132 lines
4.9 KiB
Python
132 lines
4.9 KiB
Python
"""
|
|
Helpers for scripts like run_atari.py.
|
|
"""
|
|
|
|
import os
|
|
try:
|
|
from mpi4py import MPI
|
|
except ImportError:
|
|
MPI = None
|
|
|
|
import gym
|
|
from gym.wrappers import FlattenDictWrapper
|
|
from baselines import logger
|
|
from baselines.bench import Monitor
|
|
from baselines.common import set_global_seeds
|
|
from baselines.common.atari_wrappers import make_atari, wrap_deepmind
|
|
from baselines.common.vec_env.subproc_vec_env import SubprocVecEnv
|
|
from baselines.common.vec_env.dummy_vec_env import DummyVecEnv
|
|
from baselines.common.retro_wrappers import RewardScaler
|
|
|
|
|
|
def make_vec_env(env_id, env_type, num_env, seed, wrapper_kwargs=None, start_index=0, reward_scale=1.0):
|
|
"""
|
|
Create a wrapped, monitored SubprocVecEnv for Atari and MuJoCo.
|
|
"""
|
|
if wrapper_kwargs is None: wrapper_kwargs = {}
|
|
mpi_rank = MPI.COMM_WORLD.Get_rank() if MPI else 0
|
|
def make_env(rank): # pylint: disable=C0111
|
|
def _thunk():
|
|
env = make_atari(env_id) if env_type == 'atari' else gym.make(env_id)
|
|
env.seed(seed + 10000*mpi_rank + rank if seed is not None else None)
|
|
env = Monitor(env,
|
|
logger.get_dir() and os.path.join(logger.get_dir(), str(mpi_rank) + '.' + str(rank)),
|
|
allow_early_resets=True)
|
|
|
|
if env_type == 'atari': return wrap_deepmind(env, **wrapper_kwargs)
|
|
elif reward_scale != 1: return RewardScaler(env, reward_scale)
|
|
else: return env
|
|
return _thunk
|
|
set_global_seeds(seed)
|
|
if num_env > 1: return SubprocVecEnv([make_env(i + start_index) for i in range(num_env)])
|
|
else: return DummyVecEnv([make_env(start_index)])
|
|
|
|
def make_mujoco_env(env_id, seed, reward_scale=1.0):
|
|
"""
|
|
Create a wrapped, monitored gym.Env for MuJoCo.
|
|
"""
|
|
rank = MPI.COMM_WORLD.Get_rank()
|
|
myseed = seed + 1000 * rank if seed is not None else None
|
|
set_global_seeds(myseed)
|
|
env = gym.make(env_id)
|
|
logger_path = None if logger.get_dir() is None else os.path.join(logger.get_dir(), str(rank))
|
|
env = Monitor(env, logger_path, allow_early_resets=True)
|
|
env.seed(seed)
|
|
if reward_scale != 1.0:
|
|
from baselines.common.retro_wrappers import RewardScaler
|
|
env = RewardScaler(env, reward_scale)
|
|
return env
|
|
|
|
def make_robotics_env(env_id, seed, rank=0):
|
|
"""
|
|
Create a wrapped, monitored gym.Env for MuJoCo.
|
|
"""
|
|
set_global_seeds(seed)
|
|
env = gym.make(env_id)
|
|
env = FlattenDictWrapper(env, ['observation', 'desired_goal'])
|
|
env = Monitor(
|
|
env, logger.get_dir() and os.path.join(logger.get_dir(), str(rank)),
|
|
info_keywords=('is_success',))
|
|
env.seed(seed)
|
|
return env
|
|
|
|
def arg_parser():
|
|
"""
|
|
Create an empty argparse.ArgumentParser.
|
|
"""
|
|
import argparse
|
|
return argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
|
|
|
|
def atari_arg_parser():
|
|
"""
|
|
Create an argparse.ArgumentParser for run_atari.py.
|
|
"""
|
|
print('Obsolete - use common_arg_parser instead')
|
|
return common_arg_parser()
|
|
|
|
def mujoco_arg_parser():
|
|
print('Obsolete - use common_arg_parser instead')
|
|
return common_arg_parser()
|
|
|
|
def common_arg_parser():
|
|
"""
|
|
Create an argparse.ArgumentParser for run_mujoco.py.
|
|
"""
|
|
parser = arg_parser()
|
|
parser.add_argument('--env', help='environment ID', type=str, default='Reacher-v2')
|
|
parser.add_argument('--seed', help='RNG seed', type=int, default=None)
|
|
parser.add_argument('--alg', help='Algorithm', type=str, default='ppo2')
|
|
parser.add_argument('--num_timesteps', type=float, default=1e6),
|
|
parser.add_argument('--network', help='network type (mlp, cnn, lstm, cnn_lstm, conv_only)', default=None)
|
|
parser.add_argument('--gamestate', help='game state to load (so far only used in retro games)', default=None)
|
|
parser.add_argument('--num_env', help='Number of environment copies being run in parallel. When not specified, set to number of cpus for Atari, and to 1 for Mujoco', default=None, type=int)
|
|
parser.add_argument('--reward_scale', help='Reward scale factor. Default: 1.0', default=1.0, type=float)
|
|
parser.add_argument('--save_path', help='Path to save trained model to', default=None, type=str)
|
|
parser.add_argument('--play', default=False, action='store_true')
|
|
return parser
|
|
|
|
def robotics_arg_parser():
|
|
"""
|
|
Create an argparse.ArgumentParser for run_mujoco.py.
|
|
"""
|
|
parser = arg_parser()
|
|
parser.add_argument('--env', help='environment ID', type=str, default='FetchReach-v0')
|
|
parser.add_argument('--seed', help='RNG seed', type=int, default=None)
|
|
parser.add_argument('--num-timesteps', type=int, default=int(1e6))
|
|
return parser
|
|
|
|
|
|
def parse_unknown_args(args):
|
|
"""
|
|
Parse arguments not consumed by arg parser into a dicitonary
|
|
"""
|
|
retval = {}
|
|
for arg in args:
|
|
assert arg.startswith('--')
|
|
assert '=' in arg, 'cannot parse arg {}'.format(arg)
|
|
key = arg.split('=')[0][2:]
|
|
value = arg.split('=')[1]
|
|
retval[key] = value
|
|
|
|
return retval
|