def _register_all():
from ray.rllib.agents.trainer import Trainer, with_common_config
from ray.rllib.agents.registry import ALGORITHMS, get_agent_class
from ray.rllib.contrib.registry import CONTRIBUTED_ALGORITHMS
for key in list(ALGORITHMS.keys()) + list(CONTRIBUTED_ALGORITHMS.keys(
)) + ["__fake", "__sigmoid_fake_data", "__parameter_tuning"]:
register_trainable(key, get_agent_class(key))
def _see_contrib(name):
"""Returns dummy agent class warning algo is in contrib/."""
class _SeeContrib(Trainer):
_name = "SeeContrib"
_default_config = with_common_config({})
def setup(self, config):
raise NameError(
"Please run `contrib/{}` instead.".format(name))
return _SeeContrib
# also register the aliases minus contrib/ to give a good error message
for key in list(CONTRIBUTED_ALGORITHMS.keys()):
assert key.startswith("contrib/")
alias = key.split("/", 1)[1]
register_trainable(alias, _see_contrib(alias))
def _register_all():
from ray.rllib.agents.registry import ALGORITHMS
from ray.rllib.contrib.registry import CONTRIBUTED_ALGORITHMS
for key in list(ALGORITHMS.keys()) + list(CONTRIBUTED_ALGORITHMS.keys(
)) + ["__fake", "__sigmoid_fake_data", "__parameter_tuning"]:
from ray.rllib.agents.registry import get_agent_class
register_trainable(key, get_agent_class(key))
def _register_all():
from ray.rllib.agents.registry import ALGORITHMS
from ray.rllib.contrib.registry import CONTRIBUTED_ALGORITHMS
for key in list(ALGORITHMS.keys()) + list(CONTRIBUTED_ALGORITHMS.keys(
)) + ["__fake", "__sigmoid_fake_data", "__parameter_tuning"]:
from ray.rllib.agents.registry import get_agent_class
register_trainable(key, get_agent_class(key))
type=str,
default="simple",
choices=scenarios.__all__,
help="Scenario selection, default is `simple`")
parser.add_argument("--n_epoch",
type=int,
default=100,
help="Learning episodes.")
parser.add_argument("--interval",
type=int,
default=20,
help="Save interval, defaut is 20.")
parser.add_argument("--run",
type=str,
default="PG",
choices=set(ALGORITHMS.keys()))
parser.add_argument("--share", action="store_true")
parser.add_argument("--n_workers", type=int, default=2)
parser.add_argument("--n_gpus", type=float, default=1.)
parser.add_argument("--n_cpu_per_worker", type=float, default=0.)
parser.add_argument("--s_batch_size", type=int, default=200)
parser.add_argument("--t_batch_size", type=int, default=200)
parser.add_argument("--config",
type=str,
default="simple_env_config.json",
help="Environment configuration filename.")
args = parser.parse_args()
env_config = utils.load_env_config(CONFIG_BACKUP, args.config)
env = engine.Environment(env_config,
def test_algo_import(self):
for name, func in ALGORITHMS.items():
func()