using a gpu with ray locally.

[lorrp1]

Hello, im trying to understand how to use my nvidia gpu locally using the "distributed" version and ray.

torch.cuda.get_device_name(0) return the name of 1070
torch.cuda.is_available() returns True

i tried modifying "num_gpus" both on "mayberay" and "dist".
also as found on ray documentation i added ray.get_gpu_ids() which correctly returns the number on "num_gpus" of ray.int(num_gpus ..) on mayberay.py

the program works fine apparently but when i check with "watch -n 2 nvidia-smi" it does not seems to use the gtx all.

im using the example on deepCRF which uses leduc with a lower number of workers.

i can't find any solution on ray's documentation.

[EricSteinberger]

Hi!

I fear I can't help with individual ray or gpu issues; it works on my computer, so I'm not sure how to reproduce this. You might be launching more than one worker with a GPU? This could cause the program to crash. Otherwise, not sure what the issue could be.

[lorrp1]

it has never crashed it just worked without using the gpu even if i set "@ray.remote(num_cpus=1, num_gpus=1)" , i just noticed that i had a newer version of ray thats not the same its required by pokerRL[distributed].
but the result is the same.

i checked ray-project/ray#5940 and os.listdir(proc_gpus_path)) return the right value.
i have tried changing @ray.remote(...) and also with just 1 actor and setting numcpus with lower values for the actor, but either it crashes or it works without gpu.

is there any other way to use the gpu without ray?