def test_simple_metacurriculum(curriculum_brain_name):
env = Simple1DEnvironment(use_discrete=False)
with patch("builtins.open",
new_callable=mock_open,
read_data=dummy_curriculum_json_str):
curriculum = Curriculum("TestBrain.json")
mc = MetaCurriculumTest({curriculum_brain_name: curriculum})
_check_environment_trains(env, META_CURRICULUM_CONFIG, mc, -100.0)
def test_simple_metacurriculum(curriculum_brain_name):
env = Simple1DEnvironment([BRAIN_NAME], use_discrete=False)
curriculum_config = json.loads(dummy_curriculum_json_str)
mc = MetaCurriculum({curriculum_brain_name: curriculum_config})
_check_environment_trains(env,
TRAINER_CONFIG,
meta_curriculum=mc,
success_threshold=None)
def test_subprocess_env_endtoend(num_envs):
env_manager = SubprocessEnvManager(simple_env_factory,
EngineConfig.default_config(), num_envs)
trainer_config = generate_config(PPO_CONFIG)
# Run PPO using env_manager
_check_environment_trains(
simple_env_factory(0, []),
trainer_config,
env_manager=env_manager,
success_threshold=None,
)
# Note we can't check the env's rewards directly (since they're in separate processes) so we
# check the StatsReporter's debug stat writer's last reward.
assert isinstance(StatsReporter.writers[0], DebugWriter)
assert all(val > 0.99
for val in StatsReporter.writers[0].get_last_rewards().values())
env_manager.close()
def test_subprocess_env_endtoend(num_envs):
def simple_env_factory(worker_id, config):
env = SimpleEnvironment(["1D"], use_discrete=True)
return env
env_manager = SubprocessEnvManager(simple_env_factory,
EngineConfig.default_config(), num_envs)
# Run PPO using env_manager
_check_environment_trains(
simple_env_factory(0, []),
{"1D": PPO_CONFIG},
env_manager=env_manager,
success_threshold=None,
)
# Note we can't check the env's rewards directly (since they're in separate processes) so we
# check the StatsReporter's debug stat writer's last reward.
assert isinstance(StatsReporter.writers[0], DebugWriter)
assert all(val > 0.7
for val in StatsReporter.writers[0].get_last_rewards().values())
env_manager.close()
def test_simple_metacurriculum(curriculum_brain_name):
env = Simple1DEnvironment(use_discrete=False)
curriculum_config = json.loads(dummy_curriculum_json_str)
mc = MetaCurriculum({curriculum_brain_name: curriculum_config})
_check_environment_trains(env, TRAINER_CONFIG, mc, -100.0)
def test_simple_metacurriculum(curriculum_brain_name):
env = SimpleEnvironment([BRAIN_NAME], use_discrete=False)
mc = MetaCurriculum({curriculum_brain_name: dummy_curriculum_config})
_check_environment_trains(env, {BRAIN_NAME: PPO_CONFIG},
meta_curriculum=mc,
success_threshold=None)