Error when I run on a single node with 8 gpus #44
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were you able to fix this error? I'm running into something similar |
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(Minseok) ubuntu@DESKTOP-SMIU2JP:~/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main$ python -m torch.distributed.launch --nproc_per_node=8 --use_env main.py --dataset_config configs/pretrain.json --ema --backbone timm_tf_efficientnet_b3_ns --lr_backbone 5e-5 /home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated and will be removed in future. Use torchrun. Note that --use_env is set by default in torchrun. If your script expects--local_rankargument to be set, please change it to read fromos.environ['LOCAL_RANK']` instead. Seehttps://pytorch.org/docs/stable/distributed.html#launch-utility for
further instructions
warnings.warn(
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.
| distributed init (rank 0): env://
Traceback (most recent call last):
Traceback (most recent call last):
Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 643, in
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 643, in
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 643, in
Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 643, in
main(args) main(args)main(args)
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 281, in main
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 281, in main
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 281, in main
Traceback (most recent call last):
main(args)Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 643, in
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 643, in
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 281, in main
dist.init_distributed_mode(args)dist.init_distributed_mode(args)
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/util/dist.py", line 220, in init_distributed_mode
dist.init_distributed_mode(args)Traceback (most recent call last):
dist.init_distributed_mode(args)
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/util/dist.py", line 220, in init_distributed_mode
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 643, in
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/util/dist.py", line 220, in init_distributed_mode
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/util/dist.py", line 220, in init_distributed_mode
torch.cuda.set_device(args.gpu)
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/cuda/init.py", line 311, in set_device
torch.cuda.set_device(args.gpu)torch.cuda.set_device(args.gpu)main(args)main(args)torch.cuda.set_device(args.gpu)
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/cuda/init.py", line 311, in set_device
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 281, in main
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/cuda/init.py", line 311, in set_device
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 281, in main
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/cuda/init.py", line 311, in set_device
main(args)torch._C._cuda_setDevice(device)
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/main.py", line 281, in main
RuntimeError torch._C._cuda_setDevice(device): torch._C._cuda_setDevice(device)torch._C._cuda_setDevice(device)CUDA error: invalid device ordinal
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
dist.init_distributed_mode(args)dist.init_distributed_mode(args)
RuntimeError
RuntimeError
RuntimeErrordist.init_distributed_mode(args): : File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/util/dist.py", line 220, in init_distributed_mode
CUDA error: invalid device ordinal
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.: File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/util/dist.py", line 220, in init_distributed_mode
CUDA error: invalid device ordinal
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.CUDA error: invalid device ordinal
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
File "/home/ubuntu/anaconda3/envs/Minseok/Portfolio/TeamProject/mdetr-main/util/dist.py", line 220, in init_distributed_mode
torch.cuda.set_device(args.gpu)torch.cuda.set_device(args.gpu)torch.cuda.set_device(args.gpu)
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/cuda/init.py", line 311, in set_device
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/cuda/init.py", line 311, in set_device
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/cuda/init.py", line 311, in set_device
torch._C._cuda_setDevice(device)torch._C._cuda_setDevice(device)
: CUDA error: invalid device ordinal
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.CUDA error: invalid device ordinal
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.RuntimeError
: CUDA error: invalid device ordinal
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 8606 closing signal SIGTERM
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 1 (pid: 8607) of binary: /home/ubuntu/anaconda3/envs/Minseok/bin/python
Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/distributed/launch.py", line 193, in
main()
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/distributed/launch.py", line 189, in main
launch(args)
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/distributed/launch.py", line 174, in launch
run(args)
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/distributed/run.py", line 689, in run
elastic_launch(
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 131, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "/home/ubuntu/anaconda3/envs/Minseok/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 259, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
=====================================
Root Cause:
[0]:
time: 2021-09-26_17:57:42
rank: 1 (local_rank: 1)
exitcode: 1 (pid: 8607)
error_file: <N/A>
msg: Process failed with exitcode 1
Other Failures:
[1]:
time: 2021-09-26_17:57:42
rank: 2 (local_rank: 2)
exitcode: 1 (pid: 8608)
error_file: <N/A>
msg: Process failed with exitcode 1
[2]:
time: 2021-09-26_17:57:42
rank: 3 (local_rank: 3)
exitcode: 1 (pid: 8609)
error_file: <N/A>
msg: Process failed with exitcode 1
[3]:
time: 2021-09-26_17:57:42
rank: 4 (local_rank: 4)
exitcode: 1 (pid: 8610)
error_file: <N/A>
msg: Process failed with exitcode 1
[4]:
time: 2021-09-26_17:57:42
rank: 5 (local_rank: 5)
exitcode: 1 (pid: 8611)
error_file: <N/A>
msg: Process failed with exitcode 1
[5]:
time: 2021-09-26_17:57:42
rank: 6 (local_rank: 6)
exitcode: 1 (pid: 8612)
error_file: <N/A>
msg: Process failed with exitcode 1
[6]:
time: 2021-09-26_17:57:42
rank: 7 (local_rank: 7)
exitcode: 1 (pid: 8613)
error_file: <N/A>
msg: Process failed with exitcode 1
*************************************`
I just find this error when I try to run on a single node with 8 gpus in Renet101 with Mdetr Model
it seems I got multiple errors in once and I have no idea how to fix these errors.
Can anyone help me to fix?
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