Comments (10)
@HassanBinHaroon
yes
it should be --dist-backend gloo (without the quote). You do not need to give quote for cmd line args
but if in your system nccl version <2.5. It should be fine to use nccl
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@HassanBinHaroon yes it should be --dist-backend gloo (without the quote). You do not need to give quote for cmd line args but if in your system nccl version <2.5. It should be fine to use nccl
@Jaiaid Thanks!
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@HassanBinHaroon
yes they should come with pytorch
yes, it should otherwise throw an error from NCCL (something like internal check error), to avoid that you have to do --dist-backend gloo
BTW have you tried actually using NCCL to run your code?
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@Jaiaid Yes, I have tried running code --dist-backend nccl. It logs the user warning that (I think) you recently added and code executes smoothly BTW.
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Thank you for the information.
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@Jaiaid I am using just SINGLE GPU for training. I am not forcefully adjusting the rank and It's -1 by default. The command that I have been using is "python main.py -b 512 --dist-backend gloo -a resnet18 imagenet/"
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@HassanBinHaroon If you use "python main.py -b 512 --dist-backend nccl -a resnet18 imagenet/" does it run smoothly?
@Jaiaid Yes, it absolutely runs smoothly.
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@HassanBinHaroon yes it should be --dist-backend gloo (without the quote). You do not need to give quote for cmd line args but if in your system nccl version <2.5. It should be fine to use nccl
@Jaiaid Does the nccl and gloo comes with PyTorch?
If yes, then how to check their availability and version?
I am checking the availability using the following commands. Is it the right procedure?
"import torch.distributed as dist
print(dist.is_available()) # Should print True if distributed is available
print(dist.is_nccl_available()) # Should print True if NCCL is available
print(dist.is_gloo_available()) # Should print True if Gloo is available
"
Moreover, I am checking the nccl version using the following command, Again, please enlighten is it correct procedure?
"print(torch.cuda.nccl.version)"
The output is (2,19,3)
Does it mean that I have to be compulsorily using --dist-backend gloo?
Please elaborate, Thanks!
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@HassanBinHaroon
If you are using one rank in one GPU than nccl backend should be fine but if there are multiple rank using a single GPU than it will be an issue. I guess I should improve the message.
In your case, are you using multiple rank/process in a single GPU machine?
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@HassanBinHaroon
If you use "python main.py -b 512 --dist-backend nccl -a resnet18 imagenet/" does it run smoothly?
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