runtime error:permission denied

[mdh31]

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Hi
I want to run train with GPU like this.
01:00.0 VGA compatible controller: NVIDIA Corporation GA102 [GeForce RTX 3090] (rev a1)
02:00.0 VGA compatible controller: NVIDIA Corporation GA102 [GeForce RTX 3090] (rev a1)

My command line:
$ python -m torch.distributed.run --nproc_per_node 2 --master_port 1 segment/train.py --data ./data/gnrDataset_polygon.yaml --weights ~/mdh_share/yolov5s-seg.pt --img 640 --device 0,1

error log:
WARNING:main:

---

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.

---

ERROR:torch.distributed.elastic.multiprocessing.errors.error_handler:{
"message": {
"message": "RuntimeError: Permission denied",
"extraInfo": {
"py_callstack": "Traceback (most recent call last):\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 345, in wrapper\n return f(*args, **kwargs)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/run.py", line 719, in main\n run(args)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/run.py", line 710, in run\n elastic_launch(\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 131, in call\n return launch_agent(self._config, self._entrypoint, list(args))\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 252, in launch_agent\n result = agent.run()\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 125, in wrapper\n result = f(*args, **kwargs)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 709, in run\n result = self._invoke_run(role)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 837, in _invoke_run\n self._initialize_workers(self._worker_group)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 125, in wrapper\n result = f(*args, **kwargs)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 678, in _initialize_workers\n self._rendezvous(worker_group)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 125, in wrapper\n result = f(*args, **kwargs)\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 538, in _rendezvous\n store, group_rank, group_world_size = spec.rdzv_handler.next_rendezvous()\n File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/rendezvous/static_tcp_rendezvous.py", line 55, in next_rendezvous\n self._store = TCPStore( # type: ignore[call-arg]\nRuntimeError: Permission denied\n",
"timestamp": "1718680548"
}
}
}
Traceback (most recent call last):
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/run.py", line 723, in
main()
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 345, in wrapper
return f(*args, **kwargs)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/run.py", line 719, in main
run(args)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/run.py", line 710, in run
elastic_launch(
File "/home/wise/anaconda3/envs/yolov5/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/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 252, in launch_agent
result = agent.run()
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 125, in wrapper
result = f(*args, **kwargs)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 709, in run
result = self._invoke_run(role)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 837, in _invoke_run
self._initialize_workers(self._worker_group)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 125, in wrapper
result = f(*args, **kwargs)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 678, in _initialize_workers
self._rendezvous(worker_group)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/metrics/api.py", line 125, in wrapper
result = f(*args, **kwargs)
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/agent/server/api.py", line 538, in _rendezvous
store, group_rank, group_world_size = spec.rdzv_handler.next_rendezvous()
File "/home/wise/anaconda3/envs/yolov5/lib/python3.9/site-packages/torch/distributed/elastic/rendezvous/static_tcp_rendezvous.py", line 55, in next_rendezvous
self._store = TCPStore( # type: ignore[call-arg]
RuntimeError: Permission denied

Thanks a lot.

Additional

No response

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[glenn-jocher]

@mdh31 hello,

Thank you for reaching out and providing detailed information about the issue you're encountering. The "RuntimeError: Permission denied" error typically indicates that there might be a permissions issue with the port or the environment setup.

Here are a few steps to help troubleshoot and resolve this issue:

1. Check Port Permissions: Ensure that the port you are using (--master_port 1) is not restricted or already in use. You can try using a different port number, for example:

   python -m torch.distributed.run --nproc_per_node 2 --master_port 12345 segment/train.py --data ./data/gnrDataset_polygon.yaml --weights ~/mdh_share/yolov5s-seg.pt --img 640 --device 0,1

2. Run as Administrator: If you are on a Unix-based system, try running the command with sudo to ensure you have the necessary permissions:

   sudo python -m torch.distributed.run --nproc_per_node 2 --master_port 12345 segment/train.py --data ./data/gnrDataset_polygon.yaml --weights ~/mdh_share/yolov5s-seg.pt --img 640 --device 0,1

3. Update Packages: Ensure you are using the latest versions of torch and yolov5. You can update them using:

   pip install --upgrade torch
   cd yolov5
   git pull
   pip install -r requirements.txt

4. Environment Variables: Sometimes, setting the OMP_NUM_THREADS environment variable can help. You can set it to 1 before running your command:

   export OMP_NUM_THREADS=1
   python -m torch.distributed.run --nproc_per_node 2 --master_port 12345 segment/train.py --data ./data/gnrDataset_polygon.yaml --weights ~/mdh_share/yolov5s-seg.pt --img 640 --device 0,1

5. Minimum Reproducible Example: If the issue persists, please provide a minimum reproducible code example. This will help us investigate the problem more effectively. You can find more details on creating a minimum reproducible example here: Minimum Reproducible Example.

If you have tried all the above steps and the issue still exists, please let us know with any additional error logs or details. This will help us assist you better.

Thank you for your patience, and we look forward to helping you resolve this issue.