lllyasviel / lllyasviel/ControlNet
RuntimeError when training on multiple GPUs
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Description
I tried to train on multiple GPUs, but when reading the data, even if I set num_workers=0, I still get the error
RuntimeError: unable to open shared memory object
and I don't have root access, so I can't increase the openfile data.
trainer = pl.Trainer(gpus=2, precision=32, callbacks=[logger])
As soon as I change gpus to 1, training works fine. Anyone have ideas?
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Research direction
Start by reproducing the reported Trainer configuration with gpus=2, precision=32, num_workers=0, and the logger callback, then compare it with the working single-GPU case. Trace the multi-GPU data-reading path and shared-memory failure; done means multi-GPU training works without requiring root access or increased open-file limits.
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Assessment
- Tech stack
- python
- Domain
- distributed-systems, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100