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1. unity3d ubuntu 설치
https://askubuntu.com/questions/1077816/how-to-install-unity3d-on-ubuntu-18-04
이후 터미널에 unity3d 라고 치면 실행 됨.
2. unity ml agnet 설치
//설치는 아래 두 자료 섞어 참조
//https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Installation.md
//https://www.youtube.com/watch?v=siy8qVFxwPs&list=PLctzObGsrjfwYHL1obWlVdPRbpubkuKWp&index=2
//ml agent code 다운 로드
git clone https://github.com/Unity-Technologies/ml-agents.git
//python 3.6.X 설치 _ 3.5나 3.7 안됨 반드시 3.6.X만 설치
//https://packaging.python.org/guides/installing-using-linux-tools/#installing-pip-setuptools-wheel-with-linux-package-managers
sudo apt install python3-venv python3-pip
//python3 --version 으로 python3 설치 확인
hyunoklee@hyunoklee:~/Downloads$ python3 --version
Python 3.6.7
//파이썬3 용 pip upgrade
pip3 install --upgrade pip
-> 하기만 이거 하고 다음 step 에서 ImportError: cannot import name 'main' erro 발생하는 것 같음
-> 다음 스탭서 erro 발생시 재설치 sudo python3 -m pip uninstall pip && sudo apt install python3-pip --reinstall
//필요 dependency 설치 --> 여기서 tensor flow ? mlagents-learn 도 설치 하나 ?
cd ~/ml-agents/ml-agents
pip3 install -e .
~/ml-agents/ml-agents-envs
pip3 install -e ./
reboot 후
mlagents-learn --help 실행하면 관련 명령어 나와야함.
그런데 안되면 위처럼 코드 래밸서 설치 외헤 bin 설치 하는 방법도 있음
//ml agent를 다움받은 code를 통해서가 아닌 bin으로 설치
//pip3 install mlagents
reboot 후
mlagents-learn --help 실행하면 관련 명령어 나와야함.
3. 실행 시킴
3D ball 기본예제 아래 명령어 실행시 erro 발생 원인 찾아야함.
mlagents-learn config/trainer_config.yaml --run-id=<run-identifier> --train
추가 참고 자료
https://ridohee.tistory.com/20?category=841803
https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Getting-Started-with-Balance-Ball.md
/////////
~/ml-agents$ mlagents-learn config/trainer_config.yaml --run-id=test --train
~/UnityMlBall$ mlagents-learn --train --slow trainer_config.yaml
///////
/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/trainers/learn.py:141: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
trainer_config = yaml.load(data_file)
INFO:mlagents.envs:Start training by pressing the Play button in the Unity Editor.
Process Process-1:
Traceback (most recent call last):
File "/usr/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/usr/lib/python3.6/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/envs/subprocess_environment.py", line 53, in worker
env = env_factory(worker_id)
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/trainers/learn.py", line 192, in create_unity_environment
base_port=start_port
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/envs/environment.py", line 76, in __init__
aca_params = self.send_academy_parameters(rl_init_parameters_in)
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/envs/environment.py", line 538, in send_academy_parameters
return self.communicator.initialize(inputs).rl_initialization_output
File "/home/hyunoklee/.local/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's Broadcast Hub is configured correctly
The Agents are linked to the appropriate Brains
The environment and the Python interface have compatible versions.
Traceback (most recent call last):
File "/home/hyunoklee/.local/bin/mlagents-learn", line 11, in <module>
sys.exit(main())
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/trainers/learn.py", line 262, in main
run_training(0, run_seed, options, Queue())
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/trainers/learn.py", line 88, in run_training
keep_checkpoints, lesson, env.external_brains,
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/envs/subprocess_environment.py", line 173, in external_brains
return self.envs[0].recv().payload
File "/home/hyunoklee/.local/lib/python3.6/site-packages/mlagents/envs/subprocess_environment.py", line 38, in recv
response: EnvironmentResponse = self.conn.recv()
File "/usr/lib/python3.6/multiprocessing/connection.py", line 250, in recv
buf = self._recv_bytes()
File "/usr/lib/python3.6/multiprocessing/connection.py", line 407, in _recv_bytes
buf = self._recv(4)
File "/usr/lib/python3.6/multiprocessing/connection.py", line 379, in _recv
chunk = read(handle, remaining)
ConnectionResetError: [Errno 104] Connection reset by peer