The code is running but there are many warnings about missing libraries. I do not whether these libraries are relevant for parallelisation. Example or running the code on 8 GPUs.
Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory
libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
/mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead
warnings.warn(out)
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
[W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
The code is running but there are many warnings about missing libraries. I do not whether these libraries are relevant for parallelisation. Example or running the code on 8 GPUs.
(hydronet2) pearl061@mn1:~/swDev/hydronet_parallel$ torchrun --standalone --nnodes=1 --nproc_per_node=8 train_direct_ddp.py --savedir './test_train_ddp1' --args 'train_args.json' >log_gpu_8.txt
WARNING:torch.distributed.run:
Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'librxe-rdmav34.so': librxe-rdmav34.so: cannot open shared object file: No such file or directory libibverbs: Warning: couldn't load driver 'libmlx4-rdmav34.so': libmlx4-rdmav34.so: cannot open shared object file: No such file or directory /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) /mnt/beegfs/home/pearl061/.conda/envs/hydronet2/lib/python3.8/site-packages/torch_geometric/deprecation.py:12: UserWarning: 'data.DataLoader' is deprecated, use 'loader.DataLoader' instead warnings.warn(out) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator()) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator()) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator()) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator()) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator()) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator()) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator()) [W reducer.cpp:1251] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())