GPUs requested but none are available

[shanhaidexiamo]

my server has 8 GPUs, but when I use the trainer class and set gpus = -1, it gets the run error GPUs requested but none are available, use torch to check the gpus , get the number of gpu is 8, and cuda.is_available is true. Does any one can tell me what's wrong ?

[github-actions]

Hi! thanks for your contribution!, great first issue!

[Borda]

Mind check if you have installed CUDA version of your PT as torch.cuda.is_available()

[awaelchli]

cuda.is_available is true

@shanhaidexiamo what does
torch.cuda.device_count()
return?
cuda.is_available alone does not tell us if the gpus are visible to torch.

[kyoungrok0517]

cuda.is_available is true

@shanhaidexiamo what does
torch.cuda.device_count()
return?
cuda.is_available alone does not tell us if the gpus are visible to torch.

Sorry to interrupt but I'm experiencing the same issue. the device_count() returns 2 in my case, and I'm running on GCP instance with two V100. I had no problem with my own server so it's strange (though the GPU model is different). pytorch-lightning==0.9.0

This is the env

* CUDA:
        - GPU:
                - Tesla V100-SXM2-16GB
                - Tesla V100-SXM2-16GB
        - available:         True
        - version:           10.2
* Packages:
        - numpy:             1.18.5
        - pyTorch_debug:     False
        - pyTorch_version:   1.6.0
        - pytorch-lightning: 0.9.0
        - tqdm:              4.47.0
* System:
        - OS:                Linux
        - architecture:
                - 64bit
                - ELF
        - processor:         x86_64
        - python:            3.8.3
        - version:           #24-Ubuntu SMP Sat Sep 5 02:07:13 UTC 2020

GCP command to make the similar instance

gcloud beta compute --project <project> instances create <instance-name> --zone=us-central1-a --machine-type=n1-standard-16 --subnet=default --network-tier=PREMIUM --maintenance-policy=TERMINATE --service-account=<service_account> --scopes=https://www.googleapis.com/auth/devstorage.read_only,https://www.googleapis.com/auth/logging.write,https://www.googleapis.com/auth/monitoring.write,https://www.googleapis.com/auth/servicecontrol,https://www.googleapis.com/auth/service.management.readonly,https://www.googleapis.com/auth/trace.append --accelerator=type=nvidia-tesla-v100,count=2 --image=ubuntu-2004-focal-v20200917 --image-project=ubuntu-os-cloud --boot-disk-size=200GB --boot-disk-type=pd-standard --boot-disk-device-name=thesis-1 --no-shielded-secure-boot --shielded-vtpm --shielded-integrity-monitoring --reservation-affinity=any

[Borda]

@kyoungrok0517 mind sharing this output, just to check that you have properly installed PT and drivers...
python -c "import torch ; print(torch.cuda.device_count())"

[kyoungrok0517]

@Borda That returns 2 as expected. If I use gpus = -1 argument the lightning doesn't work as I described. But if I give the exact number of gpus (e.g. gpus = 2) it works fine. I'm using ddp as the backend.

[Borda]

@kyoungrok0517 good catch, mind sending PR?

[awaelchli]

@williamFalcon is working on the parsing of gpus for DDP. The error is most likely because they are not correctly passed to or parsed in the child process.

[kyoungrok0517]

@kyoungrok0517 good catch, mind sending PR?

Hmm... so am I late to PR? I never did this before so it'll be grateful if you guide me how it works. I make pull request even though I don't know how to fix it?? Please tell me. I'd like to help.

[stale]

This issue has been automatically marked as stale because it hasn't had any recent activity. This issue will be closed in 7 days if no further activity occurs. Thank you for your contributions, Pytorch Lightning Team!

[fishbotics]

Hi all,

[EDIT] I meant gpus=-1

I am now having the same issue. I'm running my job on a server with 8 GPUs. When I run python -c "import torch ; print(torch.cuda.device_count())" I get 8, but when I run with gpus=1 and auto_select_gpus=True, I get an error saying that there are no GPUs available.

@Borda , @awaelchli : do you know if this was ever fixed?

Thanks!