dhyeythumar / ml-agents-with-google-colab Goto Github PK

Hi, I am trying to run Reinforcement Learning on a GPU runbox.

With your code, I could train the model on Colab, and Saturn Cloud which is similar to colab.

However, when I tried to run on my personal GPU runbox, it occured an error.

mlagents-learn -h showed the options, so I thought it is a problem with environment.

How can I handle this error?

~$ mlagents-learn config.yaml --run-id=test --env=ML-Agents-with-Google-Colab/headless_build/3DBall_example/3dball.x86_64

Version information:
ml-agents: 0.31.0.dev0,
ml-agents-envs: 0.31.0.dev0,
Communicator API: 1.5.0,
PyTorch: 1.11.0+cu102
[INFO] Learning was interrupted. Please wait while the graph is generated.
Traceback (most recent call last):
File "/home/desktop/venv/bin/mlagents-learn", line 33, in
sys.exit(load_entry_point('mlagents', 'console_scripts', 'mlagents-learn')())
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/learn.py", line 264, in main
run_cli(parse_command_line())
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/learn.py", line 260, in run_cli
run_training(run_seed, options, num_areas)
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/learn.py", line 136, in run_training
tc.start_learning(env_manager)
File "/home/desktop/ml-agents/ml-agents-envs/mlagents_envs/timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/trainer_controller.py", line 197, in start_learning
raise ex
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/trainer_controller.py", line 172, in start_learning
self._reset_env(env_manager)
File "/home/desktop/ml-agents/ml-agents-envs/mlagents_envs/timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/trainer_controller.py", line 105, in _reset_env
env_manager.reset(config=new_config)
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/env_manager.py", line 68, in reset
self.first_step_infos = self._reset_env(config)
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/subprocess_env_manager.py", line 446, in _reset_env
ew.previous_step = EnvironmentStep(ew.recv().payload, ew.worker_id, {}, {})
File "/home/desktop/ml-agents/ml-agents/mlagents/trainers/subprocess_env_manager.py", line 101, in recv
raise env_exception
mlagents_envs.exception.UnityEnvironmentException: Environment shut down with return code -6 (SIGABRT).

What is the Issue:
It always shows this message
File "/content/ml-agents/ml-agents/mlagents/trainers/subprocess_env_manager.py", line 98, in recv raise env_exception mlagents_envs.exception.UnityTimeOutException: The Unity environment took too long to respond. Make sure that : The environment does not need user interaction to launch The Agents' Behavior Parameters > Behavior Type is set to "Default" The environment and the Python interface have compatible versions.

Is it working on Local Machine:
I am able to train on my Local Windows machine with the editor. For google colab, I made a Linux Build as you mentioned and tried to train.