binary-husky / hmp2g Goto Github PK

I am using GPU to run this program, but the GPU usage is very low. How can I increase the GPU usage to make the program execute faster? What settings in the code need to be changed to make the best possible use of the GPU? 谢谢您

when I set up the docker environment, I run the command
$ docker run -itd --name hmp-$USER \ --net host \ --gpus all \ --shm-size=16G \ fuqingxu/hmp:latest
It's download speed is too slowly to finish it. I tried the common online solution of changing the Docker source, but it didn't work.
I even downloaded it for several nights without success. Can you help me solve this problem? A student eager to use the environment

I am developing a multi-agent reinforcement learning environment based your framework, and I want to deploy your docker image on WSL. However, when I enable the --gpus all option, I get the following message and the environment fails to start:

docker: Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running hook #0: error running hook: exit status 1, stdout: , stderr: Auto-detected mode as 'legacy' nvidia-container-cli: mount error: file creation failed: /var/lib/docker/overlay2/<layer hash>/merged/usr/lib/x86_64-linux-gnu/libnvidia-ml.so.1: file exists: unknown.

I found this issue on nvidia-docker that helped me solve the problem: NVIDIA/nvidia-container-toolkit#289. It says that WSL has its own cuda runtime libraries, which are injected into the container when the image is created, so the container cannot have those static libraries.

After starting the container under priviledged mode without gpu, enter the command below and create a new image, the hmp container can use gpu normally:

rm -rf /usr/lib/x86_64-linux-gnu/libcuda.so.1 /usr/lib/x86_64-linux-gnu/libnvidia-*.so.1 /usr/lib/x86_64-linux-gnu/libnvcuvid.so.1

I hope you can add this solution to your documentation for future reference. This would make it easier for me and other users who encounter the same problem. Thank you!

AssertionError: ('cannot find', 'MISSION/collective_assault')
I want to run DCA related experiments, but the above problem occurred. Do I need to write the missing file myself? Or could you provide the file. Looking forward to receiving your reply！

It seems impossible for me to download the docker image fuqingxu/hmp:latest with docker-ce......I succeeded with docker-desktop, but the NVIDIA container toolkit seems not supporting docker-desktop. The docker pulling process would get broken after several minutes or hours no matter what proxy or VPN I use. If possible could we communicate more through email? My email is [email protected] :(

Traceback (most recent call last):
File "D:\Program Files\JetBrains\PyCharm Community Edition 2019.3.5\plugins\python-ce\helpers\pydev\pydevd.py", line 1434, in _exec
pydev_imports.execfile(file, globals, locals) # execute the script
File "D:\Program Files\JetBrains\PyCharm Community Edition 2019.3.5\plugins\python-ce\helpers\pydev_pydev_imps_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "./THIRDPARTY/pymarl2/pymarl2src/main.py", line 126, in
my_main(None, config_dict, None)
File "./THIRDPARTY/pymarl2/pymarl2src/main.py", line 52, in my_main
run_REGISTRY[_config['run']](_run, config, _log)
File "D:\2023Work\1IntelligentBattle\hmp2g-master\THIRDPARTY\pymarl2\pymarl2src\run\run.py", line 52, in run
run_sequential(args=args, logger=logger)
File "D:\2023Work\1IntelligentBattle\hmp2g-master\THIRDPARTY\pymarl2\pymarl2src\run\run.py", line 85, in run_sequential
runner = r_REGISTRY[args.runner](args=args, logger=logger)
File "D:\2023Work\1IntelligentBattle\hmp2g-master\THIRDPARTY\pymarl2\pymarl2src\runners\efficient_parallel_runner.py", line 82, in init
self.remote_link_client = UnixTcpClientP2P(unix_path, obj='pickle')
File "D:\2023Work\1IntelligentBattle\hmp2g-master\UTIL\network.py", line 413, in init
self.self_unix_path = target_unix_path+'client'+uuid.uuid1().hex[:5]
TypeError: can only concatenate tuple (not "str") to tuple

target_unix_path = ('localhost', 12235)