Python cmd_util.make_vec_env方法代碼示例

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_env(args):
    ncpu = multiprocessing.cpu_count()
    if sys.platform == 'darwin': ncpu //= 2
    nenv = args.num_env or ncpu
    alg = args.alg
    seed = args.seed

    env_type, env_id = get_env_type(args)
    
    config = tf.ConfigProto(allow_soft_placement=True,
                            intra_op_parallelism_threads=1,
                            inter_op_parallelism_threads=1)
    config.gpu_options.allow_growth = True
    get_session(config=config)

    flatten_dict_observations = alg not in {'her'}
    env = make_vec_env(env_id, env_type, args.num_env or 1, seed, reward_scale=args.reward_scale, flatten_dict_observations=flatten_dict_observations)

    if env_type == 'mujoco':
        env = VecNormalize(env)

    return env 

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_env(args):

    alg = args.alg
    seed = args.seed

    # tf config
    config = tf.ConfigProto(allow_soft_placement=True,
                            intra_op_parallelism_threads=1,
                            inter_op_parallelism_threads=1)
    config.gpu_options.allow_growth = True
    get_session(config=config)

    flatten_dict_observations = alg not in {'her'}

    env = make_vec_env('MujocoQuadForce-v1',
                       'mujoco',
                       args.num_env or 1,
                       seed,
                       reward_scale=args.reward_scale,
                       flatten_dict_observations=flatten_dict_observations)
    # env = ActionClipWrapper(env)

    # if env_type == 'mujoco':
    #     env = VecNormalize(env)

    return env 

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_env(args):
    ncpu = multiprocessing.cpu_count()
    if sys.platform == 'darwin': ncpu //= 2
    nenv = args.num_env or ncpu
    alg = args.alg
    seed = args.seed

    env_type, env_id = get_env_type(args.env)

    if env_type in {'atari', 'retro'}:
        if alg == 'deepq':
            env = make_env(env_id, env_type, seed=seed, wrapper_kwargs={'frame_stack': True})
        elif alg == 'trpo_mpi':
            env = make_env(env_id, env_type, seed=seed)
        else:
            frame_stack_size = 4
            env = make_vec_env(env_id, env_type, nenv, seed, gamestate=args.gamestate, reward_scale=args.reward_scale)
            env = VecFrameStack(env, frame_stack_size)

    else:
       config = tf.ConfigProto(allow_soft_placement=True,
                               intra_op_parallelism_threads=1,
                               inter_op_parallelism_threads=1)
       config.gpu_options.allow_growth = True
       get_session(config=config)

       flatten_dict_observations = alg not in {'her'}
       env = make_vec_env(env_id, env_type, args.num_env or 1, seed, reward_scale=args.reward_scale, flatten_dict_observations=flatten_dict_observations)

       if env_type == 'mujoco':
           env = VecNormalize(env)

    return env 

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_env(args):
    ncpu = multiprocessing.cpu_count()
    if sys.platform == 'darwin': ncpu //= 2
    nenv = args.num_env or ncpu
    alg = args.alg
    seed = args.seed

    env_type, env_id = get_env_type(args)

    if env_type in {'atari', 'retro'}:
        if alg == 'deepq':
            env = make_env(env_id, env_type, seed=seed, wrapper_kwargs={'frame_stack': True})
        elif alg == 'trpo_mpi':
            env = make_env(env_id, env_type, seed=seed)
        else:
            frame_stack_size = 4
            env = make_vec_env(env_id, env_type, nenv, seed, gamestate=args.gamestate, reward_scale=args.reward_scale)
            env = VecFrameStack(env, frame_stack_size)

    else:
        config = tf.ConfigProto(allow_soft_placement=True,
                               intra_op_parallelism_threads=1,
                               inter_op_parallelism_threads=1)
        config.gpu_options.allow_growth = True
        get_session(config=config)

        flatten_dict_observations = alg not in {'her'}
        env = make_vec_env(env_id, env_type, args.num_env or 1, seed, reward_scale=args.reward_scale, flatten_dict_observations=flatten_dict_observations)

        if env_type == 'mujoco':
            env = VecNormalize(env, use_tf=True)

    return env 

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_testenv(args):
    ncpu = multiprocessing.cpu_count()
    if sys.platform == 'darwin': ncpu //= 2
    seed = args.seed

    env_type, env_id = get_env_type('RLTestStock-v0')

    get_session(tf.ConfigProto(allow_soft_placement=True,
                                intra_op_parallelism_threads=1,
                                inter_op_parallelism_threads=1))

    env = make_vec_env(env_id, env_type, args.num_env or 1, seed, reward_scale=args.reward_scale)

    return env 

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_env(args):
    ncpu = multiprocessing.cpu_count()
    if sys.platform == 'darwin': ncpu //= 2
    nenv = args.num_env or ncpu
    alg = args.alg
    seed = args.seed

    env_type, env_id = get_env_type(args.env)

    if env_type in {'atari', 'retro'}:
        if alg == 'deepq':
            env = make_env(env_id, env_type, seed=seed, wrapper_kwargs={'frame_stack': True})
        elif alg == 'trpo_mpi':
            env = make_env(env_id, env_type, seed=seed)
        else:
            frame_stack_size = 4
            env = make_vec_env(env_id, env_type, nenv, seed, gamestate=args.gamestate, reward_scale=args.reward_scale)
            env = VecFrameStack(env, frame_stack_size)

    else:
       config = tf.ConfigProto(allow_soft_placement=True,
                               intra_op_parallelism_threads=1,
                               inter_op_parallelism_threads=1)
       config.gpu_options.allow_growth = True
       get_session(config=config)

       env = make_vec_env(env_id, env_type, args.num_env or 1, seed, reward_scale=args.reward_scale)

    if args.custom_reward != '':
        from baselines.common.vec_env import VecEnv, VecEnvWrapper
        import baselines.common.custom_reward_wrapper as W
        assert isinstance(env,VecEnv) or isinstance(env,VecEnvWrapper)

        custom_reward_kwargs = eval(args.custom_reward_kwargs)

        if args.custom_reward == 'live_long':
            env = W.VecLiveLongReward(env,**custom_reward_kwargs)
        elif args.custom_reward == 'random_tf':
            env = W.VecTFRandomReward(env,**custom_reward_kwargs)
        elif args.custom_reward == 'preference':
            env = W.VecTFPreferenceReward(env,**custom_reward_kwargs)
        elif args.custom_reward == 'preference_normalized':
            env = W.VecTFPreferenceRewardNormalized(env,**custom_reward_kwargs)
        else:
            assert False, 'no such wrapper exist'

    if env_type == 'mujoco':
        env = VecNormalize(env)

    return env 

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_env(args):
    ncpu = multiprocessing.cpu_count()
    if sys.platform == 'darwin': ncpu //= 2
    nenv = args.num_env or ncpu
    alg = args.alg
    seed = args.seed

    env_type, env_id = get_env_type(args.env)

    print(env_id)
    #extract the agc_env_name
    noskip_idx = env_id.find("NoFrameskip")
    env_name = env_id[:noskip_idx].lower()
    print("Env Name for Masking:", env_name)

    if env_type in {'atari', 'retro'}:
        if alg == 'deepq':
            env = make_env(env_id, env_type, seed=seed, wrapper_kwargs={'frame_stack': True})
        elif alg == 'trpo_mpi':
            env = make_env(env_id, env_type, seed=seed)
        else:
            frame_stack_size = 4
            env = make_vec_env(env_id, env_type, nenv, seed, gamestate=args.gamestate, reward_scale=args.reward_scale)
            env = VecFrameStack(env, frame_stack_size)

    else:
       config = tf.ConfigProto(allow_soft_placement=True,
                               intra_op_parallelism_threads=1,
                               inter_op_parallelism_threads=1)
       config.gpu_options.allow_growth = True
       get_session(config=config)

       env = make_vec_env(env_id, env_type, args.num_env or 1, seed, reward_scale=args.reward_scale)

    if args.custom_reward != '':
        from baselines.common.vec_env import VecEnv, VecEnvWrapper
        import baselines.common.custom_reward_wrapper as W
        assert isinstance(env,VecEnv) or isinstance(env,VecEnvWrapper)

        custom_reward_kwargs = eval(args.custom_reward_kwargs)

        if args.custom_reward == 'pytorch':
            if args.custom_reward_path == '':
                assert False, 'no path for reward model'
            else:
                env = W.VecPyTorchAtariReward(env, args.custom_reward_path, env_name)
        else:
            assert False, 'no such wrapper exist'

    if env_type == 'mujoco':
        env = VecNormalize(env)
    # if env_type == 'atari':
    #     input("Normalizing for ATari game: okay? [Enter]")
    #     #normalize rewards but not observations for atari
    #     env = VecNormalizeRewards(env)

    return env 

# 需要導入模塊: from baselines.common import cmd_util [as 別名]
# 或者: from baselines.common.cmd_util import make_vec_env [as 別名]
def build_env(args):
    ncpu = multiprocessing.cpu_count()
    if sys.platform == 'darwin': ncpu //= 2
    nenv = args.num_env or ncpu
    alg = args.alg
    rank = MPI.COMM_WORLD.Get_rank() if MPI else 0
    seed = args.seed

    env_type, env_id = get_env_type(args.env)

    if env_type == 'atari':
        if alg == 'acer':
            env = make_vec_env(env_id, env_type, nenv, seed)
        elif alg == 'deepq':
            env = atari_wrappers.make_atari(env_id)
            env.seed(seed)
            env = bench.Monitor(env, logger.get_dir())
            env = atari_wrappers.wrap_deepmind(env, frame_stack=True)
        elif alg == 'trpo_mpi':
            env = atari_wrappers.make_atari(env_id)
            env.seed(seed)
            env = bench.Monitor(env, logger.get_dir() and osp.join(logger.get_dir(), str(rank)))
            env = atari_wrappers.wrap_deepmind(env)
            # TODO check if the second seeding is necessary, and eventually remove
            env.seed(seed)
        else:
            frame_stack_size = 4
            env = VecFrameStack(make_vec_env(env_id, env_type, nenv, seed), frame_stack_size)

    elif env_type == 'retro':
        import retro
        gamestate = args.gamestate or retro.State.DEFAULT
        env = retro_wrappers.make_retro(game=args.env, state=gamestate, max_episode_steps=10000,
                                        use_restricted_actions=retro.Actions.DISCRETE)
        env.seed(args.seed)
        env = bench.Monitor(env, logger.get_dir())
        env = retro_wrappers.wrap_deepmind_retro(env)

    else:
       get_session(tf.ConfigProto(allow_soft_placement=True,
                                   intra_op_parallelism_threads=1,
                                   inter_op_parallelism_threads=1))

       env = make_vec_env(env_id, env_type, args.num_env or 1, seed, reward_scale=args.reward_scale)

       if env_type == 'mujoco':
           env = VecNormalize(env)

    return env