create a new environment using Shichao's wrapper update

[YangyangFu]

class Gym_Wrapper(gym.Wrapper):
    def __init__(self, env):
        super(Gym_Wrapper, self).__init__(env)
        self.h = np.array([86400., 273.15+30, 273.15+40,1200., 1000.]+[273.15+40]*3+[1200.]*3 + [args.num_of_days*24*3600.0])
        self.l = np.array([0., 273.15+12, 273.15+0,0, 0]+[273.15+0]*3+[0.0]*3 + [0.0])
        self.time_cnt = 0.0
        self.state_dim = self.env.observation_space.shape[0] + 1
        self.action_n = self.env.action_space.n
    def step(self, action):
        ob, r, d, info = self.env.step(action)
        self.time_cnt += args.time_step
        ob = np.append(ob, [self.time_cnt])
        ob = (ob - self.l)/(self.h-self.l)
        #print(ob)
        return ob, r, d, info
    def reset(self):
        self.time_cnt = 0.0
        ob = self.env.reset()
        ob = np.append(ob, [self.time_cnt])
        ob = (ob - self.l)/(self.h-self.l)
        return ob
    def get_cost(self):
        return self.env.get_cost()
1:29
env = make_building_env(args)
env = Gym_Wrapper(env)

[mingzhe37]

@YangyangFu Have ever tried if this wrapper approach works? This runs into an error if I use Ray to run the simulation using a similar wrapper.

Failure # 1 (occurred at 2023-11-27_22-57-21)
Traceback (most recent call last):
File "/opt/conda/lib/python3.8/site-packages/ray/tune/trial_runner.py", line 893, in _process_trial
results = self.trial_executor.fetch_result(trial)
File "/opt/conda/lib/python3.8/site-packages/ray/tune/ray_trial_executor.py", line 707, in fetch_result
result = ray.get(trial_future[0], timeout=DEFAULT_GET_TIMEOUT)
File "/opt/conda/lib/python3.8/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/ray/worker.py", line 1733, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(TuneError): �[36mray::ImplicitFunc.train()�[39m (pid=178, ip=172.17.0.2, repr=trainable_function)
File "/opt/conda/lib/python3.8/site-packages/ray/tune/trainable.py", line 315, in train
result = self.step()
File "/opt/conda/lib/python3.8/site-packages/ray/tune/function_runner.py", line 381, in step
self._report_thread_runner_error(block=True)
File "/opt/conda/lib/python3.8/site-packages/ray/tune/function_runner.py", line 531, in _report_thread_runner_error
raise TuneError(
ray.tune.error.TuneError: Trial raised an exception. Traceback:
�[36mray::ImplicitFunc.train()�[39m (pid=178, ip=172.17.0.2, repr=trainable_function)
File "/opt/conda/lib/python3.8/site-packages/ray/tune/function_runner.py", line 262, in run
self._entrypoint()
File "/opt/conda/lib/python3.8/site-packages/ray/tune/function_runner.py", line 330, in entrypoint
return self._trainable_func(self.config, self._status_reporter,
File "/opt/conda/lib/python3.8/site-packages/ray/tune/function_runner.py", line 600, in _trainable_func
output = fn()
File "/mnt/shared/test_gail_tianshou.py", line 303, in trainable_function
test_gail(args)
File "/mnt/shared/test_gail_tianshou.py", line 107, in test_gail
train_envs = SubprocVectorEnv(
File "/opt/conda/lib/python3.8/site-packages/tianshou/env/venvs.py", line 394, in init
super().init(env_fns, worker_fn, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/tianshou/env/venvs.py", line 80, in init
self.workers = [worker_fn(fn) for fn in env_fns]
File "/opt/conda/lib/python3.8/site-packages/tianshou/env/venvs.py", line 80, in
self.workers = [worker_fn(fn) for fn in env_fns]
File "/opt/conda/lib/python3.8/site-packages/tianshou/env/venvs.py", line 392, in worker_fn
return SubprocEnvWorker(fn, share_memory=False)
File "/opt/conda/lib/python3.8/site-packages/tianshou/env/worker/subproc.py", line 162, in init
super().init(env_fn)
File "/opt/conda/lib/python3.8/site-packages/tianshou/env/worker/base.py", line 19, in init
self.action_space = self.get_env_attr("action_space") # noqa: B009
File "/opt/conda/lib/python3.8/site-packages/tianshou/env/worker/subproc.py", line 166, in get_env_attr
return self.parent_remote.recv()
File "/opt/conda/lib/python3.8/multiprocessing/connection.py", line 250, in recv
buf = self._recv_bytes()
File "/opt/conda/lib/python3.8/multiprocessing/connection.py", line 414, in _recv_bytes
buf = self._recv(4)
File "/opt/conda/lib/python3.8/multiprocessing/connection.py", line 379, in _recv
chunk = read(handle, remaining)
ConnectionResetError: [Errno 104] Connection reset by peer

[YangyangFu]

@mingzhe37 I didn't. It seems this env SubprocVectorEnv not working. Maybe isolate the issue to debug?