def test_basic_wrappers(env):
env.seed(5)
obs = env.reset()
act_space = env.action_space
obs_space = env.observation_space
def test_rew_lambda():
env = supersuit.reward_lambda_v0(new_dummy(), lambda x: x / 10)
env.reset()
assert env.rewards[env.agent_selection] == 1.0 / 10
y_size=10,
linear_interp=True),
supersuit.dtype_v0(knights_archers_zombies_v4.env(), np.int32),
supersuit.flatten_v0(knights_archers_zombies_v4.env()),
supersuit.reshape_v0(knights_archers_zombies_v4.env(), (512 * 512, 3)),
supersuit.normalize_obs_v0(dtype_v0(knights_archers_zombies_v4.env(),
np.float32),
env_min=-1,
env_max=5.0),
supersuit.frame_stack_v1(knights_archers_zombies_v4.env(), 8),
supersuit.pad_observations_v0(knights_archers_zombies_v4.env()),
supersuit.pad_action_space_v0(knights_archers_zombies_v4.env()),
supersuit.black_death_v0(knights_archers_zombies_v4.env()),
supersuit.agent_indicator_v0(knights_archers_zombies_v4.env(), True),
supersuit.agent_indicator_v0(knights_archers_zombies_v4.env(), False),
supersuit.reward_lambda_v0(knights_archers_zombies_v4.env(),
lambda x: x / 10),
supersuit.clip_reward_v0(knights_archers_zombies_v4.env()),
supersuit.clip_actions_v0(prison_v2.env(continuous=True)),
supersuit.frame_skip_v0(knights_archers_zombies_v4.env(), 4),
supersuit.sticky_actions_v0(knights_archers_zombies_v4.env(), 0.75),
supersuit.delay_observations_v0(knights_archers_zombies_v4.env(), 3),
]
@pytest.mark.parametrize("env", wrappers)
def test_pettingzoo_aec_api(env):
api_test.api_test(env)
parallel_wrappers = [
supersuit.frame_stack_v1(knights_archers_zombies_v4.parallel_env(), 8),
)
import supersuit
from supersuit import dtype_v0
import pytest
wrappers = [
supersuit.dtype_v0(generated_agents_parallel_v0.env(), np.int32),
supersuit.flatten_v0(generated_agents_parallel_v0.env()),
supersuit.normalize_obs_v0(
dtype_v0(generated_agents_parallel_v0.env(), np.float32),
env_min=-1,
env_max=5.0,
),
supersuit.frame_stack_v1(generated_agents_parallel_v0.env(), 8),
supersuit.reward_lambda_v0(generated_agents_parallel_v0.env(),
lambda x: x / 10),
supersuit.clip_reward_v0(generated_agents_parallel_v0.env()),
supersuit.nan_noop_v0(generated_agents_parallel_v0.env(), 0),
supersuit.nan_zeros_v0(generated_agents_parallel_v0.env()),
supersuit.nan_random_v0(generated_agents_parallel_v0.env()),
supersuit.frame_skip_v0(generated_agents_parallel_v0.env(), 4),
supersuit.sticky_actions_v0(generated_agents_parallel_v0.env(), 0.75),
supersuit.delay_observations_v0(generated_agents_parallel_v0.env(), 3),
supersuit.max_observation_v0(generated_agents_parallel_v0.env(), 3),
]
@pytest.mark.parametrize("env", wrappers)
def test_pettingzoo_aec_api_par_gen(env):
api_test(env, num_cycles=50)
),
supersuit.dtype_v0(knights_archers_zombies_v10.env(), np.int32),
supersuit.flatten_v0(knights_archers_zombies_v10.env()),
supersuit.reshape_v0(knights_archers_zombies_v10.env(vector_state=False),
(512 * 512, 3)),
supersuit.normalize_obs_v0(dtype_v0(knights_archers_zombies_v10.env(),
np.float32),
env_min=-1,
env_max=5.0),
supersuit.frame_stack_v1(combined_arms_v6.env(), 8),
supersuit.pad_observations_v0(simple_world_comm_v2.env()),
supersuit.pad_action_space_v0(simple_world_comm_v2.env()),
supersuit.black_death_v3(combined_arms_v6.env()),
supersuit.agent_indicator_v0(knights_archers_zombies_v10.env(), True),
supersuit.agent_indicator_v0(knights_archers_zombies_v10.env(), False),
supersuit.reward_lambda_v0(knights_archers_zombies_v10.env(),
lambda x: x / 10),
supersuit.clip_reward_v0(combined_arms_v6.env()),
supersuit.nan_noop_v0(knights_archers_zombies_v10.env(), 0),
supersuit.nan_zeros_v0(knights_archers_zombies_v10.env()),
supersuit.nan_random_v0(chess_v5.env()),
supersuit.nan_random_v0(knights_archers_zombies_v10.env()),
supersuit.frame_skip_v0(combined_arms_v6.env(), 4),
supersuit.sticky_actions_v0(combined_arms_v6.env(), 0.75),
supersuit.delay_observations_v0(combined_arms_v6.env(), 3),
supersuit.max_observation_v0(knights_archers_zombies_v10.env(), 3),
]
@pytest.mark.parametrize("env", wrappers)
def test_pettingzoo_aec_api(env):
api_test(env)
