I followed the instruction in README.md.
I successfully built docker image.
I run docker image with tow terminals as described in Run Docker image section.
The agent looks good and it waits for the environment.
When I run the environment, anything happens.
Below are my console messages for both.
Agent
root
INFO:mlagents_envs:Start training by pressing the Play button in the Unity Editor.
Traceback (most recent call last):
File "run.py", line 27, in <module>
env = ObstacleTowerEnv(args.environment_filename, docker_training=args.docker_training)
File "/srv/conda/lib/python3.6/site-packages/obstacle_tower_env.py", line 45, in __init__
timeout_wait=timeout_wait)
File "/srv/conda/lib/python3.6/site-packages/mlagents_envs/environment.py", line 69, in __init__
aca_params = self.send_academy_parameters(rl_init_parameters_in)
File "/srv/conda/lib/python3.6/site-packages/mlagents_envs/environment.py", line 491, in send_academy_parameters
return self.communicator.initialize(inputs).rl_initialization_output
File "/srv/conda/lib/python3.6/site-packages/mlagents_envs/rpc_communicator.py", line 80, in initialize
"The Unity environment took too long to respond. Make sure that :\n"
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 Academy and the External Brain(s) are attached to objects in the Scene
The environment and the Python interface have compatible versions.
Environment
+ ENV_PORT=
+ ENV_FILENAME=
+ '[' -z '' ']'
+ ENV_PORT=5005
+ '[' -z '' ']'
+ ENV_FILENAME=/home/otc/ObstacleTower/obstacletower.x86_64
+ touch otc_out.json
+ APP_PID=7
+ xvfb-run --auto-servernum '--server-args=-screen 0 640x480x24' /home/otc/ObstacleTower/obstacletower.x86_64 --port 5005 2
+ TAIL_PID=8
+ wait 7
+ tail -f otc_out.json