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Fixes _compute_nproc_per_node in case of bad dist configuration #2288

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Merged
merged 1 commit into from
Oct 23, 2021
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Fixes _compute_nproc_per_node in case of bad dist configuration #2288

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2 changes: 0 additions & 2 deletions .circleci/config.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,6 @@ run_pytorch_container: &run_pytorch_container
docker run --gpus=all --rm -itd --shm-size 16G -v ${wd}:/ignite -w /ignite --name pthd << pipeline.parameters.pytorch_stable_image >>
docker exec -it pthd nvidia-smi
docker exec -it pthd ls
docker exec -it pthd /bin/bash -c "$update_pth_cmd"

run_pytorch_devel_container: &run_pytorch_devel_container
- run:
Expand All @@ -97,7 +96,6 @@ run_pytorch_devel_container: &run_pytorch_devel_container
docker run --gpus=all --rm -itd --shm-size 16G -v ${wd}:/ignite -w /ignite --name pthd << pipeline.parameters.pytorch_stable_image_devel >>
docker exec -it pthd nvidia-smi
docker exec -it pthd ls
docker exec -it pthd /bin/bash -c "$update_pth_cmd"

install_dependencies: &install_dependencies
- run:
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11 changes: 5 additions & 6 deletions ignite/distributed/comp_models/native.py
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Expand Up @@ -150,12 +150,11 @@ def _init_from_context(self) -> None:

def _compute_nproc_per_node(self) -> int:
local_rank = self.get_local_rank()
device = torch.device("cpu")
if torch.cuda.is_available():
# we manually set cuda device to local rank in order to avoid a hang on all_reduce
device = torch.device(f"cuda:{local_rank}")
tensor = torch.tensor([self.get_local_rank() + 1]).to(device)
dist.all_reduce(tensor, op=dist.ReduceOp.MAX)
# Create new cpu group to get nproc_per_node such we avoid using
# badly configured NCCL
gloo_group = dist.new_group(backend="gloo")
tensor = torch.tensor([local_rank + 1]).to("cpu")
dist.all_reduce(tensor, op=dist.ReduceOp.MAX, group=gloo_group)
return int(tensor.item())

def _get_all_hostnames(self) -> List[Tuple[str, ...]]:
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