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)