Description
When I write "python flow/visualize/visualizer_rllib.py ~/ray_results/test0629/PPO_MultiAgentlhmNetwork1POEnv-v0_f48e2fe4_2023-06-29_20-17-46cjrol_re 400 --horizon 500 --gen_emission" in the terminal, it can open the sumo-gui, but run only 1 second some errors happened.
Then I will show the errors:
2023-06-30 09:45:40,604 INFO resource_spec.py:216 -- Starting Ray with 4.69 GiB memory available for workers and up to 2.35 GiB for objects. You can adjust these settings with ray.init(memory=, object_store_memory=).
2023-06-30 09:45:41,335 INFO trainer.py:371 -- Tip: set 'eager': true or the --eager flag to enable TensorFlow eager execution
2023-06-30 09:45:41,340 INFO trainer.py:512 -- Current log_level is WARN. For more information, set 'log_level': 'INFO' / 'DEBUG' or use the -v and -vv flags.
2023-06-30 09:45:41,344 WARNING ppo.py:168 -- Using the simple minibatch optimizer. This will significantly reduce performance, consider simple_optimizer=False.
2023-06-30 09:45:44,264 INFO trainable.py:346 -- Restored from checkpoint: /home/a906/ray_results/test0629/PPO_MultiAgentlhmNetwork1POEnv-v0_f48e2fe4_2023-06-29_20-17-46cjrol_re/checkpoint_400/checkpoint-400
2023-06-30 09:45:44,264 INFO trainable.py:353 -- Current state after restoring: {'_iteration': 400, '_timesteps_total': 28777138, '_time_total': 42873.71559095383, '_episodes_total': 1777}
Traceback (most recent call last):
File "/home/a906/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/models/preprocessors.py", line 62, in check_shape
if not self._obs_space.contains(observation):
File "/home/a906/anaconda3/envs/flow/lib/python3.7/site-packages/gym-0.14.0-py3.7.egg/gym/spaces/box.py", line 102, in contains
return x.shape == self.shape and np.all(x >= self.low) and np.all(x <= self.high)
AttributeError: 'dict' object has no attribute 'shape'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "flow/visualize/visualizer_rllib.py", line 386, in
visualizer_rllib(args)
File "flow/visualize/visualizer_rllib.py", line 229, in visualizer_rllib
action = agent.compute_action(state)
File "/home/a906/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/agents/trainer.py", line 643, in compute_action
policy_id].transform(observation)
File "/home/a906/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/models/preprocessors.py", line 166, in transform
self.check_shape(observation)
File "/home/a906/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/models/preprocessors.py", line 69, in check_shape
"should be an np.array, not a Python list.", observation)
ValueError: ('Observation for a Box/MultiBinary/MultiDiscrete space should be an np.array, not a Python list.', {})
/home/a906/flow/flow/visualize/test_time_rollout/test0629_20230630-0945411688089541.3611593-0_emission.csv /home/a906/flow/flow/visualize/test_time_rollout/
So, how should I do? thank you very much!