def test_sanitize_action_one_agent_done(mock_env):
mock_spec = create_mock_group_spec(vector_action_space_type="discrete",
vector_action_space_size=[2, 2, 3])
mock_step = create_mock_vector_step_result(num_agents=5)
mock_step.agent_id = np.array(range(5))
setup_mock_unityenvironment(mock_env, mock_spec, mock_step)
env = UnityEnv(" ", use_visual=False, multiagent=True)
received_step_result = create_mock_vector_step_result(num_agents=6)
received_step_result.agent_id = np.array(range(6))
# agent #3 (id = 2) is Done
received_step_result.done = np.array([False] * 2 + [True] + [False] * 3)
sanitized_result = env._sanitize_info(received_step_result)
for expected_agent_id, agent_id in zip([0, 1, 5, 3, 4],
sanitized_result.agent_id):
assert expected_agent_id == agent_id
def test_sanitize_action_single_agent_multiple_done(mock_env):
mock_spec = create_mock_group_spec(vector_action_space_type="discrete",
vector_action_space_size=[2, 2, 3])
mock_step = create_mock_vector_step_result(num_agents=1)
mock_step.agent_id = np.array(range(1))
setup_mock_unityenvironment(mock_env, mock_spec, mock_step)
env = UnityEnv(" ", use_visual=False, multiagent=False)
received_step_result = create_mock_vector_step_result(num_agents=3)
received_step_result.agent_id = np.array(range(3))
# original agent (id = 0) is Done
# so is the "new" agent (id = 1)
done = [True, True, False]
received_step_result.done = np.array(done)
sanitized_result = env._sanitize_info(received_step_result)
for expected_agent_id, agent_id in zip([2], sanitized_result.agent_id):
assert expected_agent_id == agent_id
def test_sanitize_action_shuffled_id(mock_env):
mock_spec = create_mock_group_spec(vector_action_space_type="discrete",
vector_action_space_size=[2, 2, 3])
mock_step = create_mock_vector_step_result(num_agents=5)
mock_step.agent_id = np.array(range(5))
setup_mock_unityenvironment(mock_env, mock_spec, mock_step)
env = UnityEnv(" ", use_visual=False, multiagent=True)
shuffled_step_result = create_mock_vector_step_result(num_agents=5)
shuffled_order = [4, 2, 3, 1, 0]
shuffled_step_result.reward = np.array(shuffled_order)
shuffled_step_result.agent_id = np.array(shuffled_order)
sanitized_result = env._sanitize_info(shuffled_step_result)
for expected_reward, reward in zip(range(5), sanitized_result.reward):
assert expected_reward == reward
for expected_agent_id, agent_id in zip(range(5),
sanitized_result.agent_id):
assert expected_agent_id == agent_id
def test_sanitize_action_new_agent_done(mock_env):
mock_spec = create_mock_group_spec(vector_action_space_type="discrete",
vector_action_space_size=[2, 2, 3])
mock_step = create_mock_vector_step_result(num_agents=3)
mock_step.agent_id = np.array(range(5))
setup_mock_unityenvironment(mock_env, mock_spec, mock_step)
env = UnityEnv(" ", use_visual=False, multiagent=True)
received_step_result = create_mock_vector_step_result(num_agents=7)
received_step_result.agent_id = np.array(range(7))
# agent #3 (id = 2) is Done
# so is the "new" agent (id = 5)
done = [False] * 7
done[2] = True
done[5] = True
received_step_result.done = np.array(done)
sanitized_result = env._sanitize_info(received_step_result)
for expected_agent_id, agent_id in zip([0, 1, 6, 3, 4],
sanitized_result.agent_id):
assert expected_agent_id == agent_id