def make_mujoco_env(env_id, seed, allow_early_resets=True):
"""
Create a wrapped, monitored gym.Env for MuJoCo.
:param env_id: (str) the environment ID
:param seed: (int) the inital seed for RNG
:param allow_early_resets: (bool) allows early reset of the environment
:return: (Gym Environment) The mujoco environment
"""
set_global_seeds(seed + 10000 * mpi_rank_or_zero())
env = gym.make(env_id)
env = Monitor(env, os.path.join(logger.get_dir(), '0'), allow_early_resets=allow_early_resets)
env.seed(seed)
return env
def make_robotics_env(env_id, seed, rank=0, allow_early_resets=True):
"""
Create a wrapped, monitored gym.Env for MuJoCo.
:param env_id: (str) the environment ID
:param seed: (int) the inital seed for RNG
:param rank: (int) the rank of the environment (for logging)
:param allow_early_resets: (bool) allows early reset of the environment
:return: (Gym Environment) The robotic environment
"""
set_global_seeds(seed)
env = gym.make(env_id)
keys = ['observation', 'desired_goal']
# TODO: remove try-except once most users are running modern Gym
try: # for modern Gym (>=0.15.4)
from gym.wrappers import FilterObservation, FlattenObservation
env = FlattenObservation(FilterObservation(env, keys))
except ImportError: # for older gym (<=0.15.3)
from gym.wrappers import FlattenDictWrapper # pytype:disable=import-error
env = FlattenDictWrapper(env, keys)
env = Monitor(env,
logger.get_dir()
and os.path.join(logger.get_dir(), str(rank)),
info_keywords=('is_success', ),
allow_early_resets=allow_early_resets)
env.seed(seed)
return env
def _thunk():
env = make_atari(env_id)
env.seed(seed + rank)
env = Monitor(env,
logger.get_dir()
and os.path.join(logger.get_dir(), str(rank)),
allow_early_resets=allow_early_resets)
return wrap_deepmind(env, **wrapper_kwargs)
def _init():
if isinstance(env_id, str):
env = gym.make(env_id)
if len(env_kwargs) > 0:
warnings.warn("No environment class was passed (only an env ID) so `env_kwargs` will be ignored")
else:
env = env_id(**env_kwargs)
if seed is not None:
env.seed(seed + rank)
env.action_space.seed(seed + rank)
# Wrap the env in a Monitor wrapper
# to have additional training information
monitor_path = os.path.join(monitor_dir, str(rank)) if monitor_dir is not None else None
# Create the monitor folder if needed
if monitor_path is not None:
os.makedirs(monitor_dir, exist_ok=True)
env = Monitor(env, filename=monitor_path)
# Optionally, wrap the environment with the provided wrapper
if wrapper_class is not None:
env = wrapper_class(env)
return env