Python gym.wrappers.FlattenDictWrapper() Examples

The following are 13 code examples of gym.wrappers.FlattenDictWrapper(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module gym.wrappers , or try the search function .
Example #1
Source File: cmd_util.py    From lirpg with MIT License 5 votes vote down vote up 
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
Example #2
Source File: cmd_util.py    From HardRLWithYoutube with MIT License 5 votes vote down vote up 
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
Example #3
Source File: cmd_util.py    From Reinforcement_Learning_for_Traffic_Light_Control with Apache License 2.0 5 votes vote down vote up 
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
Example #4
Source File: cmd_util.py    From Reinforcement_Learning_for_Traffic_Light_Control with Apache License 2.0 5 votes vote down vote up 
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
Example #5
Source File: cmd_util.py    From Reinforcement_Learning_for_Traffic_Light_Control with Apache License 2.0 5 votes vote down vote up 
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
Example #6
Source File: cmd_util.py    From rl_graph_generation with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
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
Example #7
Source File: cmd_util.py    From DRL_DeliveryDuel with MIT License 5 votes vote down vote up 
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
Example #8
Source File: cmd_util.py    From ICML2019-TREX with MIT License 5 votes vote down vote up 
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
Example #9
Source File: cmd_util.py    From ICML2019-TREX with MIT License 5 votes vote down vote up 
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
Example #10
Source File: cmd_util.py    From pytorch-pommerman-rl with MIT License 5 votes vote down vote up 
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
Example #11
Source File: cmd_util.py    From sonic_contest with MIT License 5 votes vote down vote up 
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
Example #12
Source File: cmd_util.py    From self-imitation-learning with MIT License 5 votes vote down vote up 
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
Example #13
Source File: test_env.py    From machina with MIT License 5 votes vote down vote up 
def _make_flat(*args, **kargs):
    if "FlattenDictWrapper" in dir():
        return FlattenDictWrapper(*args, **kargs)
    return FlattenObservation(FilterObservation(*args, **kargs))